Method and system for analyzing high-risk test case, electronic equipment and storage medium

Abstract

The invention discloses a method and system for analyzing a high-risk test case, electronic equipment and a storage medium, and relates to the field of risk testing, and the method comprises the steps: 1, obtaining a historical defect list of mass-produced vehicles; according to the historical defect list, extracting corresponding module information, performing statistical analysis on the number of defects, and collecting defect feature information; 2, executing the smoking test case of the new vehicle model, and performing peripheral function point inspection to obtain a test result of the new vehicle model; wherein the test result comprises the feature of the failed use case; 3, based on the defect features and the features of the failed cases, analyzing the high-risk test cases of the new vehicle model, and obtaining a minimum test set; 4, executing the minimum test set obtained in the step 3, updating a test result, and reporting a newly discovered defect; step 5, adding the newly found defects reported in the step 4 into the historical defect list; and returning to the step 3 for circulation, and continuing to execute the steps 3 and 4 until the test is finished.

Description

Technical Field

[0001] This application relates to the field of risk testing, and in particular to methods for analyzing high-risk test cases, systems for analyzing high-risk test cases, electronic devices, storage media, and risk testing platforms. Background Technology

[0002] Traditional automotive cockpit software testing determines the scope of test cases based on all requirements. The reference number of test cases for executing all requirements is approximately 20,000, which typically requires 7-8 people to spend a month or even longer. This results in long testing times, slow problem exposure, and slow iteration updates.

[0003] Therefore, a solution is needed to analyze high-risk test cases. This solution should be based on historical defect data reported by real users of mass-produced vehicles of the same brand. Based on defect characteristics and test case characteristics of problems found in new model testing, a minimum test set should be intelligently analyzed to effectively reduce the number of test cases executed, shorten test execution time, expose problems quickly, iterate and update quickly, and reduce costs. Summary of the Invention

[0004] The purpose of this invention is to provide a method, system, electronic device, storage medium, and risk testing platform for analyzing high-risk test cases, thereby addressing at least one technical problem: the large number of test case references, long testing time, slow problem exposure, and slow iterative updates.

[0005] This invention provides the following solution:

[0006] According to a first aspect of the present invention, a method for analyzing high-risk test cases is provided, the method comprising:

[0007] Step 1: Test begins; obtain a list of historical defects for mass-produced vehicles.

[0008] Based on the historical defect list, extract the corresponding module information, perform defect quantity statistical analysis, and collect defect characteristic information;

[0009] Step 2: Execute the smoke test cases for the new model and perform peripheral function checks to obtain the test results for the new model;

[0010] The test results include the characteristics of failed test cases.

[0011] Step 3: Based on defect characteristics and characteristics of failed test cases, analyze the high-risk test cases for the new model and obtain the minimum test set;

[0012] Step 4: Execute the minimum test set obtained in Step 3, update the test results, and report any newly discovered defects;

[0013] Step 5: Add the newly discovered defects reported in Step 4 to the historical defect list;

[0014] Return to step 3 and repeat the loop, continuing to execute steps 3 and 4 until the test ends.

[0015] Furthermore, step 3 includes:

[0016] Step 31: Configure attribute values ​​for each test case;

[0017] The attribute values ​​include the module to which the test case belongs, the test case priority, the number of defects found in the test case, the test case risk value, the test case preparation environment time, and the test case execution time.

[0018] Furthermore, step 3 includes:

[0019] Step 32: Based on the defect characteristics and the characteristics of the test cases that have failed to execute, update the attribute values ​​of the corresponding test cases, including incrementing the number of defects found by the test cases by 1;

[0020] Determine whether a pre-defined critical issue is triggered based on historical defects and failed test cases;

[0021] If yes, then increment the use case risk value by 1.

[0022] Furthermore, step 3 includes:

[0023] Step 33, analyzing high-risk test cases for the new model includes calculating high-risk test case coefficients;

[0024] The calculation of the high-risk test case coefficient includes a weighted average of 25% for the test case risk value, 25% for the number of defects found in the test case, 20% for the module to which the test case belongs and the priority of the test case, 20% for the test case execution time, and 10% for the test case preparation environment time. The high-risk test case coefficient of each test case is comprehensively evaluated.

[0025] The weighting rules for test case execution time and test case preparation environment time are as follows: the shorter the time, the higher the weight contribution.

[0026] Furthermore, step 3 includes:

[0027] Step 34: Based on the preset number of test cases to be executed, select the test cases with the highest risk test case coefficients to form the minimum test set.

[0028] Furthermore, step 3 includes:

[0029] Serious issues include crashes and malfunctions.

[0030] According to a second aspect of the present invention, a system for analyzing high-risk test cases is provided, the system comprising:

[0031] The Historical Defect List module is used to retrieve a list of historical defects from mass-produced vehicles at the start of testing.

[0032] Based on the historical defect list, extract the corresponding module information, perform defect quantity statistical analysis, and collect defect characteristic information;

[0033] The smoke test case module is used to execute smoke test cases for the new vehicle model, perform peripheral function checks, and obtain the test results for the new vehicle model.

[0034] The test results include the characteristics of failed test cases.

[0035] The minimum test set module is used to analyze high-risk test cases for new car models based on defect characteristics and characteristics of executed failed test cases, and to obtain the minimum test set.

[0036] The new discovery reporting module is used to execute the minimum test set obtained, update the test results, and report newly discovered defects;

[0037] The "Expand Defect List" module is used to add newly discovered defects to the historical defect list.

[0038] The loop test module is used to return to the loop and continue execution until the test ends.

[0039] According to a third aspect of the present invention, an electronic device is provided, comprising: a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other via the communication bus;

[0040] The memory stores a computer program that, when executed by a processor, causes the processor to perform the steps of the method for analyzing high-risk test cases.

[0041] According to a fourth aspect of the present invention, a computer-readable storage medium is provided storing a computer program executable by an electronic device, which, when run on the electronic device, causes the electronic device to perform the steps of the method for analyzing high-risk test cases.

[0042] According to a fifth aspect of the present invention, a risk testing platform is provided, comprising:

[0043] An electronic device for implementing the steps of the method for analyzing high-risk test cases;

[0044] The processor runs a program that, when running, executes the steps of the method for analyzing high-risk test cases from data output by the electronic device.

[0045] A storage medium for storing a program that, when run, executes the steps of the method for analyzing high-risk test cases based on data output from an electronic device.

[0046] The above solution achieves the following beneficial technical effects:

[0047] This application utilizes intelligent analysis based on historical defect data reported by real users of mass-produced vehicles of the same brand.

[0048] This application uses test case characteristics to identify problems based on defect features and new vehicle model testing, and intelligently analyzes the minimum test set to effectively reduce the number of test cases executed. Attached Figure Description

[0049] Figure 1 This is a flowchart of a method for analyzing high-risk test cases provided by one or more embodiments of the present invention.

[0050] Figure 2 This is a structural diagram of a system for analyzing high-risk test cases provided by one or more embodiments of the present invention.

[0051] Figure 3 This is a block diagram of an electronic device structure that provides a method for analyzing high-risk test cases according to one or more embodiments of the present invention. Detailed Implementation

[0052] The technical solution of the present invention will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0053] Figure 1 This is a flowchart of a method for analyzing high-risk test cases provided by one or more embodiments of the present invention.

[0054] like Figure 1 The methods for analyzing high-risk test cases shown include:

[0055] Step 1: Test begins; obtain a list of historical defects for mass-produced vehicles.

[0056] Based on the historical defect list, extract the corresponding module information, perform defect quantity statistical analysis, and collect defect characteristic information;

[0057] Step 2: Execute the smoke test cases for the new model and perform peripheral function checks to obtain the test results for the new model;

[0058] The test results include the characteristics of failed test cases.

[0059] Step 3: Based on defect characteristics and characteristics of failed test cases, analyze the high-risk test cases for the new model and obtain the minimum test set;

[0060] Step 4: Execute the minimum test set obtained in Step 3, update the test results, and report any newly discovered defects;

[0061] Step 5: Add the newly discovered defects reported in Step 4 to the historical defect list;

[0062] Return to step 3 and repeat the loop, continuing to execute steps 3 and 4 until the test ends.

[0063] Specifically, step 1 also includes: the historical defect list is derived from defect data reported by real users of mass-produced vehicles collected by the company's after-sales department.

[0064] Step 2 also includes: smoke test cases covering the entertainment module, navigation module, local function module, and voice function module of the new vehicle's cockpit software; specifically, this includes executing 60-100 smoke test cases for the entertainment module, 60-80 smoke test cases for the navigation module, 100-150 smoke test cases for the local function module, and 80-120 smoke test cases for other modules.

[0065] The termination condition for "until the test ends" in step 5 is any of the following: 1. The preset test cycle (e.g., 7 days) is reached; 2. In two consecutive cycles, the number of new defect reports decreases by ≥50%; 3. No new defect reports are submitted after the minimum test set is executed.

[0066] In this embodiment, step 3 includes:

[0067] Step 31: Configure attribute values ​​for each test case;

[0068] The attribute values ​​include the module to which the test case belongs, the test case priority, the number of defects found in the test case, the test case risk value, the test case preparation environment time, and the test case execution time.

[0069] Specifically, step 31 also includes: the functional modules of the new vehicle model's cockpit software corresponding to the module to which the use case belongs;

[0070] This includes a navigation module, an online music module, a local function module, and a voice function module; based on use case priority, the functional modules are divided into three levels: P0, P1, and P2, according to their importance and functional hierarchy.

[0071] In this embodiment, step 3 includes:

[0072] Step 32: Based on the defect characteristics and the characteristics of the test cases that have failed to execute, update the attribute values ​​of the corresponding test cases, including incrementing the number of defects found by the test cases by 1;

[0073] Determine whether a pre-defined critical issue is triggered based on historical defects and failed test cases;

[0074] If yes, then increment the use case risk value by 1.

[0075] In this embodiment, step 3 includes:

[0076] Step 33, analyzing high-risk test cases for the new model includes calculating high-risk test case coefficients;

[0077] The calculation of the high-risk test case coefficient includes a weighted average of 25% for the test case risk value, 25% for the number of defects found in the test case, 20% for the module to which the test case belongs and the priority of the test case, 20% for the test case execution time, and 10% for the test case preparation environment time. The high-risk test case coefficient of each test case is comprehensively evaluated.

[0078] The weighting rules for test case execution time and test case preparation environment time are as follows: the shorter the time, the higher the weight contribution.

[0079] Specifically, step 33 also includes the following weight calculation rules for "the module to which the use case belongs and the priority of the use case": if the module to which the use case belongs is a high-defect module with a historical defect rate of ≥10% and the use case priority is P0, then the weight contribution of this dimension is the maximum value; if the module to which the use case belongs is a low-defect module with a historical defect rate of <5% and the use case priority is P2, then the weight contribution of this dimension is the minimum value.

[0080] In this embodiment, step 3 includes:

[0081] Step 34: Based on the preset number of test cases to be executed, select the test cases with the highest risk test case coefficients to form the minimum test set.

[0082] Specifically, the "preset number of test cases to be executed" in step 34 is top100, top500, or top5000, depending on the testing cycle and manpower configuration of the new model.

[0083] In this embodiment, step 3 includes:

[0084] Serious issues include crashes and malfunctions.

[0085] Figure 2 This is a structural diagram of a system for analyzing high-risk test cases provided by one or more embodiments of the present invention.

[0086] like Figure 2The system for analyzing high-risk test cases shown includes: a historical defect list module, a smoke test case module, a minimum test set module, a new discovery reporting module, an expanded defect list module, and a loop test module.

[0087] The Historical Defect List module is used to retrieve a list of historical defects from mass-produced vehicles at the start of testing.

[0088] Based on the historical defect list, extract the corresponding module information, perform defect quantity statistical analysis, and collect defect characteristic information;

[0089] The smoke test case module is used to execute smoke test cases for the new vehicle model, perform peripheral function checks, and obtain the test results for the new vehicle model.

[0090] The test results include the characteristics of failed test cases.

[0091] The minimum test set module is used to analyze high-risk test cases for new car models based on defect characteristics and characteristics of executed failed test cases, and to obtain the minimum test set.

[0092] The new discovery reporting module is used to execute the minimum test set obtained, update the test results, and report newly discovered defects;

[0093] The "Expand Defect List" module is used to add newly discovered defects to the historical defect list.

[0094] The loop test module is used to return to the loop and continue execution until the test ends.

[0095] It is worth noting that although this system / device only discloses the historical defect list module, smoke test case module, minimum test set module, new discovery reporting module, defect list expansion module, and loop test module, it does not mean that this device is limited to the above-mentioned basic functional modules. On the contrary, what this invention intends to express is that, based on the above-mentioned basic functional modules, those skilled in the art can arbitrarily add one or more functional modules in combination with existing technology to form an infinite number of embodiments or technical solutions. That is to say, this system / device is open rather than closed. The fact that this embodiment only discloses a few basic functional modules should not be taken as a reason to believe that the scope of protection of the claims of this invention is limited to the above-disclosed basic functional modules.

[0096] In one specific embodiment, a method for extracting defect features and intelligently analyzing high-risk test cases based on historical defect statistics is disclosed, including:

[0097] 1. Obtain a historical defect list of a certain brand's mass-produced vehicles from the company's after-sales department, extract the corresponding module information, and perform quantitative analysis.

[0098] 2. Execute smoke test cases for the new vehicle model and perform peripheral function checks to obtain test results.

[0099] 3. Based on historical defect characteristics and failed test case characteristics, intelligently analyze high-risk test cases and obtain the minimum test set.

[0100] 4. Execute the extracted minimum set of test cases, update the test results, and report more defects.

[0101] 5. Add the new defect to the historical defect results, repeat steps 3 and 4, dynamically adjust the test case set and test until the test ends.

[0102] The methods for intelligently analyzing high-risk test cases are as follows:

[0103] 1. Add attribute values ​​to each test case: module to which the test case belongs, test case priority, number of defects found by the test case, test case risk value, test case preparation environment time, and test case execution time.

[0104] 2. For each problem discovered, the corresponding test case's attribute module and priority are determined based on the corresponding function and its functional level within the module, plus "Number of Defects Found by Test Case" +1. If serious functional issues such as crashes or function failures are found, the "Test Case Risk Value" is incremented by 1.

[0105] 3. Comprehensively evaluate the high-risk test case coefficient, with the weighting coefficient taking 25% of the test case risk value, 25% of the number of defects found in the test case, 20% of the module to which the test case belongs and the priority of the test case, 20% of the test case execution time (the less time the better), and 10% of the test case preparation time (the less time the better).

[0106] 4. Input the number of test cases you want to run each time according to the above algorithm, such as top 100 or top 500 test cases to execute.

[0107] In another specific embodiment, it includes:

[0108] 1. Of the 210 issues reported by the after-sales department (real users) for mass-produced vehicles of the same brand, 54 were related to navigation (25.7%), 34 to online music (16.2%) (including 1 A), and 22 to local functions (10.5%). These three modules accounted for 52.3% of the total issues. The remaining 15 modules, including controller issues, accounted for 47.6%.

[0109] 2. A full suite of test cases for the cockpit software of a certain vehicle model is currently undergoing design changes. The test cases include approximately 2500 entertainment modules (600 of which are online music), approximately 2500 navigation modules, approximately 4000 local functions, and approximately 3000 voice functions. The test engineers first executed 60 entertainment smoke test cases, 130 local smoke test cases, 60 navigation smoke test cases, and 100 other module test cases. During the execution of the smoke test cases and the inspection process, 3 defects were found in online music, 1 in navigation, 2 in local functions (Bluetooth phone, connection settings), and 1 in voice function.

[0110] 3. Background: Due to the tight schedule, the version of this car model needs to be delivered to users in only half a month, and the testing time is only one week. With 5 people, assuming each person executes an average of 120 test cases per day, and considering the tight project cycle and heavy workload, each person can execute 150 test cases per day and work for 6 days, the total number of test cases that can be executed is no more than 5,000.

[0111] 4. Use intelligent analysis of high-risk use cases to execute the top 5000 use cases.

[0112] Based on the above embodiments, a method for intelligent analysis of high-risk use cases is disclosed:

[0113] 1. Add attribute values ​​to each test case: module to which the test case belongs, test case priority, number of defects found by the test case, test case risk value, test case preparation environment time, and test case execution time.

[0114] 2. For each problem discovered by after-sales users, the corresponding test case can be assigned to a module and priority based on the corresponding function and the level of function within the functional module, and the number of defects found in the test case is increased by 1. If serious functional problems such as crashes or functional failures are found, the risk value of the test case is increased by 1.

[0115] 1) The online music service has an A-level issue with the artist categorization function due to after-sales problems, and the corresponding use case risk value is increased by 1;

[0116] 2) The navigation's collection and company functions have many issues and are not dynamically tested, so they take less time (dynamic testing takes twice as long because it takes up the driver's time).

[0117] 3) The number of defects found in the local Bluetooth phone and connection settings test cases was relatively large, and the value of "number of defects found in test cases" was high;

[0118] 3. A comprehensive evaluation of high-risk use case coefficients is conducted, using a weighted average of 25% for the use case risk value, 25% for the number of defects found, 20% for the module to which the use case belongs and its priority, 20% for the use case execution time (lower is better), and 10% for the use case preparation time (lower is better). Based on these rules, use cases related to singers in the online music function category have a higher risk value; use cases for navigation favorites, local module Bluetooth phone, and connection settings have a higher number of defects found.

[0119] 4. Execute the top 5000 test cases based on the above algorithm. The results are as follows: The high-risk test cases run the full-featured test cases, approximately 60 for online music, 100 for navigation and favorites, 240 for Bluetooth phone calls, 300 for connection settings, and other functional modules run approximately 1000 P0 test cases, approximately 2500 P1 test cases, and approximately 800 P2 test cases.

[0120] 5. After reviewing the results, it was decided to cancel the testing of 800 test cases in P2 to reduce costs.

[0121] Figure 3 This is a block diagram of an electronic device structure that provides a method for analyzing high-risk test cases according to one or more embodiments of the present invention.

[0122] like Figure 3 As shown, this application provides an electronic device, including: a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other through the communication bus;

[0123] The memory stores a computer program, which, when executed by the processor, causes the processor to perform steps to analyze high-risk test cases.

[0124] This application also provides a computer-readable storage medium storing a computer program executable by an electronic device, which, when run on the electronic device, causes the electronic device to perform steps of a method for analyzing high-risk test cases.

[0125] This application also provides a risk testing platform, including:

[0126] Electronic equipment used to implement the steps of analyzing high-risk test cases;

[0127] The processor runs programs, and when the program runs, it executes steps to analyze high-risk test cases by taking data output from electronic devices.

[0128] Storage medium used to store programs that, when run, execute steps to analyze high-risk test cases based on data output from electronic devices.

[0129] The communication bus mentioned in the above electronic devices can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. This communication bus can be divided into address bus, data bus, control bus, etc. For ease of illustration, only one thick line is used to represent it in the diagram, but this does not mean that there is only one bus or one type of bus.

[0130] The electronic device comprises a hardware layer, an operating system layer running on top of the hardware layer, and an application layer running on the operating system. The hardware layer includes hardware such as a central processing unit (CPU), a memory management unit (MMU), and memory. The operating system can be any one or more computer operating systems that control the electronic device through processes, such as Linux, Unix, Android, iOS, or Windows. Furthermore, in this embodiment of the invention, the electronic device can be a smartphone, tablet computer, or other handheld device, or a desktop computer, portable computer, or other electronic device; there is no particular limitation in this embodiment.

[0131] In this embodiment of the invention, the executing entity for electronic device control can be an electronic device itself, or a functional module within an electronic device capable of calling and executing a program. The electronic device can obtain the firmware corresponding to the storage medium. This firmware is provided by the supplier, and different storage media may have the same or different firmware; no limitation is made here. After obtaining the firmware corresponding to the storage medium, the electronic device can write this firmware into the storage medium; specifically, it burns the firmware corresponding to the storage medium into the storage medium. The process of burning the firmware into the storage medium can be implemented using existing technology, and will not be elaborated upon in this embodiment of the invention.

[0132] Electronic devices can also obtain reset commands corresponding to the storage media. The reset commands corresponding to the storage media are provided by the supplier. The reset commands corresponding to different storage media can be the same or different, and no restrictions are imposed here.

[0133] At this time, the storage medium of the electronic device is a storage medium on which the corresponding firmware has been written. The electronic device can respond to the reset command corresponding to the storage medium on which the corresponding firmware has been written, thereby resetting the storage medium on which the corresponding firmware has been written according to the reset command. The process of resetting the storage medium according to the reset command can be implemented by existing technology and will not be described in detail in this embodiment of the invention.

[0134] For ease of description, the above devices are described separately by function as various units and modules. Of course, in implementing this application, the functions of each unit and module can be implemented in one or more software and / or hardware.

[0135] It will be understood by those skilled in the art that, unless otherwise defined, all terms used herein (including technical and scientific terms) have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. It should also be understood that terms such as those defined in general dictionaries should be understood to have the meaning consistent with their meaning in the context of the prior art, and should not be interpreted in an idealized or overly formal sense unless specifically defined.

[0136] For the sake of simplicity, the method embodiments are described as a series of actions. However, those skilled in the art should understand that the embodiments of the present invention are not limited to the described order of actions, because according to the embodiments of the present invention, some steps can be performed in other orders or simultaneously. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are preferred embodiments, and the actions involved are not necessarily essential to the embodiments of the present invention.

[0137] As can be seen from the above description of the embodiments, those skilled in the art can clearly understand that this application can be implemented by means of software plus necessary general-purpose hardware platforms. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in various embodiments or some parts of the embodiments of this application.

[0138] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method of analyzing high risk test cases, the method comprising: The analysis high-risk test case method comprises: Step 1, test start, acquire the historical defect list of the vehicle in mass production; According to the historical defect list, the corresponding module information is extracted, and the defect quantity statistical analysis is carried out to collect the defect characteristic information; Step 2, execute the smoke test case of the new vehicle model, and perform the surrounding function point inspection to obtain the test result of the new vehicle model; Wherein, the test result includes the executed failed case characteristics; Step 3, based on the defect characteristics and the executed failed case characteristics, analyze the high-risk test case of the new vehicle model, and acquire the minimum test set; Step 4, execute the minimum test set acquired in step 3, update the test result, and report the newly found defects; Step 5, add the newly found defects reported in step 4 to the historical defect list; Return to step 3 and continue to execute step 3 and step 4 until the test is completed.

2. The method of claim 1, wherein, The step 3 comprises: Step 31, configure attribute values for each test case; The attribute values include the module to which the test case belongs, the test case priority, the test case defect number, the test case risk value, the test case preparation environment time, and the test case execution time value information.

3. The method of claim 1, wherein, The step 3 comprises: Step 32, according to the defect characteristics and the executed failed case characteristics, update the attribute values of the corresponding test case, including increasing the test case defect number by 1; According to the historical defects and the executed failed cases, it is judged whether a preset serious problem is triggered; If yes, the test case risk value is increased by 1.

4. The method of claim 1, wherein, The step 3 comprises: Step 33, analyzing the high-risk test case of the new vehicle model comprises calculating the high-risk case coefficient; The calculation of the high-risk case coefficient comprises taking 25% of the test case risk value, 25% of the test case defect number, 20% of the test case priority and the test case belonging module, 20% of the test case execution time, and 10% of the test case preparation environment time as the weighted coefficients to comprehensively evaluate the high-risk case coefficient of each test case; Wherein, the shorter the time, the higher the weight contribution.

5. The method of claim 1, wherein, The step 3 comprises: Step 34, according to the preset number of to-be-executed test cases, select the test cases with high risk case coefficients in the front to form the minimum test set.

6. The method of claim 1, wherein, The step 3 comprises: The serious problem includes the problem types of flashback and function failure.

7. A system for analyzing high risk test cases, the system comprising: The analysis high-risk test case system comprises: A historical defect list module is configured to acquire the historical defect list of the vehicle in mass production at the beginning of the test; According to the historical defect list, the corresponding module information is extracted, and the defect quantity statistical analysis is carried out to collect the defect characteristic information; A smoke test case module is configured to execute the smoke test case of the new vehicle model, and perform the surrounding function point inspection to obtain the test result of the new vehicle model; Wherein, the test result includes the executed failed case characteristics; A minimum test set module is configured to analyze the high-risk test case of the new vehicle model based on the defect characteristics and the executed failed case characteristics, and acquire the minimum test set; A report new discovery module is configured to execute the acquired minimum test set, update the test result, and report the newly found defects; A push defect list module is configured to add the newly found defects reported to the historical defect list; Loop test module for returning to do loop, continue to execute until the test ends.

8. An electronic device, comprising: Comprise: A processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory complete the communication among each other through the communication bus; The memory stores a computer program, when the computer program is executed by the processor, the processor executes the steps of the method for analyzing high-risk test cases as claimed in any one of claims 1 to 7.

9. A computer-readable storage medium, characterized in that, The memory stores a computer program executable by the electronic device, when the computer program runs on the electronic device, the electronic device executes the steps of the method for analyzing high-risk test cases as claimed in any one of claims 1 to 7.

10. A risk testing platform, characterized in that, Comprise: An electronic device for implementing the steps of the method for analyzing high-risk test cases as claimed in any one of claims 1 to 7; A processor, the processor runs a program, when the program runs from the data output by the electronic device, the steps of the method for analyzing high-risk test cases as claimed in any one of claims 1 to 7 are executed; A storage medium for storing a program, when the program runs, the steps of the method for analyzing high-risk test cases as claimed in any one of claims 1 to 7 are executed for the data output from the electronic device.

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