Terminal application software evaluation method and device, electronic equipment, storage medium and program product

Abstract

The invention discloses a terminal application software evaluation method and device, electronic equipment, a storage medium and a program product, and relates to the technical field of artificial intelligence. The method comprises the following steps: calculating a first cumulative fault expected value and a second cumulative fault expected value of a current evaluation time period according to an endpoint moment of the current evaluation time period by adopting a target cumulative fault detection model; calculating the reliability of the target software according to the first accumulated fault expected value and the second accumulated fault expected value; and obtaining a target evaluation result of the terminal application software based on the target software reliability of the terminal application software in the current evaluation time period. According to the technical scheme provided by the embodiment of the invention, quantitative evaluation on the reliability of the terminal application software is realized, and the evaluation efficiency and the evaluation accuracy of the terminal application software are improved, so that the software quality of the terminal application software is effectively improved.

Description

Technical Field

[0001] The present invention relates to the field of artificial intelligence technology, and in particular to a terminal application software evaluation method, device, electronic device, storage medium and program product. Background Art

[0002] As financial institutions continue to deepen their digital finance concepts, more and more traditional and emerging businesses can be processed in one stop through terminal application software, which runs on physical terminal devices. At present, the evaluation of the software quality of terminal application software often relies on manual experience, and there is a lack of specific measurement methods for the quality of terminal application software, which needs to be improved urgently. Summary of the invention

[0003] The present invention provides a terminal application software evaluation method, device, electronic device, storage medium and program product, which take into account the characteristics of tight coupling and strong association between terminal application software and terminal equipment, realize quantitative evaluation of the reliability of terminal application software, improve the evaluation efficiency and evaluation accuracy of terminal application software, and thus effectively improve the software quality of terminal application software.

[0004] According to one aspect of the present invention, a terminal application software evaluation method is provided, the method comprising:

[0005] Obtaining the current evaluation time period of the terminal application software and a pre-generated target cumulative fault detection model; wherein the target cumulative fault detection model includes a pure software cumulative fault detection sub-model and a terminal-related fault detection sub-model;

[0006] Using the target cumulative fault detection model, according to the endpoint time of the current evaluation time period, calculate a first cumulative fault expected value and a second cumulative fault expected value of the current evaluation time period;

[0007] Calculating the target software reliability of the terminal application software in the current evaluation time period according to the first cumulative failure expectation value and the second cumulative failure expectation value;

[0008] Based on the target software reliability of the terminal application software in the current evaluation time period, the terminal application software is evaluated to obtain a target evaluation result of the terminal application software.

[0009] According to another aspect of the present invention, there is provided a terminal application software evaluation device, the device comprising:

[0010] A current evaluation time period acquisition module is used to acquire the current evaluation time period of the terminal application software and a pre-generated target cumulative fault detection model; wherein the target cumulative fault detection model includes a pure software cumulative fault detection sub-model and a terminal associated fault detection sub-model;

[0011] A cumulative fault expectation value calculation module, configured to calculate a first cumulative fault expectation value and a second cumulative fault expectation value of the current evaluation time period according to the endpoint time of the current evaluation time period by using the target cumulative fault detection model;

[0012] a target software reliability calculation module, configured to calculate the target software reliability of the terminal application software according to the first cumulative failure expectation value and the second cumulative failure expectation value;

[0013] The target evaluation result generating module is used to evaluate the terminal application software based on the target software reliability to obtain the target evaluation result of the terminal application software.

[0014] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising:

[0015] at least one processor; and

[0016] a memory communicatively connected to the at least one processor; wherein,

[0017] The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the terminal application software evaluation method described in any embodiment of the present invention.

[0018] According to another aspect of the present invention, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the terminal application software evaluation method described in any embodiment of the present invention when executed.

[0019] According to another aspect of the present invention, a computer program product is provided. The computer program product includes a computer program. When the computer program is executed by a processor, the terminal application software evaluation method according to any embodiment of the present invention is implemented.

[0020] The technical solution of the embodiment of the present invention obtains the current evaluation time period of the terminal application software and a pre-generated target cumulative fault detection model, wherein the target cumulative fault detection model includes a pure software cumulative fault detection sub-model and a terminal-associated fault detection sub-model, adopts the target cumulative fault detection model, calculates the first cumulative fault expectation value and the second cumulative fault expectation value of the current evaluation time period according to the endpoint time of the current evaluation time period, calculates the target software reliability of the terminal application software in the current evaluation time period according to the first cumulative fault expectation value and the second cumulative fault expectation value, evaluates the terminal application software based on the target software reliability of the terminal application software in the current evaluation time period, and obtains the target evaluation result of the terminal application software, evaluates the terminal application software through the target cumulative fault detection model including the pure software cumulative fault detection sub-model and the terminal-associated cumulative fault detection sub-model, takes into account the characteristics of tight coupling and strong association between the terminal application software and the terminal device, realizes the quantitative evaluation of the reliability of the terminal application software, improves the evaluation efficiency and evaluation accuracy of the terminal application software, and effectively improves the software quality of the terminal application software.

[0021] It should be understood that the contents described in this section are not intended to identify the key or important features of the embodiments of the present invention, nor are they intended to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0023] Figure 1 is a flow chart of a terminal application software evaluation method provided according to Embodiment 1 of the present invention;

[0024] Figure 2 is a flow chart of a terminal application software evaluation method provided according to Embodiment 2 of the present invention;

[0025] Figure 3 This is an architecture diagram of a method for evaluating terminal application software of a financial institution provided according to Embodiment 2 of the present invention;

[0026] Figure 4 is a schematic diagram of the structure of a terminal application software evaluation device provided according to Embodiment 3 of the present invention;

[0027] Figure 5 It is a structural schematic diagram of an electronic device for implementing the terminal application software evaluation method according to an embodiment of the present invention. DETAILED DESCRIPTION

[0028] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0029] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0030] Embodiment 1

[0031] Figure 1 A flowchart of a terminal application software evaluation method provided in Embodiment 1 of the present invention. The embodiment of the present invention is applicable to the case of performing software quality evaluation on terminal application software. The method can be executed by a terminal application software evaluation device, which can be implemented in the form of hardware and / or software. The terminal application software evaluation device can be configured in an electronic device that carries a terminal application software evaluation function, such as a client, a server, or a terminal device.

[0032] See also Figure 1 The terminal application software evaluation method shown includes:

[0033] S110 : Acquire the current evaluation time period of the terminal application software and a pre-generated target cumulative fault detection model.

[0034] Terminal application software can be an application software with a strong association between software functions and terminal devices. The degree of association between general software and terminal application software and terminal devices is different. Specifically, general software can run in different types of terminal devices and can realize the software functions of general software; but terminal application software itself is generated to realize the specific functions of terminal devices, and terminal application software runs on terminal devices to realize the corresponding software functions. Compared with general software, terminal application software has a stronger association with terminal devices.

[0035] The current evaluation time period may be a time period during which the terminal application software evaluation is currently being performed. The current evaluation time period may be a time period during which the software failure occurred most recently to the current moment. The current evaluation time period may include at least one evaluation moment. The target cumulative fault detection model may be used to predict the cumulative number of faults of the terminal application software. The input data of the target cumulative fault detection model may be a certain moment, and the output data may be the expected value of the cumulative faults at that moment. The target cumulative fault detection model may be pre-generated and stored in the device. The target cumulative fault detection model includes a pure software cumulative fault detection sub-model and a terminal associated fault detection sub-model. Among them, the pure software cumulative fault detection sub-model may be used to separately characterize the change of the pure software cumulative fault detection number over time. The terminal associated software cumulative fault detection sub-model may be used to separately characterize the change relationship of the terminal associated software cumulative fault detection number over time. For the terminal application software, the two types of faults, pure software faults and terminal associated faults, are independent of each other and have no mutual dependence.

[0036] In an optional embodiment of the present invention, the terminal application software is a financial institution terminal application software.

[0037] Financial institution terminal application software usually runs on financial institution terminal devices. More and more traditional and new businesses of financial institutions have been processed in a one-stop manner through financial institution terminal application software configured on financial institution terminal devices. Financial institution terminal application software often involves a large amount of capital flow, sensitive customer information and complex business logic, which is directly related to customer property safety, customer experience and social reputation of financial institutions, and has extremely high requirements for software quality and reliability. Exemplary, financial institution terminal devices may include ATM (Automated Teller Machine, self-service teller machine), self-service business terminal or foreign currency exchange machine, etc.

[0038] This solution improves the software quality of the financial institution's terminal application software, ensures the financial institution's fund security, and improves the user experience of the financial institution's terminal application software by concretizing the terminal application software as the financial institution's terminal application software.

[0039] Specifically, the current evaluation time period of the terminal application software may be obtained. A pre-generated target cumulative fault detection model may be obtained.

[0040] S120 , using a target cumulative fault detection model, and calculating a first cumulative fault expected value and a second cumulative fault expected value of the current evaluation time period according to the endpoint time of the current evaluation time period.

[0041] The endpoint time of the current evaluation time period may include a start time and an end time. The first cumulative fault expectation value may be a predicted value of the cumulative number of faults at the start time of the current evaluation time period. The second cumulative fault expectation value may be a predicted value of the cumulative number of faults at the end time of the current evaluation time period. The first cumulative fault expectation value and the second cumulative fault expectation value are both prediction results of the target cumulative fault detection model.

[0042] Specifically, the endpoint times of the current evaluation time period can be respectively input into the target cumulative fault detection model to calculate the first cumulative fault expectation value corresponding to the start time of the current evaluation time period and the second cumulative fault expectation value corresponding to the end time of the current evaluation time period.

[0043] S130. Calculate the target software reliability of the terminal application software in the current evaluation time period according to the first cumulative failure expectation value and the second cumulative failure expectation value.

[0044] The target software reliability can be the software reliability of the terminal application software in the current evaluation period, that is, the probability that the terminal application software completes the expected software function in the current evaluation period under the specified conditions. The target software reliability can be used to quantitatively evaluate the software quality of the terminal application software in the current evaluation period.

[0045] Specifically, the software reliability calculation formula may be used to calculate the target software reliability of the terminal application software in the current evaluation time period according to the first cumulative failure expectation value and the second cumulative failure expectation value.

[0046] Exemplarily, the following formula may be used to calculate the target software reliability of the terminal application software in the current evaluation time period:

[0047]

[0048] Where R(x|t) is the target software reliability of the terminal application software in the current evaluation period; m r (t) is the first cumulative failure expectation value; m r (t+x) is the second cumulative fault expectation value; (t, t+x] is the current evaluation time period.

[0049] S140 . Evaluate the terminal application software based on the target software reliability of the terminal application software in the current evaluation time period to obtain a target evaluation result of the terminal application software.

[0050] The target evaluation result may be an evaluation result of the terminal application software in the current evaluation time period. The target evaluation result may be used to characterize the software quality of the terminal application software in the current evaluation time period. Exemplarily, the target evaluation result may include pass or fail. Wherein, if the target evaluation result is pass, it can be understood that the software quality of the terminal application software in the current evaluation time period meets the use requirements and does not need to be adjusted; if the target evaluation result is fail, it can be understood that the software quality of the terminal application software in the current evaluation time period may not meet the use requirements and may need to be adjusted.

[0051] Specifically, a preset software reliability threshold can be obtained, and the target software reliability and the preset software reliability threshold can be compared; when the target software reliability is greater than or equal to the preset software reliability threshold, the target evaluation result of the terminal application software is determined to be unsuccessful; when the target software reliability is less than the preset software reliability threshold, the target evaluation result of the terminal application software is determined to be passed. The preset software reliability threshold can be a preset lower limit of the software reliability. The preset software reliability threshold can be used to measure the software reliability of the terminal application software. The preset software reliability threshold can be preset and adjusted by the technician based on experience.

[0052] In an optional embodiment of the present invention, the terminal application software is evaluated based on the target software reliability of the terminal application software in the current evaluation time period to obtain a target evaluation result of the terminal application software, including: obtaining a preset software reliability threshold, a preset software reliability change degree threshold and the target software reliability of adjacent evaluation time periods of the current evaluation time period; comparing the target software reliability of the current evaluation time period with the preset software reliability threshold to obtain a software reliability evaluation result; calculating the difference between the target software reliability of the current evaluation time period and the target software reliability of adjacent evaluation time periods to obtain a target software reliability change degree; comparing the target software reliability change degree with the preset software reliability change degree threshold to obtain a software reliability change degree evaluation result; determining the target evaluation result of the terminal application software according to the software reliability evaluation result and the software reliability change degree evaluation result.

[0053] The software reliability evaluation result may be a comparison result between the target software reliability of the current evaluation time period and the preset software reliability threshold. The software reliability evaluation result may be used to characterize the detection result of the software reliability of the terminal application software in the current evaluation time period. Exemplarily, the software reliability evaluation result may include that the target software reliability of the current evaluation time period is greater than or equal to the preset software reliability threshold, and that the target software reliability of the current evaluation time period is less than the preset software reliability threshold. Among them, if the target software reliability of the current evaluation time period is greater than or equal to the preset software reliability threshold, it can be used to characterize that the terminal application software of the current evaluation time period has passed the evaluation in the dimension of software reliability; if the target software reliability of the current evaluation time period is less than the preset software reliability threshold, it can be used to characterize that the terminal application software of the current evaluation time period has failed the evaluation in the dimension of software reliability.

[0054] The adjacent evaluation time period may be an evaluation time period adjacent to the current evaluation time period, that is, the previous evaluation time period of the current evaluation time period. The target software reliability change degree may be the difference between the target software reliability of the current evaluation time period and the target software reliability of the adjacent evaluation time period. The target software reliability change degree may be used to evaluate the change in software reliability of the terminal application software. The preset software reliability change degree threshold may be a preset lower limit of the software reliability change degree. The preset software reliability change degree threshold may be used to measure the change in software reliability. The preset software reliability change degree threshold may be preset and adjusted by a technician based on experience. The software reliability change degree evaluation result may be a comparison result between the target software reliability change degree of the current evaluation time period and the preset software reliability change degree threshold. The software reliability change degree evaluation result may be used to characterize the detection result of the reliability change degree of the terminal application software in the current evaluation time period. Exemplarily, the software reliability change degree evaluation result may include that the target software reliability change degree of the current evaluation time period is greater than or equal to the preset software reliability change degree threshold, and the target software reliability change degree of the current evaluation time period is less than the preset software reliability change degree threshold. Among them, if the degree of change of the target software reliability in the current evaluation time period is greater than or equal to the preset software reliability threshold, it can be used to characterize that the terminal application software in the current evaluation time period has passed the evaluation in the dimension of the degree of change of software reliability; if the degree of change of the target software reliability in the current evaluation time period is less than the preset software reliability change threshold, it can be used to characterize that the terminal application software in the current evaluation time period has failed the evaluation in the dimension of the degree of change of software reliability.

[0055] Specifically, the preset software reliability threshold and the preset software reliability change degree threshold pre-set by the technician can be obtained. The target software reliability detected in the adjacent evaluation time period of the current evaluation time period can be obtained. The target software reliability of the current evaluation time period can be compared with the preset software reliability threshold. When the target software reliability of the current evaluation time period is greater than or equal to the preset software reliability threshold, it can be determined that the software reliability evaluation result of the terminal application software in the current evaluation time period is evaluated as passed in the dimension of software reliability; when the target software reliability of the current evaluation time period is less than the preset software reliability threshold, it can be determined that the software reliability evaluation result of the terminal application software in the current evaluation time period is evaluated as failed in the dimension of software reliability. The difference between the target software reliability of the current evaluation time period and the target software reliability of the adjacent evaluation time period can be calculated to obtain the change degree of the target software reliability. The target software reliability change degree and the preset software reliability change degree threshold can be compared. When the target software reliability change degree in the current evaluation time period is greater than or equal to the preset software reliability threshold, the software reliability change degree evaluation result of the terminal application software in the current evaluation time period can be determined as passed in the dimension of software reliability change degree; when the target software reliability change degree in the current evaluation time period is less than the preset software reliability change degree threshold, the software reliability change degree evaluation result of the terminal application software in the current evaluation time period can be determined as failed in the dimension of software reliability change degree. When both the software reliability evaluation result and the software reliability change degree evaluation result are passed, the target evaluation result of the terminal application software is determined to be passed; when either the software reliability evaluation result or the software reliability change degree evaluation result is failed, the target evaluation result of the terminal application software is determined to be failed.

[0056] This solution conducts a comprehensive evaluation of the terminal application software through the software reliability evaluation results and the software reliability change degree evaluation results of the terminal application software. On the basis of the software reliability of the terminal application software, the software reliability change degree of the terminal application software is considered, thereby further improving the accuracy of the terminal application software evaluation.

[0057] The technical solution of the embodiment of the present invention obtains the current evaluation time period of the terminal application software and a pre-generated target cumulative fault detection model, wherein the target cumulative fault detection model includes a pure software cumulative fault detection sub-model and a terminal-associated fault detection sub-model, adopts the target cumulative fault detection model, calculates the first cumulative fault expectation value and the second cumulative fault expectation value of the current evaluation time period according to the endpoint time of the current evaluation time period, calculates the target software reliability of the terminal application software in the current evaluation time period according to the first cumulative fault expectation value and the second cumulative fault expectation value, evaluates the terminal application software based on the target software reliability of the terminal application software in the current evaluation time period, and obtains the target evaluation result of the terminal application software, evaluates the terminal application software through the target cumulative fault detection model including the pure software cumulative fault detection sub-model and the terminal-associated cumulative fault detection sub-model, takes into account the characteristics of tight coupling and strong association between the terminal application software and the terminal device, realizes the quantitative evaluation of the reliability of the terminal application software, improves the evaluation efficiency and evaluation accuracy of the terminal application software, and effectively improves the software quality of the terminal application software.

[0058] In an optional embodiment of the present invention, the current evaluation time period is in the software testing stage or the long-term stable operation stage; accordingly, after obtaining the target evaluation result of the terminal application software, it also includes: when the target evaluation result of the terminal application software is the first target evaluation result, sending a software reliability exception notification to remind the operation and maintenance user of the terminal application software; when the current evaluation time period is in the software testing stage, and the target evaluation result of the terminal application software is the second target evaluation result, performing reinforcement testing and version backtracking on the terminal application software; when the current evaluation time period is in the long-term stable operation stage, and when it is detected that the target evaluation result of the terminal application software is the second target evaluation result, issuing an emergency warning to the operation and maintenance user of the terminal application software, and adopting risk avoidance measures to eliminate risks for the terminal application software.

[0059] The software testing phase may be a phase in which the terminal application software is tested when the terminal application software is not put online for use. The long-term stable operation phase may be a phase in which the terminal application software has been put online and has entered a long-term stable operation. In comparison, the terminal application software can be directly modified in the software testing phase; however, in the long-term stable operation phase, the stability of the terminal application software needs to be taken into account when modifying the terminal application software to ensure the user's experience of the terminal application software. The first target evaluation result may be used to characterize a situation in which the terminal application software evaluation fails. The second target evaluation result may be used to characterize another situation in which the terminal application software evaluation passes. In comparison, both the first target evaluation result and the second target evaluation result fail; the target software reliability corresponding to the first target evaluation result is higher than the software reliability of the second target evaluation result. It can be understood that the software quality corresponding to the first target evaluation result is higher than the software quality corresponding to the second target evaluation result. The software reliability abnormality notification may be used to feedback the software reliability abnormality to the operation and maintenance user to remind the operation and maintenance user of the terminal application software. The operation and maintenance user may be a user who maintains the operation of the terminal application software. Emergency warnings can provide feedback to the maintenance user of the terminal application software on abnormal software reliability, so that the maintenance user can handle the failure of the terminal application software. In comparison, both software reliability abnormality notifications and emergency warnings are abnormal notifications of the terminal application software, but the urgency of emergency warnings is higher than that of software reliability abnormality notifications. Risk avoidance measures can be used to handle failures of the terminal application software during the long-term stable operation stage of the terminal application software. Exemplary risk avoidance measures may include automatic version rollback or grayscale diversion.

[0060] Optionally, the first preset software credibility threshold, the second preset software reliability threshold, the first preset software reliability change degree threshold, the second preset software reliability threshold, and the target software reliability of the adjacent evaluation time period of the current evaluation time period can be obtained. The target software reliability of the current evaluation time period can be compared with the first preset software reliability threshold and the second preset software reliability threshold. When the target software reliability of the current evaluation time period is greater than or equal to the first preset software reliability threshold, it can be determined that the software reliability evaluation result of the terminal application software in the current evaluation time period is evaluated as passed in the dimension of software reliability. When the target software reliability of the current evaluation time period is less than the first preset software reliability threshold and greater than or equal to the second preset software reliability threshold, it can be determined that the software reliability evaluation result of the terminal application software in the current evaluation time period is evaluated as failed in the dimension of software reliability and belongs to the first software reliability evaluation result. When the target software reliability of the current evaluation time period is less than the second preset software reliability threshold, it can be determined that the software reliability evaluation result of the terminal application software in the current evaluation time period is evaluated as failed in the dimension of software reliability and belongs to the second software reliability evaluation result. The difference between the target software reliability of the current evaluation time period and the target software reliability of the adjacent evaluation time period can be calculated to obtain the target software reliability change degree. The target software reliability change degree can be compared with the first preset software reliability change degree threshold and the second preset software reliability change degree threshold. When the target software reliability change degree of the current evaluation time period is greater than or equal to the first preset software reliability threshold, it can be determined that the software reliability change degree evaluation result of the terminal application software in the current evaluation time period is evaluated as passed in the dimension of software reliability change degree. When the target software reliability change degree of the current evaluation time period is less than the first preset software reliability change degree threshold, and greater than or equal to the second preset software reliability threshold, it can be determined that the software reliability change degree evaluation result of the terminal application software in the current evaluation time period is evaluated as failed in the dimension of software reliability change degree, and belongs to the first software reliability change degree evaluation result. When the target software reliability change degree of the current evaluation time period is less than the second preset software reliability threshold, it can be determined that the software reliability change degree evaluation result of the terminal application software in the current evaluation time period is evaluated as failed in the dimension of software reliability change degree, and belongs to the second software reliability change degree evaluation result. When there is a second software reliability evaluation result or a second software reliability change degree evaluation result in the software reliability evaluation result and the software reliability change degree evaluation result, the target evaluation result of the terminal application software is determined to be the second target evaluation result.When there is a first software reliability evaluation result or a first software reliability change degree evaluation result in the software reliability evaluation results and the software reliability change degree evaluation results, and there is no second software reliability evaluation result or a second software reliability change degree evaluation result, the target evaluation result of the terminal application software is determined to be the first target evaluation result.

[0061] Specifically, after obtaining the target evaluation result of the terminal application software, when the target evaluation result of the terminal application software is the first target evaluation result, a software reliability anomaly notification can be sent to the operation and maintenance user to remind the operation and maintenance user of the terminal application software to pay attention to the terminal application software. When the current evaluation time period is in the software testing stage, and the target evaluation result of the terminal application software is the second target evaluation result, the terminal application software can be reinforced and tested and version backtracked to improve the software quality of the terminal application software. When the current evaluation time period is in the long-term stable operation stage, and when it is detected that the target evaluation result of the terminal application software is the second target evaluation result, an emergency warning can be issued to the operation and maintenance user of the terminal application software, and risk avoidance measures can be adopted to eliminate risks for the terminal application software.

[0062] This solution concretizes the application scenarios of software evaluation into the software testing stage or the long-term stable operation stage. After obtaining the evaluation results of the terminal application software, it performs graded processing according to the evaluation results of different stages and different targets, taking into account the different situations in the software testing stage and the long-term stable operation stage. On the premise of minimizing the reliability risk of the terminal application software, different processing methods are adopted for terminal application software at different evaluation levels, which improves the flexibility of risk control, takes into account the stability of the use of the terminal application software, and thus ensures the user experience of the terminal application software.

[0063] Embodiment 2

[0064] Figure 2A flowchart of a terminal application software evaluation method provided in the second embodiment of the present invention. Based on the above embodiments, the embodiment of the present invention further adds "obtaining an initial cumulative fault detection model, a pure software fault introduction function, a terminal-associated software fault introduction function, a pure software fault detection rate function, and a terminal-associated software fault detection rate function; wherein the pure software fault detection rate function and the terminal-associated software fault detection rate function are different; adjusting the initial cumulative fault detection model according to the pure software fault introduction function and the pure software fault detection rate function to obtain a pure software cumulative fault detection sub-model; and adjusting the initial cumulative fault detection model according to the terminal-associated software fault introduction function and the terminal-associated software fault detection rate function to obtain a terminal-associated software fault detection sub-model." The pure software cumulative fault detection submodel and the terminal-associated software cumulative fault detection submodel are summed to obtain a reference cumulative fault detection model; the actual historical cumulative fault values ​​at each historical evaluation moment in the historical evaluation time period are obtained, and the initial cumulative fault detection model is adjusted according to each historical evaluation moment in the historical evaluation time period and the corresponding actual historical cumulative fault values ​​to obtain a target cumulative fault detection model, which takes into account the independence of pure software faults and terminal-associated software faults, and respectively considers the introduction detection process of pure software faults and the introduction detection process of terminal-associated software faults, thereby improving the adaptability between the generated target cumulative fault detection model and the terminal application software, and further improving the accuracy of the target cumulative fault detection model. It should be noted that for the parts not described in detail in the embodiments of the present invention, reference may be made to the descriptions of other embodiments.

[0065] See also Figure 2 The terminal application software evaluation method shown includes:

[0066] S210 , obtaining an initial cumulative fault detection model, a pure software fault introduction function, a terminal-associated software fault introduction function, a pure software fault detection rate function, and a terminal-associated software fault detection rate function.

[0067] The initial cumulative fault detection model may be an initial function model determined by the cumulative number of faults. The initial cumulative fault detection model may be used to characterize the change of the cumulative number of faults over time. The pure software fault introduction function may be used to characterize the change of the pure software fault number over time. The terminal-associated software fault introduction function may be used to characterize the change of the terminal-associated software fault number over time. Optionally, the pure software fault introduction function and the terminal-associated software fault introduction function may be different. Specifically, the pure software fault introduction function and the terminal-associated fault introduction function may both be proportional to the number of software faults at a certain moment, but the change rates of the pure software fault introduction function and the terminal-associated introduction function may be different. The pure software fault detection rate function may be used to characterize the change of the pure software fault detection rate over time. The terminal-associated software fault detection rate function may be used to characterize the change of the terminal-associated software fault detection rate over time. Optionally, the pure software fault detection rate function and the terminal-associated software fault detection rate function are different. Specifically, the pure software fault detection rate function and the terminal-associated fault detection rate function may both be S-shaped trend functions; but the inflection points of the pure software fault detection rate function and the terminal-associated detection rate function are lagged.

[0068] Specifically, a preset initial cumulative fault detection model, a pure software fault introduction function, a terminal-associated software fault introduction function, a pure software fault detection rate function, and a terminal-associated software fault detection rate function may be obtained.

[0069] Exemplarily, the following formula may be used to represent the initial cumulative fault detection model:

[0070]

[0071] Where m(t) is the initial cumulative fault detection function (i.e., the initial cumulative fault detection model); a(t) is the software fault introduction function; b(t) is the software fault detection rate function; and (t, t+Δt] is the evaluation time period.

[0072] The following formula can be used to express the pure software fault introduction function:

[0073]

[0074] In the formula, a 1 (t) is a pure software fault introduction function; a 1 = pa, where a 1 is the total number of pure software faults parameter of the pure software fault introduction function, a is the total number of software faults parameter, and p is the proportion of pure software faults; α 1 Introduce the rate-of-change parameter of the function for pure software faults.

[0075] The following formula can be used to express the terminal-associated software fault introduction function:

[0076]

[0077] In the formula, a 2 (t) is a function for introducing a terminal-related software fault; a 2 =(1-p)a, where a 2 is the total number of terminal-related software failures parameter of the terminal-related software failure introduction function, a is the total number of software failures parameter, and p is the proportion of pure software failures; α 2 Introduce a rate of change parameter for the function for terminal-associated software failures.

[0078] The following formula can be used to express the pure software fault detection rate function:

[0079]

[0080] Where b 1 (t) is the pure software fault detection rate function; b 1 is the pure software fault detection rate parameter of the pure software fault detection rate function; β 1 is the rate of change parameter of the pure software fault detection rate function.

[0081] The following formula can be used to express the terminal-associated software fault detection rate function:

[0082]

[0083] Where b 2 (t) is the terminal-associated software fault detection rate function; b 2 is the terminal-associated software fault detection rate parameter of the terminal-associated software fault detection rate function; β 2 is the rate of change parameter of the terminal-associated software fault detection rate function.

[0084] S220. According to the pure software fault introduction function and the pure software fault detection rate function, the initial cumulative fault detection model is adjusted to obtain a pure software cumulative fault detection sub-model; and according to the terminal-associated software fault introduction function and the terminal-associated software fault detection rate function, the initial cumulative fault detection model is adjusted to obtain a terminal-associated software cumulative fault detection sub-model.

[0085] Specifically, the initial cumulative fault detection model can be filled according to the pure software fault introduction function and the pure software fault detection rate function to obtain a pure software cumulative fault detection sub-model, and the initial cumulative fault detection model can be filled according to the terminal-associated software fault introduction function and the terminal-associated software fault detection rate function to obtain a terminal-associated software cumulative fault detection sub-model.

[0086] Exemplarily, the following formula may be used to represent the pure software cumulative fault detection sub-model:

[0087]

[0088] In the formula, m 1 (t) is the pure software cumulative fault detection function (i.e., the pure software cumulative fault detection sub-model); (t, t+Δt] is the evaluation time period; b 1 is the pure software fault detection rate parameter of the pure software fault detection rate function; β 1 is the rate of change parameter of the pure software fault detection rate function; a 1 = pa, where a 1 is the total number of pure software faults parameter of the pure software fault introduction function, a is the total number of software faults parameter, and p is the proportion of pure software faults; α 1 Introduce the rate-of-change parameter of the function for pure software faults.

[0089] The following formula can be used to represent the terminal-associated software cumulative fault detection sub-model:

[0090]

[0091] In the formula, m 2 (t) is the terminal-associated software cumulative fault detection function (i.e., the terminal-associated software cumulative fault detection sub-model); (t, t+Δt] is the evaluation time period; b 2 is the terminal-associated software fault detection rate parameter of the terminal-associated software fault detection rate function; β 2 is the change rate parameter of the terminal-associated software fault detection rate function; a 2 =(1-p)a, where a 2 is the total number of terminal-related software faults parameter of the terminal-related software fault introduction function, a is the total number of software faults parameter of the terminal-related software fault introduction function, and p is the proportion of pure software faults; α 2 Introduce a rate of change parameter for the function for terminal-associated software failures.

[0092] S230 , summing the pure software cumulative fault detection sub-model and the terminal-associated software cumulative fault detection sub-model to obtain a reference cumulative fault detection model.

[0093] Because pure software faults and terminal-associated software faults are independent of each other, the cumulative fault count of the terminal application software can be directly determined by summing the cumulative fault count of pure software and the cumulative fault count of terminal-associated software. The reference cumulative fault detection model can be the sum of the cumulative fault detection function of pure software and the cumulative fault detection function of terminal-associated software. The reference cumulative fault detection model can be used to predict the comprehensive software fault situation of the terminal application software.

[0094] Specifically, the boundary condition m can be used 1 (0) = 0, solve the pure software cumulative fault detection sub-model to obtain the pure software cumulative fault detection sub-model. The boundary condition m can be used 2 (0) = 0, the terminal-associated software cumulative fault detection submodel is solved to obtain the terminal-associated software cumulative fault detection submodel. The pure software cumulative fault detection submodel and the terminal-associated software cumulative fault detection submodel can be summed to obtain a reference cumulative fault detection model.

[0095] Exemplarily, the following formula may be used to characterize the reference cumulative fault detection model:

[0096] m r (t) = m 1 (t)+m 2 (t);

[0097] In the formula, m r (t) is the reference cumulative fault detection function (i.e., the reference cumulative fault detection model); m 1 (t) is the pure software cumulative fault detection sub-model; m 2 (t) is the terminal-associated software cumulative fault detection sub-model.

[0098] S240. Obtain the actual value of historical cumulative faults at each historical evaluation moment in the historical evaluation time period, and adjust the reference cumulative fault detection model according to each historical evaluation moment in the historical evaluation time period and the corresponding actual value of historical cumulative faults to obtain a target cumulative fault detection model.

[0099] The historical evaluation time period may be a time period for performing terminal application software evaluation in history. The historical evaluation time period may include multiple historical evaluation moments. The historical evaluation moment may be a moment for performing terminal application software evaluation in history. The historical cumulative fault actual value may be an actual value of the cumulative fault number at the historical evaluation moment.

[0100] Specifically, the number of successful API (Application Programming Interface) requests and the number of failed executions of test cases can be detected through health check scripts, business monitoring, and user fault reporting to obtain the fault data of the terminal application software. Terminal equipment failures and human failures can be eliminated from the fault data of the terminal application software. The actual value of the historical cumulative faults corresponding to each historical evaluation moment in the historical evaluation time period can be obtained from the fault data of the terminal application software. The parameter estimation algorithm can be used to calculate the parameters of the reference cumulative fault detection model to obtain the initial parameters of the reference cumulative fault detection model. The historical evaluation moment is input into the reference cumulative fault detection model to obtain the expected value of the historical cumulative faults at each historical evaluation moment. The degree of difference between the expected value of the historical cumulative faults at each historical evaluation moment and the corresponding actual value of the historical cumulative faults can be calculated. According to the degree of difference between the expected value of the historical cumulative faults at each historical evaluation moment and the corresponding actual value of the historical cumulative faults, the initial parameters of the reference cumulative fault detection model are evaluated. When the initial parameter evaluation of the reference cumulative fault detection model passes, the reference cumulative fault detection model is determined as the target cumulative fault detection model; when the initial parameter evaluation of the reference cumulative fault detection model fails, the initial parameters of the reference cumulative fault detection model are adjusted, and the step of inputting the historical evaluation time into the reference cumulative fault detection model to obtain the expected value of the historical cumulative faults corresponding to the historical evaluation time is returned to execute until the target cumulative fault detection model is determined. The expected value of the historical cumulative faults can be the predicted value of the cumulative number of faults by the reference cumulative fault detection model at the historical evaluation time. Optionally, the degree of difference between the expected value of the historical cumulative faults and the actual value of the historical cumulative faults can be the sum of squared errors between the expected value of the historical cumulative faults and the actual value of the historical cumulative faults.

[0101] In an optional embodiment of the present invention, the initial cumulative fault detection model is adjusted according to the pure software fault introduction function and the pure software fault detection rate function to obtain the pure software cumulative fault detection sub-model, and the initial cumulative fault detection model is adjusted according to the terminal-associated software fault introduction function and the terminal-associated software fault detection rate function to obtain the terminal-associated software cumulative fault detection sub-model, including: selecting a target pure software fault introduction function in each pure software fault introduction function, selecting a target pure software fault detection rate function in each pure software fault detection rate function, selecting a target terminal-associated software fault introduction function in each terminal-associated software fault introduction function, and selecting a target terminal-associated software fault detection rate function in each terminal-associated software fault detection rate function; adjusting the initial cumulative fault detection model according to the target pure software fault introduction function and the target pure software fault detection rate function to obtain the pure software cumulative fault detection sub-model, and adjusting the initial cumulative fault detection model according to the target terminal-associated software fault introduction function and the target terminal-associated software fault detection rate function to obtain the terminal-associated software cumulative fault detection sub-model. model; adjusting the parameters of the reference cumulative fault detection model according to each historical evaluation moment and the corresponding historical cumulative fault actual value in the historical evaluation time period to obtain a target cumulative fault detection model, including: using the reference cumulative fault detection model, according to each historical evaluation moment, obtaining the historical cumulative fault expected value at each historical evaluation moment; evaluating the reference cumulative fault detection model according to the degree of difference between the historical cumulative fault expected value at each historical evaluation moment and the corresponding historical cumulative fault actual value; when the reference cumulative fault detection model evaluation fails, returning to execute the steps of selecting a target pure software fault introduction function in each pure software fault introduction function, selecting a target pure software fault detection rate function in each pure software fault detection rate function, selecting a target terminal-associated software fault introduction function in each terminal-associated software fault introduction function, and selecting a target terminal-associated software fault detection rate function in each terminal-associated software fault detection rate function, until the reference cumulative fault detection model evaluation passes or the pure software fault introduction function, the pure software fault detection rate function, the terminal-associated software fault introduction function and the terminal-associated software fault detection rate function are all selected.

[0102] The number of pure software fault introduction function, terminal-associated software fault introduction function, pure software fault detection rate function and terminal-associated software fault detection rate function is at least one. The target pure software fault introduction function may be the screening result of each pure software fault introduction function. The target pure software fault detection rate function may be the screening result of each pure software fault detection rate function. The target terminal-associated software fault introduction function may be the screening result of each terminal-associated software fault introduction function. The target terminal-associated software fault detection rate function may be the screening result of each terminal-associated software fault detection rate function.

[0103] Specifically, a target pure software fault introduction function may be selected from each pure software fault introduction function, a target pure software fault detection rate function may be selected from each pure software fault detection rate function, a target terminal-associated software fault introduction function may be selected from each terminal-associated software fault introduction function, and a target terminal-associated software fault detection rate function may be selected from each terminal-associated software fault detection rate function in a sequential or random manner. The initial cumulative fault detection model may be filled in accordance with the target pure software fault introduction function and the target pure software fault detection rate function to obtain a pure software cumulative fault detection sub-model. The initial cumulative fault detection model may be filled in accordance with the target terminal-associated software fault introduction function and the target terminal-associated software fault detection rate function to obtain a terminal-associated software cumulative fault detection sub-model. The boundary condition m may be used. 1 (0) = 0, solve the pure software cumulative fault detection sub-model to obtain the pure software cumulative fault detection function. The boundary condition m can be used 2 (0) = 0, the terminal-associated software cumulative fault detection submodel is solved to obtain the terminal-associated software cumulative fault detection function. The pure software cumulative fault detection function and the terminal-associated software cumulative fault detection function can be summed to obtain a reference cumulative fault detection model. Each historical evaluation moment can be input into the reference cumulative fault detection model, and the historical cumulative fault expected value of each historical evaluation moment can be output. The degree of difference between the historical cumulative fault expected value and the corresponding historical cumulative fault actual value at each historical evaluation moment can be calculated. The degree of difference between the historical cumulative fault expected value and the corresponding historical cumulative fault actual value at each historical evaluation moment is compared with a preset difference degree threshold. When the degree of difference between the historical cumulative fault expected value and the historical cumulative fault actual value is greater than or equal to the preset difference degree threshold, it is determined that the reference cumulative fault detection model evaluation fails; when the degree of difference between the historical cumulative fault expected value and the historical cumulative fault actual value is less than the preset difference degree threshold, it is determined that the reference cumulative fault detection model evaluation passes. When the reference cumulative fault detection model evaluation fails, the steps of selecting a target pure software fault introduction function from each pure software fault introduction function, selecting a target pure software fault detection rate function from each pure software fault detection rate function, selecting a target terminal-associated software fault introduction function from each terminal-associated software fault introduction function, and selecting a target terminal-associated software fault detection rate function from each terminal-associated software fault detection rate function are returned to execute until the reference cumulative fault detection model evaluation passes or the pure software fault introduction function, pure software fault detection rate function, terminal-associated software fault introduction function, and terminal-associated software fault detection rate function are all selected.

[0104] Optionally, after the pure software fault introduction function, the pure software fault detection rate function, the terminal-associated software fault introduction function and the terminal-associated software fault detection rate function are all selected, when the initial parameter evaluation of the reference cumulative fault detection model fails, the initial parameters of the reference cumulative fault detection model can be adjusted, and the step of inputting the historical evaluation time into the reference cumulative fault detection model to obtain the expected value of the historical cumulative faults corresponding to the historical evaluation time is returned until the target cumulative fault detection model is determined.

[0105] This scheme specifies the pure software fault introduction function, terminal associated fault introduction function, pure software fault detection rate function and terminal associated fault detection function into multiple functions, and introduces the screening process and optimization process of the pure software fault introduction function, terminal associated fault introduction function, pure software fault detection rate function and terminal associated fault detection function in the target cumulative fault detection model generation process, thereby improving the adaptability of the pure software fault introduction function, terminal associated fault introduction function, pure software fault detection rate function and terminal associated fault detection function in the target cumulative fault detection model, thereby improving the accuracy of the target cumulative fault detection model, thereby improving the accuracy of the terminal application software evaluation.

[0106] S250: Acquire a current evaluation time period of the terminal application software and a pre-generated target cumulative fault detection model of the terminal application software.

[0107] Among them, the target cumulative fault detection model includes a pure software cumulative fault detection sub-model and a terminal associated fault detection sub-model.

[0108] S260: Using the target cumulative fault detection model, according to the endpoint time of the current evaluation time period, calculate the first cumulative fault expected value and the second cumulative fault expected value of the current evaluation time period.

[0109] S270: Calculate the target software reliability of the terminal application software in the current evaluation time period according to the first cumulative failure expectation value and the second cumulative failure expectation value.

[0110] S280: Evaluate the terminal application software based on the target software reliability of the terminal application software in the current evaluation time period to obtain a target evaluation result of the terminal application software.

[0111] The technical solution of the embodiment of the present invention provides a generation process of a target cumulative fault detection model, that is, the initial cumulative fault detection model is adjusted and integrated through a pure software fault introduction function, a terminal-associated software fault introduction function, a pure software fault detection rate function, and a terminal-associated software fault detection rate function to generate a target cumulative fault detection model, taking into account the independence of pure software faults and terminal-associated software faults, and considering the introduction process and detection process of pure software faults and terminal-associated software faults respectively, thereby improving the adaptability between the generated target cumulative fault detection model and the terminal application software, and further improving the accuracy of the target cumulative fault detection model.

[0112] Figure 3 This is a diagram of the architecture of a method for evaluating terminal application software of a financial institution. Figure 3 This is a preferred embodiment of the present invention. Figure 3 As shown in the figure, the terminal application software evaluation method of financial institutions mainly includes four parts: software fault data collection, terminal application software cumulative fault detection model hypothesis and model construction, software cumulative fault detection model parameter estimation, and software reliability evaluation and risk warning.

[0113] 1) Software failure data collection

[0114] In order to ensure the authenticity and reliability of software fault data collection, in the process of collecting fault data through the software testing process, the test environment of the terminal application software of the financial institution is usually simulated as much as possible to the real operating environment. Among them, the test environment can be the use environment of the terminal application software (i.e. running on a real terminal device) and load conditions. In the acceptance test phase, it is also necessary to use real terminal devices for testing to ensure the accuracy and authenticity of software fault data collection. In the software testing process and long-term stable operation process, the occurrence time of each software fault and the accumulated fault data detected at a certain moment are obtained. The number of successful API (Application Programming Interface) requests and the number of failed dial test case executions can be detected through health check scripts, business monitoring and user fault reporting to obtain the fault data of the terminal application software of the financial institution. In the fault data of the terminal application software of the financial institution, more attention should be paid to the faults of the software itself, and the faults of the terminal equipment of the financial institution such as ATMs, teller machines and foreign exchange machines and human faults such as personnel operation errors should be eliminated.

[0115] 2) Terminal application software cumulative fault detection model assumptions and model construction

[0116] Financial institutions’ terminal application software often has the following characteristics: the operating environment is strongly associated with ATMs, teller machines, foreign exchange machines, etc., is directly related to the safety of customer property, and has high requirements for software reliability. The software failure and troubleshooting process is also significantly different from that of general software. Specifically, the fault detection and troubleshooting process of financial institutions’ terminal application software usually has the following characteristics:

[0117] ① The business logic call chain of financial institution terminal application software is long, and there is a tight coupling relationship between software and hardware modules. It often runs on specific terminals such as ATMs and automatic business terminals. Some software failures are often strongly related to financial institution terminal equipment. Due to reasons such as equipment procurement cycle and software testing plan planning, the discovery time of terminal-related failures is likely to be later than the start time of software testing.

[0118] ② The testing methods for pure software faults and terminal device-related faults are often quite different in the software testing stage. Compared with pure software faults, terminal-related faults are discovered later. Fault types can be divided into two categories: pure software faults and terminal-related faults. The two fault types are discovered and debugged separately, and there is no obvious dependency between them.

[0119] ③ New faults may be introduced during the troubleshooting process. Since the troubleshooting process of terminal-related faults is quite different from that of pure software faults, the introduction of faults during the troubleshooting of the two types of faults is considered separately.

[0120] ④ With the continuous deepening of the software testing process, under the influence of the improvement of the testing efficiency of operation and maintenance users and the reduction of the total number of terminal application software failures, the software fault detection rate b(t) has an S-shaped change. Combined with the actual situation, the troubleshooting of terminal-related faults often starts after pure software faults, and there are significant differences in the troubleshooting time and process of the two. Specifically, the inflection point of the S trend curve of terminal-related faults has a significant lag, so the software fault detection rate function of the two fault types is considered separately.

[0121] In view of the characteristics of such terminal application software, taking into account the changes in the total number of potential faults of the terminal application software, whether the discovered faults have been perfectly repaired, whether new faults have been introduced, and the correlation between faults, we obtain model assumptions that meet the characteristics of the terminal application software and further construct a reference cumulative fault detection model. Based on the above analysis, the following assumptions for the reference cumulative fault detection model are proposed for the terminal application software of financial institutions:

[0122] ① The testing environment and operating environment of financial institution terminal application software are similar.

[0123] ② The faults in the program are divided into two categories: pure software faults and terminal-related faults. At time t, the number of pure software faults that can be detected per unit time is proportional to the number of pure software faults introduced into the terminal application software of the financial institution, and the number of terminal-related faults that can be detected per unit time is proportional to the number of terminal-related faults introduced.

[0124] ③ There is no mutual dependence between pure software failure and terminal-related failure.

[0125] ④ Whenever a fault occurs, the fault that caused it will be removed immediately, that is, the fault elimination rate is 100%, but new faults may be introduced. The probability of introducing faults during pure software faults and terminal-related fault troubleshooting is different.

[0126] ⑤ The software fault detection rate changes with time, which is a non-decreasing S-shaped curve. Pure software faults and terminal-related faults consider their own software fault detection rates respectively.

[0127] At the time of historical evaluation, the total number of faults in the terminal application software of financial institutions (a) is pure software faults (a 1 ) and terminal related failures (a 2 ). The software fault detection rate of the financial institution terminal application software is set to b(t), using b 1 (t) and b 2 (t) represent the changing trends of the fault detection rates of the two types of software. Combining the assumptions of the cumulative fault detection model, we can obtain the initial pure software cumulative fault detection model and the initial terminal-related software cumulative fault detection model:

[0128] The following formula can be used to characterize the initial pure software cumulative fault detection model:

[0129]

[0130] In the formula, m 1 (t) is the initial pure software cumulative fault detection function; a 1 (t) is a pure software fault introduction function; b 1 (t) is the pure software fault detection rate function; (t, t+Δt] is the evaluation time period.

[0131] The following formula can be used to characterize the initial terminal associated software cumulative fault detection model:

[0132]

[0133] In the formula, m 2 (t) is the initial terminal associated software cumulative fault detection function; a 2 (t) is the terminal-related software fault introduction function; b 2(t) is the terminal-associated software fault detection rate function; (t, t+Δt] is the evaluation time period.

[0134] Assume that the proportion of pure software failures in the terminal application software of a financial institution to the total failures is p, that is, a 1 =pa,a 2 =(1-p)a, where a 1 is the total number of pure software failures, a is the total number of software failures, and p is the proportion of pure software failures.

[0135] The number of pure software faults introduced should be proportional to the number of pure software faults detected. After analysis, a(t) = ae αt The function form of is more in line with the characteristics of terminal application software of financial institutions. Considering the introduction process of pure software faults and hardware-related faults respectively, the pure software fault introduction function and the terminal-related software fault introduction function can be obtained.

[0136] The following formula can be used to express the pure software fault introduction function:

[0137]

[0138] In the formula, a 1 (t) is a pure software fault introduction function; a 1 = pa, where a 1 is the total number of pure software faults parameter of the pure software fault introduction function, a is the total number of software faults parameter, and p is the proportion of pure software faults; α 1 Introduce the rate-of-change parameter of the function for pure software faults.

[0139] The following formula can be used to express the terminal-associated software fault introduction function:

[0140]

[0141] In the formula, a 2 (t) is a function for introducing a terminal-related software fault; a 2 =(1-p)a, where a 2 is the total number of terminal-related software failures parameter of the terminal-related software failure introduction function, a is the total number of software failures parameter, and p is the proportion of pure software failures; α 2 Introduce a rate of change parameter for the function for terminal-associated software failures.

[0142] The software fault detection rate of financial institution terminal application software describes the changing pattern of the software fault detection rate of financial institution terminal application software during the troubleshooting process. Referring to the actual situation of financial institution terminal software and the fault detection rate function of the general software reliability model, the following formulas can be used to represent the two types of software fault detection rate functions respectively, or other similar S-shaped trend function expressions can be used to represent the two types of software fault detection rate functions.

[0143] The following formula can be used to express the pure software fault detection rate function:

[0144]

[0145] Where b 1 (t) is the pure software fault detection rate function; b 1 is the pure software fault detection rate parameter of the pure software fault detection rate function; β 1 is the rate of change parameter of the pure software fault detection rate function.

[0146] The following formula can be used to express the terminal-associated software fault detection rate function:

[0147]

[0148] Where b 2 (t) is the terminal-associated software fault detection rate function; b 2 is the terminal-associated software fault detection rate parameter of the terminal-associated software fault detection rate function; β 2 is the rate of change parameter of the terminal-associated software fault detection rate function.

[0149] In summary, in any interval (t, t+Δt), there are pure software cumulative fault detection sub-models and terminal-associated software cumulative fault detection sub-models. The following formula can be used to represent the pure software cumulative fault detection sub-model:

[0150]

[0151] In the formula, m 1 (t) is the pure software cumulative fault detection function (i.e., the pure software cumulative fault detection sub-model); (t, t+Δt] is the evaluation time period; b 1 is the pure software fault detection rate parameter of the pure software fault detection rate function; β 1 is the rate of change parameter of the pure software fault detection rate function; a 1 = pa, where a 1 is the total number of pure software faults parameter of the pure software fault introduction function, a is the total number of software faults parameter, and p is the proportion of pure software faults; α 1 Introduce the rate-of-change parameter of the function for pure software faults.

[0152] The following formula can be used to represent the terminal-associated software cumulative fault detection sub-model:

[0153]

[0154] In the formula, m 2 (t) is the terminal-associated software cumulative fault detection function (i.e., the terminal-associated software cumulative fault detection sub-model); (t, t+Δt] is the evaluation time period; b 2 is the terminal-associated software fault detection rate parameter of the terminal-associated software fault detection rate function; β 2 is the change rate parameter of the terminal-associated software fault detection rate function; a 2 =(1-p)a, where a 2 is the total number of terminal-related software failures parameter of the terminal-related software failure introduction function, a is the total number of software failures parameter, and p is the proportion of pure software failures; α 2 Introduce a rate of change parameter for the function for terminal-associated software failures.

[0155] The reference cumulative fault detection model of the terminal application software of a financial institution can be the sum of the pure software cumulative fault detection sub-model and the terminal-related software cumulative fault detection sub-model. The boundary condition m can be used. 1 (0) = 0, solve the pure software cumulative fault detection sub-model to obtain the pure software cumulative fault detection function. The boundary condition m can be used 2 (0)=0, the terminal-associated software cumulative fault detection sub-model is solved to obtain the terminal-associated software cumulative fault detection function.

[0156] The reference cumulative fault detection model can be characterized by the following formula:

[0157] m r (t) = m 1 (t)+m 2 (t);

[0158] In the formula, m r (t) is the reference cumulative fault detection function; m 1 (t) is the pure software cumulative fault detection function; m 2 (t) is the cumulative fault detection function of the terminal-associated software.

[0159] For specific financial institution terminal application software, if the above model assumptions are significantly different, the constructed cumulative fault detection model can be flexibly adjusted. Specifically, if the software function logic of the financial institution terminal application software is relatively simple, software testing and hardware terminal testing can be carried out at the same time, and terminal-related faults can be ignored (i.e., m 2(t) case), only pure software faults are considered. According to the fitting of real fault data and the comparison of actual application scenarios, the function expressions of software fault number a(t) and software fault detection rate b(t) can be adjusted. For example, other trend-similar S-shaped function expressions can be used to continuously optimize and improve based on the above model construction method.

[0160] 3) Parameter estimation of software cumulative fault detection model

[0161] Use the actual fault data of terminal application software for data fitting and parameter estimation, so that the change trend of the software cumulative fault detection model is most consistent with the actual fault data. There are many parameter estimation methods, and various mathematical analysis tools can be used for data fitting to estimate the unknown parameters in the cumulative fault detection model of financial institution terminal application software. Exemplarily, parameter estimation methods may include maximum likelihood estimation and least squares estimation.

[0162] Exemplarily, the least squares estimation can be used to solve the unknown parameters in the cumulative fault detection model. The sum of squared errors (SSE) can be used to evaluate the matching degree between the expected value of the cumulative fault detection model and the actual fault data.

[0163] Exemplarily, the following formula may be used to represent the sum of squared errors:

[0164]

[0165] Where SSE is the sum of squared errors; n is the number of evaluation moments corresponding to the fault data; y i is the actual value of historical accumulated faults; m r (t i ) is the expected value of historical cumulative failures; t i Assess the moment for history.

[0166] 4) Software reliability evaluation and risk warning

[0167] According to the constructed cumulative fault detection model of financial institution terminal application software, the cumulative number of faults of financial institution terminal application software can be solved, and then the software reliability (R) and other indicators of the terminal application software can be solved to evaluate the software quality of the terminal application software.

[0168] The following formula can be used to calculate the target software reliability of the terminal application software in the current evaluation period:

[0169]

[0170] Where R(x|t) is the target software reliability of the terminal application software in the current evaluation period; m r(t) is the first cumulative failure expectation value; m r (t+x) is the second cumulative fault expectation value; (t, t+x] is the current evaluation time period.

[0171] In the specific application process, a reasonable preset software reliability threshold can be formulated in combination with the reliability requirements and reliability assessment results of the financial institutions for the terminal application software to guide the development process of the terminal application software, such as testing, troubleshooting and version release quality requirements. Optionally, a reasonable preset software reliability threshold can be set according to the reliability requirements of the specific project to evaluate the gap between the software quality and the target of the terminal application software. According to the gap between the target software reliability of the terminal application software and the preset software reliability threshold or the degree of recent software reliability changes, different graded warning and processing strategies can be used for risk avoidance. If the software quality assessment of the terminal application software is completed in the software testing phase, it can guide the implementation of software testing, development and version release quality assessment; if the software quality assessment of the terminal application software is completed in the operation phase (i.e., the long-term stable operation phase), timely warnings can be issued to notify the operation and maintenance users to focus on key risks.

[0172] If the target evaluation result of software reliability is lower than the preset threshold, the version release will be postponed, or the problems existing in the testing and troubleshooting process will be adjusted, and the software testing and troubleshooting iteration process will be carried out again. When the software has entered the long-term stable operation stage, it can also be combined with automatic detection and customer fault reporting to dynamically detect various reliability indicators of financial institution terminal application software. If it is found that the reliability indicator is in a state of gradual deterioration, an alarm will be issued in time to notify the operation and maintenance user to intervene in a comprehensive analysis and focus on risks. The software reliability risk classification warning system can be implemented. According to the gap between the target software reliability of the terminal application software in the current evaluation period and the preset software reliability threshold or the change degree of the target software reliability of the current evaluation period compared with the target software reliability of the previous iteration cycle (i.e., the adjacent evaluation period), different risk warning and elimination measures are adopted to minimize the reliability risk of financial institution terminal application software. Specifically, if there is a small gap between the target software reliability of the financial institution terminal application software in the current evaluation period and the preset software reliability threshold required by the project, or there is a small reliability decline, the operation and maintenance user will be notified through a system message prompt to pay attention. There is a large gap or a significant decrease in reliability between the target software reliability of the financial institution's terminal application software in the current evaluation period and the preset software reliability threshold required by the project, and notification will be made through prominent means such as SMS or email. There is a significant gap or a significant decrease in reliability between the target software reliability of the financial institution's terminal application software in the current evaluation period and the preset software reliability threshold required by the project. During the software testing phase, reinforcement testing and version backtracking can be carried out in a timely manner according to the preset strategy; during the long-term stable operation phase, emergency alarms or automatic activation of risk avoidance measures (such as automatic version rollback or grayscale drainage, etc.) can be used for risk warning and elimination.

[0173] Existing software cumulative fault detection models focus more on the application software itself. During the modeling process, they rarely consider the impact of the operating environment of financial institution terminal application software running on physical or special terminal devices. There is still no cumulative fault detection model that meets the characteristics of financial institution terminal application software and is applied to the research and development process of financial institution terminal application software. The software quality evaluation of financial institution terminal application software often relies on personnel experience and judgment, and lacks specific quantitative measurement methods for software reliability.

[0174] The present invention provides a reliability evaluation and risk warning method applied to terminal application software of financial institutions. Based on the assumption of the terminal application software of financial institutions in the process of fault discovery and elimination, a mathematical model expression of the corresponding relationship between the cumulative number of faults and time is obtained, and various evaluation indicators that can quantitatively evaluate the reliability of the terminal application software of financial institutions are further obtained. According to the preset software reliability thresholds set by different software, the software quality level of the current evaluation time period is evaluated and risk warning is carried out. The reliability level of the terminal application software of financial institutions in the processes of research and development, testing, release and production can be quantitatively evaluated and risk warning can be carried out. It can improve the standardized operation of projects in the process of promoting digital finance of financial institutions, reduce the security risks of terminal application software of financial institutions, improve the risk management level, and effectively improve the software quality of terminal application software of financial institutions to ensure the property safety and user experience of customers. It is of great significance for guiding the version testing, release and risk warning process of terminal application software of financial institutions.

[0175] Embodiment 3

[0176] Figure 4 This is a schematic diagram of the structure of a terminal application software evaluation device provided in Embodiment 3 of the present invention. The embodiment of the present invention can be applied to the situation of performing software quality evaluation on terminal application software, the device can execute the terminal application software evaluation method, the device can be implemented in the form of hardware and / or software, and the device can be configured in an electronic device carrying the terminal application software evaluation function, such as a client, a server or a terminal device.

[0177] See also Figure 4 The terminal application software evaluation device shown includes: a current evaluation time period acquisition module 410, a cumulative fault expectation value calculation module 420, a target software reliability calculation module 430 and a target evaluation result generation module 440. The current evaluation time period acquisition module 410 is used to acquire the current evaluation time period of the terminal application software and a pre-generated target cumulative fault detection model; wherein the target cumulative fault detection model includes a pure software cumulative fault detection sub-model and a terminal associated fault detection sub-model; the cumulative fault expectation value calculation module 420 is used to use the target cumulative fault detection model to calculate the first cumulative fault expectation value and the second cumulative fault expectation value of the current evaluation time period according to the endpoint time of the current evaluation time period; the target software reliability calculation module 430 is used to calculate the target software reliability of the terminal application software according to the first cumulative fault expectation value and the second cumulative fault expectation value; the target evaluation result generation module 440 is used to evaluate the terminal application software based on the target software reliability to obtain the target evaluation result of the terminal application software.

[0178] The technical solution of the embodiment of the present invention obtains the current evaluation time period of the terminal application software and a pre-generated target cumulative fault detection model, wherein the target cumulative fault detection model includes a pure software cumulative fault detection sub-model and a terminal-associated fault detection sub-model, adopts the target cumulative fault detection model, calculates the first cumulative fault expectation value and the second cumulative fault expectation value of the current evaluation time period according to the endpoint time of the current evaluation time period, calculates the target software reliability of the terminal application software in the current evaluation time period according to the first cumulative fault expectation value and the second cumulative fault expectation value, evaluates the terminal application software based on the target software reliability of the terminal application software in the current evaluation time period, and obtains the target evaluation result of the terminal application software, evaluates the terminal application software through the target cumulative fault detection model including the pure software cumulative fault detection sub-model and the terminal-associated cumulative fault detection sub-model, takes into account the characteristics of tight coupling and strong association between the terminal application software and the terminal device, realizes the quantitative evaluation of the reliability of the terminal application software, improves the evaluation efficiency and evaluation accuracy of the terminal application software, and effectively improves the software quality of the terminal application software.

[0179] In an optional embodiment of the present invention, the device further includes: an initial cumulative fault detection model acquisition module, which is used to acquire the initial cumulative fault detection model, the pure software fault introduction function, the terminal-associated software fault introduction function, the pure software fault detection rate function and the terminal-associated software fault detection rate function before acquiring the current evaluation time period of the terminal application software and the pre-generated target cumulative fault detection model; wherein the pure software fault detection rate function and the terminal-associated software fault detection rate function are different; an initial cumulative fault detection model adjustment module, which is used to adjust the initial cumulative fault detection model according to the pure software fault introduction function and the pure software fault detection rate function to obtain a pure software cumulative fault detection sub-model, and According to the terminal-associated software fault introduction function and the terminal-associated software fault detection rate function, the initial cumulative fault detection model is adjusted to obtain a terminal-associated software cumulative fault detection sub-model; a reference cumulative fault detection model generation model is used to sum the pure software cumulative fault detection sub-model and the terminal-associated software cumulative fault detection sub-model to obtain a reference cumulative fault detection model; a target cumulative fault detection model generation module is used to obtain the actual value of the historical cumulative faults at each historical evaluation moment in the historical evaluation time period, and according to each of the historical evaluation moments in the historical evaluation time period and the corresponding actual value of the historical cumulative faults, the reference cumulative fault detection model is adjusted to obtain a target cumulative fault detection model.

[0180] In an optional embodiment of the present invention, the initial cumulative fault detection model adjustment module includes: a function screening unit, which is used to select a target pure software fault introduction function from each of the pure software fault introduction functions, select a target pure software fault detection rate function from each of the pure software fault detection rate functions, select a target terminal-associated software fault introduction function from each of the terminal-associated software fault introduction functions, and select a target terminal-associated software fault detection rate function from each of the terminal-associated software fault detection rate functions; an initial cumulative fault detection model adjustment unit, which is used to adjust the initial cumulative fault detection model according to the target pure software fault introduction function and the target pure software fault detection rate function to obtain a pure software cumulative fault detection sub-model, and adjust the initial cumulative fault detection model according to the target terminal-associated software fault introduction function and the target terminal-associated software fault detection rate function to obtain a terminal-associated software cumulative fault detection sub-model; the target cumulative fault detection model generation module includes: a historical cumulative fault expected value calculation unit, which is used to adopt the reference cumulative fault A detection model, according to each of the historical evaluation moments, obtains the historical cumulative fault expected value of each of the historical evaluation moments; a reference cumulative fault detection model evaluation unit, used to evaluate the reference cumulative fault detection model according to the degree of difference between the historical cumulative fault expected value and the corresponding historical cumulative fault actual value at each of the historical evaluation moments; a target cumulative fault detection model generation unit, used to return to the steps of selecting a target pure software fault introduction function from each of the pure software fault introduction functions, selecting a target pure software fault detection rate function from each of the pure software fault detection rate functions, selecting a target terminal-associated software fault introduction function from each of the terminal-associated software fault introduction functions, and selecting a target terminal-associated software fault detection rate function from each of the terminal-associated software fault detection rate functions when the reference cumulative fault detection model evaluation fails, until the reference cumulative fault detection model evaluation passes or the pure software fault introduction function, the pure software fault detection rate function, the terminal-associated software fault introduction function, and the terminal-associated software fault detection rate function are all selected.

[0181] In an optional embodiment of the present invention, the target evaluation result generation module 440 includes: a target software reliability acquisition unit, which is used to acquire a preset software reliability threshold, a preset software reliability change degree threshold and the target software reliability of the adjacent evaluation time period of the current evaluation time period; a software reliability evaluation result generation unit, which is used to compare the target software reliability of the current evaluation time period with the preset software reliability threshold to obtain a software reliability evaluation result; a target software reliability change degree calculation unit, which is used to calculate the difference between the target software reliability of the current evaluation time period and the target software reliability of the adjacent evaluation time period to obtain the target software reliability change degree; a software reliability change degree evaluation result generation unit, which is used to compare the target software reliability change degree with the preset software reliability change degree threshold to obtain a software reliability change degree evaluation result; a terminal application software evaluation unit, which is used to determine the target evaluation result of the terminal application software based on the software reliability evaluation result and the software reliability change degree evaluation result.

[0182] In an optional embodiment of the present invention, the current evaluation time period is in the software testing stage or the long-term stable operation stage; accordingly, the device also includes: a first exception handling module, which is used to send a software reliability exception notification after obtaining the target evaluation result of the terminal application software, when the target evaluation result of the terminal application software is the first target evaluation result, to remind the operation and maintenance user of the terminal application software; a second exception handling module, which is used to perform reinforcement testing and version backtracking on the terminal application software in the current evaluation time period; wherein, both the first target evaluation result and the second target evaluation result are failed; the target software reliability corresponding to the first target evaluation result is higher than the software reliability of the second target evaluation result; a third exception handling module, which is used to send an emergency warning to the operation and maintenance user of the terminal application software when the current evaluation time period is in the long-term stable operation stage, and when it is detected that the target evaluation result of the terminal application software is the second target evaluation result, and adopt risk avoidance measures to eliminate the risk of the terminal application software.

[0183] In an optional embodiment of the present invention, the terminal application software is a financial institution terminal application software.

[0184] The terminal application software evaluation device provided in the embodiment of the present invention can execute the terminal application software evaluation method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0185] In the technical solution of the embodiment of the present invention, the collected information is information and data authorized by the user or fully authorized by all parties, and the collection, storage, use, processing, transmission, provision, disclosure and application of the relevant data comply with the relevant laws, regulations and standards of the relevant countries and regions, take necessary confidentiality measures, do not violate public order and good morals, and provide corresponding operation entrances for users to choose to authorize or refuse.

[0186] Embodiment 4

[0187] According to an embodiment of the present invention, the present invention also provides an electronic device, a readable storage medium and a computer program product.

[0188] Figure 5 A schematic diagram of the structure of an electronic device 500 that can be used to implement an embodiment of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or required herein.

[0189] like Figure 5 As shown, the electronic device 500 includes at least one processor 501, and a memory connected to the at least one processor 501 in communication, such as a read-only memory (ROM) 502, a random access memory (RAM) 503, etc., wherein the memory stores a computer program that can be executed by at least one processor, and the processor 501 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 502 or the computer program loaded from the storage unit 508 to the random access memory (RAM) 503. In the RAM 503, various programs and data required for the operation of the electronic device 500 can also be stored. The processor 501, the ROM 502, and the RAM 503 are connected to each other via a bus 504. An input / output (I / O) interface 505 is also connected to the bus 504.

[0190] Multiple components in the electronic device 500 are connected to the I / O interface 505, including: an input unit 506, such as a keyboard, a mouse, etc.; an output unit 507, such as various types of displays, speakers, etc.; a storage unit 508, such as a disk, an optical disk, etc.; and a communication unit 509, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 509 allows the electronic device 500 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0191] The processor 501 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the processor 501 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, digital signal processors (DSPs), and any appropriate processors, controllers, microcontrollers, etc. The processor 501 executes the various methods and processes described above, such as the terminal application software evaluation method.

[0192] In some embodiments, the terminal application software evaluation method may be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 508. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 500 via the ROM 502 and / or the communication unit 509. When the computer program is loaded into the RAM 503 and executed by the processor 501, one or more steps of the terminal application software evaluation method described above may be performed. Alternatively, in other embodiments, the processor 501 may be configured to execute the terminal application software evaluation method in any other appropriate manner (e.g., by means of firmware).

[0193] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0194] Computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that when the computer program is executed by the processor, the functions / operations specified in the flow chart and / or block diagram are implemented. The computer program may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0195] In the context of the present invention, a computer-readable storage medium may be a tangible medium that may contain or store a computer program for use by or in combination with an instruction execution system, device or equipment. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0196] To provide interaction with a user, the systems and techniques described herein may be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices may also be used to provide interaction with the user; for example, the feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form (including acoustic input, voice input, or tactile input).

[0197] The systems and techniques described herein may be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0198] A computing system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The relationship between the client and the server is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or a cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS (Virtual Private Server) services.

[0199] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps described in the present invention can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution of the present invention can be achieved, and this document does not limit this.

[0200] The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A terminal application software evaluation method, characterized in that: The method comprises: Acquire the current evaluation time period of the terminal application software and a pre-generated target cumulative fault detection model of the terminal application software; wherein the target cumulative fault detection model includes a pure software cumulative fault detection sub-model and a terminal-related fault detection sub-model; Using the target cumulative fault detection model, according to the endpoint time of the current evaluation time period, calculate a first cumulative fault expected value and a second cumulative fault expected value of the current evaluation time period; Calculating the target software reliability of the terminal application software in the current evaluation time period according to the first cumulative failure expectation value and the second cumulative failure expectation value; Based on the target software reliability of the terminal application software in the current evaluation time period, the terminal application software is evaluated to obtain a target evaluation result of the terminal application software.

2. The method according to claim 1, characterized in that: Before obtaining the current evaluation time period of the terminal application software and the pre-generated target cumulative fault detection model, the method further includes: Obtaining an initial cumulative fault detection model, a pure software fault introduction function, a terminal-associated software fault introduction function, a pure software fault detection rate function, and a terminal-associated software fault detection rate function; wherein the pure software fault detection rate function and the terminal-associated software fault detection rate function are different; According to the pure software fault introduction function and the pure software fault detection rate function, the initial cumulative fault detection model is adjusted to obtain a pure software cumulative fault detection sub-model; and according to the terminal-associated software fault introduction function and the terminal-associated software fault detection rate function, the initial cumulative fault detection model is adjusted to obtain a terminal-associated software cumulative fault detection sub-model; Summing the pure software cumulative fault detection sub-model and the terminal-associated software cumulative fault detection sub-model to obtain a reference cumulative fault detection model; The historical cumulative fault actual value at each historical evaluation moment in the historical evaluation time period is obtained, and the reference cumulative fault detection model is adjusted according to each historical evaluation moment in the historical evaluation time period and the corresponding historical cumulative fault actual value to obtain a target cumulative fault detection model.

3. The method according to claim 2, characterized in that The adjusting the initial cumulative fault detection model according to the pure software fault introduction function and the pure software fault detection rate function to obtain the pure software cumulative fault detection sub-model, and the adjusting the initial cumulative fault detection model according to the terminal-associated software fault introduction function and the terminal-associated software fault detection rate function to obtain the terminal-associated software cumulative fault detection sub-model, include: Selecting a target pure software fault introduction function from among the pure software fault introduction functions, selecting a target pure software fault detection rate function from among the pure software fault detection rate functions, selecting a target terminal-associated software fault introduction function from among the terminal-associated software fault introduction functions, and selecting a target terminal-associated software fault detection rate function from among the terminal-associated software fault detection rate functions; According to the target pure software fault introduction function and the target pure software fault detection rate function, the initial cumulative fault detection model is adjusted to obtain a pure software cumulative fault detection sub-model; and according to the target terminal-associated software fault introduction function and the target terminal-associated software fault detection rate function, the initial cumulative fault detection model is adjusted to obtain a terminal-associated software cumulative fault detection sub-model; The step of adjusting the reference cumulative fault detection model according to each of the historical evaluation moments in the historical evaluation time period and the corresponding actual value of the historical cumulative faults to obtain a target cumulative fault detection model includes: Using the reference cumulative fault detection model, according to each of the historical evaluation moments, obtain the historical cumulative fault expectation value at each of the historical evaluation moments; evaluating the reference cumulative fault detection model according to the degree of difference between the historical cumulative fault expected value and the corresponding historical cumulative fault actual value at each of the historical evaluation moments; When the reference cumulative fault detection model evaluation fails, the steps of selecting a target pure software fault introduction function from each of the pure software fault introduction functions, selecting a target pure software fault detection rate function from each of the pure software fault detection rate functions, selecting a target terminal-associated software fault introduction function from each of the terminal-associated software fault introduction functions, and selecting a target terminal-associated software fault detection rate function from each of the terminal-associated software fault detection rate functions are returned to execute until the reference cumulative fault detection model evaluation passes or the pure software fault introduction function, the pure software fault detection rate function, the terminal-associated software fault introduction function, and the terminal-associated software fault detection rate function are all selected.

4. The method according to claim 1, characterized in that The evaluating the terminal application software based on the target software reliability of the terminal application software in the current evaluation time period to obtain the target evaluation result of the terminal application software includes: Obtaining a preset software reliability threshold, a preset software reliability change threshold, and a target software reliability of an adjacent evaluation time period of the current evaluation time period; Comparing the target software reliability of the current evaluation time period with the preset software reliability threshold to obtain a software reliability evaluation result; Calculating the difference between the target software reliability of the current evaluation time period and the target software reliability of the adjacent evaluation time period to obtain a change degree of the target software reliability; Comparing the target software reliability change degree with the preset software reliability change degree threshold, and obtaining a software reliability change degree evaluation result; The target evaluation result of the terminal application software is determined according to the software reliability evaluation result and the software reliability change degree evaluation result.

5. The method according to claim 4, characterized in that The current evaluation period is in the software testing phase or the long-term stable operation phase; Accordingly, after obtaining the target evaluation result of the terminal application software, the method further includes: When the target evaluation result of the terminal application software is the first target evaluation result, sending a software reliability abnormality notification to remind an operation and maintenance user of the terminal application software; When the current evaluation time period is in the software testing phase, and the target evaluation result of the terminal application software is the second target evaluation result, the terminal application software is subjected to reinforcement testing and version backtracking; wherein both the first target evaluation result and the second target evaluation result are failures; and the target software reliability corresponding to the first target evaluation result is higher than the software reliability of the second target evaluation result; When the current evaluation time period is in the long-term stable operation stage, and when it is detected that the target evaluation result of the terminal application software is the second target evaluation result, an emergency alarm is issued to the operation and maintenance user of the terminal application software, and risk avoidance measures are adopted to eliminate the risks of the terminal application software.

6. The method according to claim 1, characterized in that The terminal application software is the terminal application software of a financial institution.

7. A terminal application software evaluation device, characterized in that: The device comprises: A current evaluation time period acquisition module is used to acquire the current evaluation time period of the terminal application software and a pre-generated target cumulative fault detection model; wherein the target cumulative fault detection model includes a pure software cumulative fault detection sub-model and a terminal associated fault detection sub-model; A cumulative fault expectation value calculation module, configured to calculate a first cumulative fault expectation value and a second cumulative fault expectation value of the current evaluation time period according to the endpoint time of the current evaluation time period by using the target cumulative fault detection model; a target software reliability calculation module, configured to calculate the target software reliability of the terminal application software according to the first cumulative failure expectation value and the second cumulative failure expectation value; The target evaluation result generating module is used to evaluate the terminal application software based on the target software reliability to obtain the target evaluation result of the terminal application software.

8. An electronic device, characterized in that: The electronic device comprises: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the terminal application software evaluation method according to any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the terminal application software evaluation method according to any one of claims 1 to 6 when executed.

10. A computer program product, characterized in that The computer program product comprises a computer program, and when the computer program is executed by a processor, the terminal application software evaluation method according to any one of claims 1 to 6 is implemented.

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