Legacy defect correction method and device, electronic equipment and storage medium

Abstract

The invention provides a legacy defect correction method and device, electronic equipment and a storage medium, and relates to the technical field of software development, and the method comprises the steps: obtaining test information of a non-functional test in response to a non-functional test check result indicating that a legacy defect exists; generating corresponding legacy defect items based on the test information; determining candidate defect solutions based on the legacy defect items, and processing the candidate defect solutions based on the test information to generate a target defect solution; and correcting the defect items based on the target defect solution. According to the method, non-functional test information, defect items, a solution knowledge base and a quality strategy are deeply fused, a set of automatic, closed-loop and intelligent remnant defect correction mechanism is constructed, the problems that in the prior art, manual tracking is depended, repairing is blind, and the quality is uncontrollable are effectively solved, and the remnant defect correction efficiency is improved. The reliability, the maintainability and the delivery efficiency of a software system are remarkably improved, and the credibility of a user on the product quality is enhanced.

Description

Technical Field

[0001] This disclosure relates to the field of software development technology, and in particular to a method, apparatus, electronic device and storage medium for correcting legacy defects. Background Technology

[0002] In modern software development and delivery, non-functional testing is a crucial step in ensuring system quality and is widely used for quality verification across dimensions such as performance, security, reliability, compatibility, and usability. Unlike functional testing, which focuses on "whether the system does the right thing," non-functional testing focuses on "whether the system does it well enough," and its results directly impact software stability, user experience, and the operational security of the production environment. Summary of the Invention

[0003] This disclosure aims to at least partially address one of the technical problems in the related art.

[0004] Therefore, one objective of this disclosure is to propose a method for correcting legacy defects.

[0005] The second objective of this disclosure is to provide a device for correcting legacy defects.

[0006] The third objective of this disclosure is to propose an electronic device.

[0007] The fourth objective of this disclosure is to provide a non-transitory computer-readable storage medium.

[0008] The fifth objective of this disclosure is to provide a computer program product.

[0009] To achieve the above objectives, a first aspect of this disclosure provides a method for correcting legacy defects, comprising: in response to a non-functional test result indicating the existence of a legacy defect, acquiring test information of the non-functional test; generating a corresponding legacy defect item based on the test information; determining candidate defect solutions based on the legacy defect item, and processing the candidate defect solutions based on the test information to generate a target defect solution; and correcting the defect item based on the target defect solution.

[0010] According to one embodiment of this disclosure, generating corresponding legacy defect items based on the test information includes: obtaining legacy defect data and test types from the test information; and establishing the legacy defect items based on the legacy defect data and the test types.

[0011] According to one embodiment of this disclosure, determining a candidate defect solution based on the legacy defect includes: matching and obtaining at least one sub-defect solution from a candidate defect solution library based on the legacy defect; and determining the candidate defect solution based on the sub-defect solution.

[0012] According to one embodiment of this disclosure, determining the candidate defect solution based on the sub-defect solution includes: calculating a feasibility assessment value for any sub-defect solution; and selecting the sub-defect solution with the largest feasibility assessment value as the candidate defect solution.

[0013] According to one embodiment of this disclosure, processing the candidate defect solutions based on the test information to generate a target defect solution includes: obtaining the test level and test type in the test information; determining a target test accuracy based on the test level and the test type; and adjusting the candidate defect solutions based on the target test accuracy to generate the target defect solution.

[0014] According to one embodiment of this disclosure, adjusting the candidate defect solution based on the target test accuracy to generate the target defect solution includes: determining the candidate test accuracy of the candidate defect solution; adjusting the solution parameters in the candidate defect solution in response to the candidate test accuracy being less than the target test accuracy; repeating the above calculation of the candidate test accuracy of the candidate defect solution and subsequent steps until the candidate test accuracy is greater than or equal to the target test accuracy, and outputting the target defect solution.

[0015] According to one embodiment of this disclosure, determining the candidate test accuracy of the candidate defect solution includes: obtaining a test accuracy prediction model; inputting the legacy defect and the candidate defect solution into the test accuracy prediction model to generate the candidate test accuracy of the candidate defect solution.

[0016] According to one embodiment of this disclosure, determining the target test accuracy based on the test level and the test type includes: obtaining a level-type-test accuracy mapping relationship; and matching the test level and the test type from the level-type-test accuracy mapping relationship to determine the target test accuracy.

[0017] To achieve the above objectives, a second aspect of this disclosure provides a legacy defect correction device, comprising: an acquisition module, configured to acquire test information of the non-functional test in response to a non-functional test result indicating the existence of a legacy defect; an establishment module, configured to generate a corresponding legacy defect item based on the test information; a generation module, configured to determine candidate defect solutions based on the legacy defect item and process the candidate defect solutions based on the test information to generate a target defect solution; and a correction module, configured to correct the defect item based on the target defect solution.

[0018] To achieve the above objectives, a third aspect of this disclosure provides an electronic device, comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor to implement the legacy defect correction method as described in the first aspect of this disclosure.

[0019] To achieve the above objectives, a fourth aspect of this disclosure provides a non-transitory computer-readable storage medium storing computer instructions, wherein the computer instructions are used to implement the legacy defect correction method as described in the first aspect of this disclosure.

[0020] To achieve the above objectives, a fifth aspect of this disclosure provides a computer program product including a computer program that, when executed by a processor, is used to implement the legacy defect correction method as described in the first aspect of this disclosure. Attached Figure Description

[0021] Figure 1 This is a schematic diagram of a method for correcting a legacy defect according to one embodiment of the present disclosure; Figure 2 This is a schematic diagram of another method for correcting legacy defects according to one embodiment of this disclosure; Figure 3 This is a schematic diagram of another method for correcting legacy defects according to one embodiment of this disclosure; Figure 4 This is a schematic diagram of a legacy defect correction device according to one embodiment of the present disclosure; Figure 5 This is a schematic diagram of an electronic device according to one embodiment of the present disclosure. Detailed Implementation

[0022] Embodiments of this disclosure are described in detail below, examples of which are illustrated in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain this disclosure, and should not be construed as limiting this disclosure.

[0023] The acquisition, storage, use, and processing of data in this disclosed technical solution all comply with the relevant provisions of relevant laws and regulations.

[0024] It should be noted that in the embodiments of this application, certain software, components, models and other existing solutions in the industry may be mentioned. These should be regarded as exemplary and are only intended to illustrate the feasibility of implementing the technical solution of this application. However, it does not mean that the applicant has used or necessarily used the solution.

[0025] In actual testing practice, when the execution results of non-functional test cases fail to meet the preset test indicators (such as exceeding response time limits, failing to meet concurrent user counts, or having security vulnerabilities), the testing team needs to comprehensively assess the scope of the defect's impact, its severity level, and the risk to the current version's production deployment. If it is determined that the defect will affect the system's core capabilities or violate production access standards, it must be fixed before the current version is released. If the assessment confirms that it will not affect the current production deployment, the defect can be marked as a "legacy defect" (or "deferred defect") and included in subsequent iterations or special rectification plans for resolution.

[0026] However, current legacy defect tracking and management mechanisms generally rely heavily on manual operations. Specifically, this manifests in several ways: production version checkers must proactively inquire with development or testing teams about defect remediation progress; manually review historical test results to verify remediation effectiveness; and manually update defect status (e.g., from "Repairing" to "Pending Verification" or "Closed"). There is a lack of automated status transition and closed-loop verification mechanisms. This manually driven management model is not only inefficient and error-prone, but also prone to delays in defect status updates, missed remediations, or duplicate verification, thereby increasing online quality risks and weakening the reliability and user trust of the software system.

[0027] To address the aforementioned issues, this disclosure proposes a method for correcting legacy defects. Figure 1 This is a schematic diagram of a method for correcting legacy defects according to one embodiment of this disclosure, as shown below. Figure 1 As shown, the method for correcting this legacy defect includes the following steps: S101, in response to the non-functional test result indicating the presence of a residual defect, obtain the test information of the non-functional test.

[0028] The legacy defect correction method of this application embodiment can be applied to software non-functional testing scenarios. The execution subject of legacy defect correction in this application embodiment can be the legacy defect correction device of this application embodiment, which can be installed on an electronic device.

[0029] It should be noted that non-functional testing is a type of testing used to evaluate the performance, usability, reliability, and other non-functional characteristics of a software application.

[0030] Legacy defects are those discovered in the current version. After assessment, these defects do not affect normal production operations and do not need to be resolved before the current version is put into production. They are generally minor defects.

[0031] It should be noted that test information refers to a structured set of data used to describe the process and results of a test execution. This information is a key input for subsequent defect identification, classification, analysis, repair, and tracking.

[0032] Test information may include various types of data, without any limitations here. For example, it may be shown in the table below:

[0033] S102, Based on the test information, generate the corresponding legacy defect items.

[0034] Legacy defect items refer to structured task records created in the defect management system for non-functional defects that are determined to be remediable with a delay. These records are used for subsequent tracking, allocation, repair, and verification. Therefore, by establishing legacy defect items, a failed test execution can be transformed into a traceable, assignable, and closed-loop defect task, while avoiding omissions in manual data entry and ensuring the completeness of key fields. This provides a data foundation for subsequent "solution matching," "progress tracking," and "production verification."

[0035] S103, determine candidate defect solutions based on legacy defect items, and process the candidate defect solutions based on test information to generate target defect solutions.

[0036] In this disclosure, there are various methods for determining candidate defect solutions based on legacy defect issues, and no limitation is made here.

[0037] In one possible implementation, legacy defects can be input into a solution building model to generate at least one corresponding candidate defect solution. This solution building model is pre-trained and can be stored in the electronic device's storage space for easy retrieval when needed.

[0038] In another possible implementation, the candidate defect solution that best matches the current legacy defect can be determined from historical solutions by screening and matching legacy defect items from candidate defect solutions.

[0039] In this embodiment of the disclosure, the candidate defect solutions are processed based on test information to generate the target defect solution, which realizes the leap from "passively recording defects" to "actively recommending high-quality repair solutions" and is the core link of intelligent software quality governance.

[0040] It should be noted that the processing of candidate defective solutions can be divided into two operations. First, a feasibility assessment can be performed to calculate the comprehensive score of each solution. Then, a compliance verification can be performed on the candidate defective solutions to check whether the solutions violate the domain rules of this test type.

[0041] S104, Correct the defect based on the target defect solution.

[0042] In this embodiment, in response to the indication of a legacy defect by non-functional test results, test information for the non-functional test is first obtained. Then, based on the test information, a corresponding legacy defect item is generated. Next, candidate defect solutions are determined based on the legacy defect item, and these solutions are processed based on the test information to generate a target defect solution. Finally, the defect item is corrected based on the target defect solution. This disclosure deeply integrates non-functional test information, defect items, a solution knowledge base, and quality strategies to construct an automated, closed-loop, and intelligent legacy defect correction mechanism. This effectively solves the pain points of existing technologies, such as reliance on manual tracking, blind repairs, and uncontrollable quality, significantly improving the reliability, maintainability, and delivery efficiency of the software system, and enhancing user trust in product quality.

[0043] In this embodiment of the disclosure, based on test information, corresponding legacy defect items are generated. First, the legacy defect data and test type in the test information can be obtained, and then legacy defect items can be established based on the legacy defect data and test type.

[0044] In the above embodiments, the candidate defect solutions are determined based on legacy defects, and can also be achieved through... Figure 2 To further explain, the method includes: S201, Based on the legacy defect items, at least one sub-defect solution is obtained by matching from the candidate defect solution library.

[0045] It should be noted that the sub-defect solution is an atomic-level repair strategy unit for a certain type of typical non-functional defect (such as 'response timeout under high concurrency'), and can be used independently or in combination.

[0046] The candidate defect solution library is a database that stores sub-defect solutions. Sub-defect solutions can be manually entered or generated based on historical legacy defect solutions; there are no restrictions here.

[0047] S202, determine candidate defect solutions based on sub-defect solutions.

[0048] In this embodiment of the disclosure, the candidate defect solution is determined based on the sub-defect solution. First, the feasibility evaluation value of any sub-defect solution is calculated, and then the sub-defect solution with the largest feasibility evaluation value is selected as the candidate defect solution.

[0049] In the embodiments of this disclosure, there are various methods for calculating the feasibility assessment value of the sub-defect solution, and no limitation is made herein.

[0050] In one possible implementation, the feasibility assessment value of the sub-defect solution can be calculated using a pre-designed algorithm. This algorithm can be pre-designed and can be modified according to actual design needs; no limitations are imposed here. For example, the following algorithm can be used for calculation:

[0051] in, This represents the historical pass rate of the solution. To estimate repair costs, The sub-defect solution with the highest score is selected as the candidate defect solution, with the preset weights.

[0052] In another possible implementation, a model can also be generated from pre-trained defect solutions. In this embodiment, candidate defect solutions are processed based on test information to generate a target defect solution. Furthermore, [the process can be further described using...] Figure 3 To further explain, the method includes: S301, retrieve the test level and test type from the test information.

[0053] S302, determine the target test accuracy based on the test level and test type.

[0054] In this embodiment of the disclosure, the level-type-test accuracy mapping relationship can be obtained first, and then the target test accuracy can be determined by matching the level-type-test accuracy mapping relationship based on the test level and test type.

[0055] It should be noted that the target test accuracy is the minimum historical success rate that must be achieved for the current defect repair, which is determined by both the test level and the test type.

[0056] The mapping relationship between grade, type, and test precision can be pre-designed or generated based on historical non-functional test results; no limitations are imposed here.

[0057] S303, adjust the candidate defect solutions based on the target test accuracy to generate the target defect solution.

[0058] In this embodiment of the disclosure, the candidate test accuracy of the candidate defect solution can be determined first. In response to the candidate test accuracy being less than the target test accuracy, the solution parameters in the candidate defect solution are adjusted. The above calculation of the candidate test accuracy of the candidate defect solution and its subsequent steps are repeated until the candidate test accuracy is greater than or equal to the target test accuracy, and the target defect solution is output.

[0059] It should be noted that solution parameters refer to quantifiable, configurable technical variables in a sub-defect solution that directly affect the repair outcome. Solution parameters can include various types, as shown in the table below:

[0060] In this embodiment of the disclosure, the candidate defect solution can be adjusted based on historical mapping relationships. For example, the system can maintain a historical statistical table of "parameter value - test pass rate". For example, if the number of threads is 50, the performance test pass rate is 70%; if the number of threads is 80, the pass rate is 92%. When the current accuracy is insufficient, the minimum parameter value that makes the pass rate ≥ the target accuracy is automatically selected.

[0061] Another possible approach is to use gradient search or heuristic adjustments. For example, if there is no direct historical data, the algorithm can increment / decrement by a preset step size (e.g., +10%, ×1.5) until the accuracy is achieved or the upper limit is reached.

[0062] Another possible approach is to combine parameters for optimization. For example, for multi-parameter schemes (such as "number of threads + cache size"), orthogonal experimental design or Bayesian optimization can be used to narrow the search space.

[0063] In this embodiment of the disclosure, the candidate test accuracy of the candidate defect solution can be determined by first obtaining a test accuracy prediction model, and then inputting the legacy defect and the candidate defect solution into the test accuracy prediction model to generate the candidate test accuracy of the candidate defect solution.

[0064] Corresponding to the legacy defect correction methods provided in the above embodiments, one embodiment of this disclosure also provides a legacy defect correction device. Since the legacy defect correction device provided in this disclosure corresponds to the legacy defect correction methods provided in the above embodiments, the implementation methods of the above legacy defect correction methods are also applicable to the legacy defect correction device provided in this disclosure, and will not be described in detail in the following embodiments.

[0065] Figure 4 This is a schematic diagram of a legacy defect correction device according to one embodiment of the present disclosure. As shown in FIG4, the legacy defect correction device 400 includes: The acquisition module 410 is used to acquire test information of non-functional tests in response to the indication of a residual defect in the non-functional test verification results.

[0066] Module 420 is established to generate corresponding legacy defect items based on test information.

[0067] The generation module 430 is used to determine candidate defect solutions based on legacy defect items and process the candidate defect solutions based on test information to generate the target defect solution.

[0068] Correction module 440 is used to correct defects based on the target defect solution.

[0069] According to one embodiment of this disclosure, generating corresponding legacy defect items based on test information includes: obtaining legacy defect data and test types from the test information; and establishing legacy defect items based on the legacy defect data and test types.

[0070] According to one embodiment of this disclosure, determining candidate defect solutions based on legacy defect items includes: matching and obtaining at least one sub-defect solution from a candidate defect solution library based on the legacy defect item; and determining candidate defect solutions based on the sub-defect solutions.

[0071] According to one embodiment of this disclosure, determining a candidate defect solution based on a sub-defect solution includes: calculating a feasibility assessment value for executing the sub-defect solution based on any sub-defect solution; and selecting the sub-defect solution with the largest feasibility assessment value as a candidate defect solution.

[0072] According to one embodiment of this disclosure, processing candidate defect solutions based on test information to generate a target defect solution includes: obtaining test level and test type from the test information; determining a target test accuracy based on the test level and test type; and adjusting the candidate defect solutions based on the target test accuracy to generate the target defect solution.

[0073] According to one embodiment of this disclosure, adjusting a candidate defect solution based on a target test accuracy to generate a target defect solution includes: determining the candidate test accuracy of the candidate defect solution; adjusting the solution parameters in the candidate defect solution in response to the candidate test accuracy being less than the target test accuracy; repeating the above calculation of the candidate test accuracy of the candidate defect solution and its subsequent steps until the candidate test accuracy is greater than or equal to the target test accuracy, and outputting the target defect solution.

[0074] According to one embodiment of this disclosure, determining the candidate test accuracy of a candidate defect solution includes: obtaining a test accuracy prediction model; inputting legacy defect items and candidate defect solutions into the test accuracy prediction model to generate the candidate test accuracy of the candidate defect solution.

[0075] According to one embodiment of this disclosure, determining a target test accuracy based on test level and test type includes: obtaining a level-type-test accuracy mapping relationship; and matching the test level and test type from the level-type-test accuracy mapping relationship to determine the target test accuracy.

[0076] This disclosure establishes an automated, closed-loop, and intelligent legacy defect correction mechanism by deeply integrating non-functional test information, defect items, solution knowledge bases, and quality strategies. It effectively addresses the pain points of existing technologies, such as reliance on manual tracking, blind repair, and uncontrollable quality, significantly improving the reliability, maintainability, and delivery efficiency of software systems, and enhancing users' trust in product quality.

[0077] To implement the above embodiments, this disclosure also proposes an electronic device 500. Figure 5 This is a schematic diagram of an electronic device according to one embodiment of the present disclosure, such as... Figure 5 As shown, the electronic device 500 includes: a processor 501 and a memory 502 communicatively connected to the processor. The memory 502 stores instructions executable by at least one processor. The instructions are executed by at least one processor 501 to achieve the functions described in this disclosure. Figures 1-3 Method for correcting residual defects in the embodiments.

[0078] To implement the above embodiments, this disclosure also proposes a non-transitory computer-readable storage medium storing computer instructions, wherein the computer instructions are used to cause a computer to implement the present disclosure. Figures 1-3 Method for correcting residual defects in the embodiments.

[0079] To implement the above embodiments, this disclosure also proposes a computer program product, including a computer program, which, when executed by a processor, implements the features of this disclosure. Figures 1-3 Method for correcting residual defects in the embodiments.

[0080] It should be noted that personal information collected from users should be used for legitimate and reasonable purposes and should not be shared or sold outside of these legitimate uses. Furthermore, such collection / sharing should only be conducted after receiving the user's informed consent, including but not limited to notifying the user to read the user agreement / user notice and sign an agreement / authorization that includes authorization of relevant user information before the user uses the function. In addition, any necessary steps must be taken to protect and safeguard access to such personal information data and ensure that others with access to personal information data comply with their privacy policies and procedures.

[0081] This application is intended to provide an implementation scheme for users to selectively prevent the use or access to their personal information data. Specifically, this disclosure is intended to provide hardware and / or software to prevent or block access to such personal information data. Once personal information data is no longer needed, risks can be minimized by restricting data collection and deleting data. Furthermore, where applicable, such personal information is de-identified to protect user privacy.

[0082] In the foregoing descriptions of the embodiments, the terms "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0083] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this application, "multiple" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0084] Any process or method description in the flowchart or otherwise herein can be understood as representing a module, segment, or portion of code comprising one or more executable instructions for implementing custom logic functions or processes, and the scope of the preferred embodiments of this application includes additional implementations in which functions may be performed not in the order shown or discussed, including substantially simultaneously or in reverse order depending on the functions involved, as should be understood by those skilled in the art to which embodiments of this application pertain.

[0085] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-included system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that contains, stores, communicates, propagates, or transmits programs for use by, or in conjunction with, an instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of computer-readable media include: an electrical connection having one or more wires (electronic device), a portable computer disk drive (magnetic device), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Alternatively, the computer-readable medium may be paper or other suitable media on which the program can be printed, since the program can be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in a computer memory.

[0086] It should be understood that various parts of this application can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented using software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0087] Those skilled in the art will understand that all or part of the steps of the methods in the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, the program includes one or a combination of the steps of the method embodiments.

[0088] Furthermore, the functional units in the various embodiments of this application can be integrated into a processing module, or each unit can exist physically separately, or two or more units can be integrated into a module. The integrated module can be implemented in hardware or as a software functional module. If the integrated module is implemented as a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium.

[0089] The storage medium mentioned above can be a read-only memory, a disk, or an optical disk, etc. Although embodiments of this application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting this application. Those skilled in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of this application.

Claims

1. A method for correcting legacy defects, characterized in that, include: In response to the non-functional test results indicating the presence of a residual defect, the test information of the non-functional test is obtained; Based on the test information, corresponding legacy defects are generated; Candidate defect solutions are determined based on the aforementioned legacy defects, and the candidate defect solutions are processed based on the test information to generate the target defect solution; The defect is corrected based on the target defect solution.

2. The method according to claim 1, characterized in that, The step of generating corresponding legacy defects based on the test information includes: Obtain the remaining defect data and test type from the test information; The legacy defect items are established based on the legacy defect data and the test type.

3. The method according to claim 1 or 2, characterized in that, The process of determining candidate defect solutions based on the legacy defect issues includes: Based on the aforementioned legacy defect, at least one sub-defect solution is obtained by matching from the candidate defect solution library; The candidate defect solution is determined based on the sub-defect solution.

4. The method according to claim 3, characterized in that, The process of determining the candidate defect solution based on the sub-defect solution includes: Calculate the feasibility assessment value of any sub-defect solution; The sub-defect solution with the highest feasibility assessment value is selected as the candidate defect solution.

5. The method according to claim 4, characterized in that, The step of processing the candidate defect solutions based on the test information to generate the target defect solution includes: Obtain the test level and test type from the test information; The target test accuracy is determined based on the test level and the test type; The candidate defect solutions are adjusted based on the target test accuracy to generate the target defect solution.

6. The method according to claim 5, characterized in that, The step of adjusting the candidate defect solutions based on the target test accuracy to generate the target defect solution includes: Determine the candidate test accuracy of the candidate defect solutions; In response to the candidate test accuracy being less than the target test accuracy, the solution parameters in the candidate defect solution are adjusted; Repeat the above calculation of the candidate test accuracy of the candidate defect solution and its subsequent steps until the candidate test accuracy is greater than or equal to the target test accuracy, and then output the target defect solution.

7. The method according to claim 6, characterized in that, Determining the candidate test accuracy of the candidate defect solution includes: Obtain a test accuracy prediction model; The legacy defect and the candidate defect solution are input into the test accuracy prediction model to generate the candidate test accuracy of the candidate defect solution.

8. The method according to claim 5, characterized in that, Determining the target test accuracy based on the test level and the test type includes: Obtain the mapping relationship between level, type, and test precision; The target test accuracy is determined by matching the test level and the test type from the level-type-test accuracy mapping relationship.

9. A device for correcting legacy defects, characterized in that, include: The acquisition module is used to acquire the test information of the non-functional test in response to the non-functional test inspection result indicating the existence of a residual defect; A module is established to generate corresponding legacy defect items based on the test information; A generation module is used to determine candidate defect solutions based on the legacy defect issues, and process the candidate defect solutions based on the test information to generate a target defect solution; The correction module is used to correct the defect based on the target defect solution.

10. An electronic device, characterized in that, Including memory and processor; The processor reads executable program code stored in the memory to run a program corresponding to the executable program code, so as to implement the method as described in any one of claims 1-8.

11. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement the method as described in any one of claims 1-8.

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