CN115809203B - Dynamic nesting method and device for software test cases and application of dynamic nesting method and device - Google Patents

Dynamic nesting method and device for software test cases and application of dynamic nesting method and device Download PDF

Info

Publication number
CN115809203B
CN115809203B CN202310070856.5A CN202310070856A CN115809203B CN 115809203 B CN115809203 B CN 115809203B CN 202310070856 A CN202310070856 A CN 202310070856A CN 115809203 B CN115809203 B CN 115809203B
Authority
CN
China
Prior art keywords
test
point
test case
functional
case
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Active
Application number
CN202310070856.5A
Other languages
Chinese (zh)
Other versions
CN115809203A (en
Inventor
王忠泉
请求不公布姓名
刘剑
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Hangzhou Roledith Technology Co ltd
Original Assignee
Hangzhou Roledith Technology Co ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Hangzhou Roledith Technology Co ltd filed Critical Hangzhou Roledith Technology Co ltd
Priority to CN202310070856.5A priority Critical patent/CN115809203B/en
Publication of CN115809203A publication Critical patent/CN115809203A/en
Application granted granted Critical
Publication of CN115809203B publication Critical patent/CN115809203B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • YGENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02DCLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
    • Y02D10/00Energy efficient computing, e.g. low power processors, power management or thermal management

Landscapes

  • Debugging And Monitoring (AREA)

Abstract

The application provides a dynamic nesting method and device for software test cases and application thereof, comprising the steps of acquiring all test points covered by all tested modules and carding; numbering according to carding results; generating a test case library for each test point design and setting priority; combining the numbers into each test case and outputting the numbers; extracting the number of the functional point from the functional point of the detected defect; extracting and executing the test cases with high priority matched with any one or more of the numbers from the test case library; if successful, ending; if the test case fails, acquiring the rest cases with different number dimensions in the number of the failed case and the number policy when the test case is generated, and continuing to execute the rest cases; whether the test case to be added in the test case library contains the number dimension or not and the priority is high; if yes, reserving execution; if not, discarding; and repeatedly executing until loop nesting is finished. The method and the device can improve accuracy and integrity of regression defects, and enable regression tests to be dependent.

Description

Dynamic nesting method and device for software test cases and application of dynamic nesting method and device
Technical Field
The application relates to the technical field of software testing, in particular to a dynamic nesting method and device for software testing cases and application thereof.
Background
At present, most methods select the use cases of functional modules related to defects and then perform peripheral point detection as the use cases of regression tests or according to the functional characteristics of the defects, and the method has larger difference in accuracy due to the difference of experience level of testers, and has the problem of time waste if the corresponding and related modules are selected to execute.
Therefore, a method and a device for dynamically nesting software test cases, which can save regression time and improve the determinability of regression test, and application thereof are needed to solve the problems in the prior art.
Disclosure of Invention
The embodiment of the application provides a dynamic nesting method and device for software test cases and application thereof, and aims at solving the problems of long regression time, low accuracy and the like in the prior art.
The core technology of the invention mainly classifies and assigns numbers to test cases according to the relevance of functions of the test cases in the stage of case design, and can rapidly screen out of a plurality of test cases as a basic basis of regression test according to defect modification characteristics during defect regression.
In a first aspect, the present application provides a method for dynamically nesting software test cases, the method comprising the steps of:
s00, acquiring all test points covered by all tested modules, and combing the transverse and longitudinal functional association of each test point;
wherein the horizontal function association represents a function point, and the vertical function association represents a flow change of the function point;
s10, numbering each test point according to a carding result, wherein the numbers at least comprise a use case function module number a, a function point number b and a flow number c;
s20, designing and generating a test case library for each test point, and setting priority for each test case;
s30, combining the numbers into each test case and outputting the numbers;
s40, starting from the functional point of the tested defect during regression testing, extracting a case functional module number a, a functional point number b and a flow number c of the functional point;
s50, extracting a test case with at least one priority matched with any one or more of a case functional module number a, a functional point number b and a flow number c from a test case library, and executing the test case;
s60, if the execution is successful, ending the functional point regression test; if the execution fails, acquiring different number dimensions in the number strategies of the failed case numbers a, b and c and the number strategies when the test case is generated, and finishing the continuous execution of the other cases;
s70, taking the acquired number dimension as a core, and entering a test case library to be added to determine whether the test case contains the number dimension and has high priority;
s80, if yes, reserving adding and executing; if not, discarding;
and S90, repeatedly executing the steps S60-S80 until the loop nesting is finished.
Further, in step S00, the test point is the smallest molecule of the functional point.
Further, in step S00, the association of the horizontal functions is that the same or similar function points appear in different modules, and the association of the vertical functions is that the state of the corresponding function points changes, so that the state of the subsequent flow is changed.
Further, in step S10, the case function module number a is a range number and a directional number, the function point number b is a unified number given to the whole function point analyzed by the function point, the whole function point appears in other modules, and the flow number c is a unified number given to the whole function analyzed by the function point and having an influence on the subsequent flow.
Further, in step S20, the priority includes high, medium, and low.
Further, the medium-high priority in the priority is a key function case under the main flow, the medium priority in the priority is a test case except for the high priority and the low priority, and the low priority is a function case which has no influence or almost no influence on the system use or is mostly covered by the medium-high test case.
Further, in step S10, the other number for distinction is the feature number d.
In a second aspect, the present application provides a software test case dynamic nesting device, including:
the acquisition and carding module is used for acquiring all test points covered by all tested modules and carding the transverse and longitudinal functional association of each test point;
wherein the horizontal function association is that the same or similar function points appear in different modules, and the vertical function association is that the state change of the subsequent flow is caused by the state change of the corresponding function points;
the numbering module is used for numbering each test point according to the carding result, and the numbering comprises a use case function module numbering a, a function point numbering b, a flow numbering c and a feature numbering d;
the test cases and the generation module thereof are used for designing and generating a test case library for each test point and setting priority for each test case; combining the numbers into each test case and outputting the numbers;
the execution module starts from the functional point of the tested defect and extracts the case functional module number a, the functional point number b and the flow number c of the functional point during regression testing; extracting a test case with at least one priority matched with any one or more of a case functional module number a, a functional point number b and a flow number c from a test case library, and executing the test case;
the nesting module is used for ending the functional point regression test if the execution is successful; if the execution fails, acquiring different number dimensions in the number strategies of the failed case numbers a, b and c and the number strategies when the test case is generated, and finishing the continuous execution of the other cases; taking the acquired number dimension as a core, entering a test case library to determine whether the test case to be added contains the number dimension and has high priority; if yes, keeping adding and executing; if not, discarding; repeatedly executing until the loop nesting is finished;
and the output module is used for outputting the test result.
In a third aspect, the present application provides an electronic device comprising a memory having a computer program stored therein and a processor configured to run the computer program to perform the software test case dynamic nesting method described above.
In a fourth aspect, the present application provides a readable storage medium having stored therein a computer program comprising program code for controlling a process to execute a process comprising a method of dynamic nesting according to the software test case described above.
The main contributions and innovation points of the invention are as follows: 1. compared with the prior art, the method and the device have the advantages that through item association function points and process state changes, numbering and priority setting are carried out, and a circulation nesting process is designed, the accuracy and the integrity of regression defects can be improved to a large extent, regression tests can be made to be dependent, and the application range is wider;
2. compared with the prior art, the method and the device have the advantages that test cases can be classified and numbered according to the relevance of functions of the test cases in the case design stage, the test cases can be rapidly screened out from a plurality of test cases according to defect modification characteristics to serve as a basic basis of regression test during defect regression, case level positioning can be rapidly performed during regression test, regression time is saved, determinability of the regression test is improved, and the method and the device are more logical and stable.
The details of one or more embodiments of the application are set forth in the accompanying drawings and the description below to provide a more thorough understanding of the other features, objects, and advantages of the application.
Drawings
The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiments of the application and together with the description serve to explain the application and do not constitute an undue limitation to the application. In the drawings:
FIG. 1 is a flow chart of a software test case dynamic nesting method according to embodiments of the present application;
fig. 2 is a schematic diagram of a hardware structure of an electronic device according to an embodiment of the present application.
Detailed Description
Reference will now be made in detail to exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, the same numbers in different drawings refer to the same or similar elements, unless otherwise indicated. The implementations described in the following exemplary embodiments do not represent all implementations consistent with one or more embodiments of the present specification. Rather, they are merely examples of apparatus and methods consistent with aspects of one or more embodiments of the present description as detailed in the accompanying claims.
It should be noted that: in other embodiments, the steps of the corresponding method are not necessarily performed in the order shown and described in this specification. In some other embodiments, the method may include more or fewer steps than described in this specification. Furthermore, individual steps described in this specification, in other embodiments, may be described as being split into multiple steps; while various steps described in this specification may be combined into a single step in other embodiments.
Most of the current methods are to select the use cases of the functional modules related to the defect and then use the selected use cases as regression test use cases or perform peripheral spot inspection according to the functional characteristics of the defect, and the method is different according to the experience level of testers, has large difference in accuracy, and has the problem of time waste if the corresponding and related modules are selected to execute.
Based on the above, the method and the device solve the problems in the prior art by classifying and assigning the test cases to numbers according to the relevance of the functions of the test cases based on the case design stage.
Example 1
The application aims to provide a dynamic nesting method for software test cases, and specifically relates to a method for dynamically nesting the software test cases, which comprises the following steps of:
s00, acquiring all test points covered by all tested modules, and combing the transverse and longitudinal functional association of each test point;
wherein, the horizontal function association is that the same or similar function points appear in different modules, and the vertical function association is that the state change of the subsequent flow is caused by the state change of the corresponding function points;
the test points are the smallest molecules of the functional points, and the granularity can be slightly larger, so that the test points are thinned when the use cases are written;
s10, numbering each test point according to a carding result, wherein the numbers at least comprise a use case function module number a, a function point number b, a flow number c and other characteristic numbers d for distinguishing;
in the present embodiment, the functional module a is generally a module number or the like in a range or a directivity number (referred to herein as a);
the function point number b is a uniform number (b is used for reference herein) for the whole function point which is analyzed for the function point and also appears in other modules;
the flow number c is a uniform number (c is used herein) given to the whole flow of the function which is analyzed for the function point and has an influence on the subsequent flow;
s20, designing and generating a test case library for each test point, and setting a priority for each test case, wherein the priorities are generally high, medium and low;
in this embodiment, each test point is designed to generate a test case, a priority is set for the test case, the priority is high, medium and low, and according to the definition of the actual functional point and the requirement, the high is a key functional case under the general main flow, the low is a functional case which has little influence on the system use or is mostly covered by the medium and high-level cases, and the medium is other cases except the high and low levels;
s30, combining the numbers into each test case (a-b-c-d) and outputting the numbers;
s40, starting from the functional point of the tested defect during regression testing, extracting a case functional module number a, a functional point number b and a flow number c of the functional point;
s50, extracting a test case with at least one priority matched with any one or more of a case functional module number a, a functional point number b and a flow number c from a test case library, and executing the test case;
s60, if the execution is successful, ending the functional point regression test; if the execution fails, acquiring different number dimensions in the number strategies of the failed case numbers a, b and c and the number strategies when the test case is generated, and finishing the continuous execution of the other cases;
s70, taking the acquired number dimension as a core, and entering a test case library to be added to determine whether the test case contains the number dimension and has high priority;
s80, if yes, reserving adding and executing; if not, discarding;
and S90, repeatedly executing the steps S60-S80 until the loop nesting is finished.
In order to better illustrate the solution of the present application, the following is taken as an example of regression of a search function of a certain module:
before the steps S00-S30 are executed according to the application, a test case library written in advance is used for screening out the test case with high and medium priority of the function, wherein the test case library comprises a function module number a, a function point number b and a flow number c; the number a corresponds to the module where the function is located, the number b is a search function, and the number c is the flow where the function is located, such as list display, page turning, export and the like;
when the regression is defective, extracting a, namely a module, b, namely a search function and c, namely a flow of the search function under the module according to the step S40, wherein the priority of matching any one or more numbers is a test case in high and medium, and executing the test case;
if the execution is successful, the function point regression is finished;
if the list display function fails (case number: sbgl-ss-lbzs-001 (equipment management-search-list display-001)) in the executing process, finding out different number dimensions (lbzs) in the number dimensions of the failed case numbers a, b and c and the number strategies ((sbgl, ss) (equipment management-search)) of the case generation, and continuing to execute the rest cases;
with the lbzs number as the core, the use cases with the lbzs number (sbgl-lbzs-dc-001 (device management-list presentation-export-001), etc.) are pulled in the test case library and executed, and nested in this loop until the test passes.
Example two
Based on the same conception, the application also provides a dynamic nesting device for the software test cases, which comprises the following steps:
the acquisition and carding module is used for acquiring all test points covered by all tested modules and carding the transverse and longitudinal functional association of each test point;
wherein the horizontal function association is that the same or similar function points appear in different modules, and the vertical function association is that the state change of the subsequent flow is caused by the state change of the corresponding function points;
the numbering module is used for numbering each test point according to the carding result, and the numbering comprises a use case function module numbering a, a function point numbering b, a flow numbering c and a feature numbering d;
the test cases and the generation module thereof are used for designing and generating a test case library for each test point and setting priority for each test case; combining the numbers into each test case and outputting the numbers;
the execution module starts from the functional point of the tested defect and extracts the case functional module number a, the functional point number b and the flow number c of the functional point during regression testing; extracting a test case with at least one priority matched with any one or more of a case functional module number a, a functional point number b and a flow number c from a test case library, and executing the test case;
the nesting module is used for ending the functional point regression test if the execution is successful; if the execution fails, acquiring different number dimensions in the number strategies of the failed case numbers a, b and c and the number strategies when the test case is generated, and finishing the continuous execution of the other cases; taking the acquired number dimension as a core, entering a test case library to determine whether the test case to be added contains the number dimension and has high priority; if yes, keeping adding and executing; if not, discarding; repeatedly executing until the loop nesting is finished;
and the output module is used for outputting the test result.
Example III
This embodiment also provides an electronic device, referring to fig. 2, comprising a memory 404 and a processor 402, the memory 404 having stored therein a computer program, the processor 402 being arranged to run the computer program to perform the steps of any of the method embodiments described above.
In particular, the processor 402 may include a Central Processing Unit (CPU), or an Application Specific Integrated Circuit (ASIC), or may be configured to implement one or more integrated circuits of embodiments of the present application.
The memory 404 may include, among other things, mass storage 404 for data or instructions. By way of example, and not limitation, memory 404 may comprise a Hard Disk Drive (HDD), floppy disk drive, solid State Drive (SSD), flash memory, optical disk, magneto-optical disk, tape, or Universal Serial Bus (USB) drive, or a combination of two or more of these. Memory 404 may include removable or non-removable (or fixed) media, where appropriate. Memory 404 may be internal or external to the data processing apparatus, where appropriate. In a particular embodiment, the memory 404 is a Non-Volatile (Non-Volatile) memory. In particular embodiments, memory 404 includes Read-only memory (ROM) and Random Access Memory (RAM). Where appropriate, the ROM may be a mask-programmed ROM, a Programmable ROM (PROM), an Erasable PROM (EPROM), an Electrically Erasable PROM (EEPROM), an electrically rewritable ROM (EAROM) or FLASH memory (FLASH) or a combination of two or more of these. The RAM may be Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM) where appropriate, and the DRAM may be fast page mode dynamic random access memory 404 (FPMDRAM), extended Data Output Dynamic Random Access Memory (EDODRAM), synchronous Dynamic Random Access Memory (SDRAM), or the like.
Memory 404 may be used to store or cache various data files that need to be processed and/or used for communication, as well as possible computer program instructions for execution by processor 402.
The processor 402 implements any of the software test case dynamic nesting methods of the above embodiments by reading and executing computer program instructions stored in the memory 404.
Optionally, the electronic apparatus may further include a transmission device 406 and an input/output device 408, where the transmission device 406 is connected to the processor 402 and the input/output device 408 is connected to the processor 402.
The transmission device 406 may be used to receive or transmit data via a network. Specific examples of the network described above may include a wired or wireless network provided by a communication provider of the electronic device. In one example, the transmission device includes a network adapter (Network InterfaceController, simply referred to as NIC) that can connect to other network devices through the base station to communicate with the internet. In one example, the transmission device 406 may be a Radio Frequency (RF) module, which is configured to communicate with the internet wirelessly.
The input-output device 408 is used to input or output information. In this embodiment, the input information may be software to be tested, and the output information may be a test result, and the like.
Example IV
The present embodiment also provides a readable storage medium having stored therein a computer program comprising program code for controlling a process to execute the process, the process comprising the software test case dynamic nesting method according to the first embodiment.
It should be noted that, specific examples in this embodiment may refer to examples described in the foregoing embodiments and alternative implementations, and this embodiment is not repeated herein.
In general, the various embodiments may be implemented in hardware or special purpose circuits, software, logic or any combination thereof. Some aspects of the invention may be implemented in hardware, while other aspects may be implemented in firmware or software which may be executed by a controller, microprocessor or other computing device, although the invention is not limited thereto. While various aspects of the invention may be illustrated and described as block diagrams, flow charts, or using some other pictorial representation, it is well understood that these blocks, apparatus, systems, techniques or methods described herein may be implemented in, as non-limiting examples, hardware, software, firmware, special purpose circuits or logic, general purpose hardware or controller or other computing devices, or some combination thereof.
Embodiments of the invention may be implemented by computer software executable by a data processor of a mobile device, such as in a processor entity, or by hardware, or by a combination of software and hardware. Computer software or programs (also referred to as program products) including software routines, applets, and/or macros can be stored in any apparatus-readable data storage medium and they include program instructions for performing particular tasks. The computer program product may include one or more computer-executable components configured to perform embodiments when the program is run. The one or more computer-executable components may be at least one software code or a portion thereof. In addition, in this regard, it should be noted that any blocks of the logic flows as illustrated may represent program steps, or interconnected logic circuits, blocks and functions, or a combination of program steps and logic circuits, blocks and functions. The software may be stored on physical media such as memory chips or memory blocks implemented within the processor, magnetic media such as hard or floppy disks, and optical media such as, for example, DVDs and data variants thereof, CDs, etc. The physical medium is a non-transitory medium.
It should be understood by those skilled in the art that the technical features of the above embodiments may be combined in any manner, and for brevity, all of the possible combinations of the technical features of the above embodiments are not described, however, they should be considered as being within the scope of the description provided herein, as long as there is no contradiction between the combinations of the technical features.
The foregoing examples merely represent several embodiments of the present application, the description of which is more specific and detailed and which should not be construed as limiting the scope of the present application in any way. It should be noted that variations and modifications can be made by those skilled in the art without departing from the spirit of the present application, which falls within the scope of the present application. Accordingly, the scope of protection of the present application shall be subject to the appended claims.

Claims (10)

1. The dynamic nesting method for the software test cases is characterized by comprising the following steps of:
s00, acquiring all test points covered by all tested modules, and combing the transverse and longitudinal functional association of each test point;
wherein the horizontal function association represents a function point, and the vertical function association represents a flow change of the function point;
s10, numbering each test point according to a carding result, wherein the numbers at least comprise a use case function module number a, a function point number b and a flow number c;
s20, designing and generating a test case library for each test point, and setting priority for each test case;
s30, combining the numbers into each test case and outputting the numbers;
s40, starting from the functional point of the tested defect during regression testing, extracting a case functional module number a, a functional point number b and a flow number c of the functional point;
s50, extracting a test case with at least one or more matched priorities of a case functional module number a, a functional point number b and a flow number c from the test case library, and executing the test case;
s60, if the execution is successful, ending the functional point regression test; if the execution fails, acquiring different number dimensions in the number strategies of the failed case numbers a, b and c and the number strategies when the test case is generated, and finishing the continuous execution of the other cases;
s70, taking the acquired number dimension as a core, entering the test case library, and judging whether the test case to be added in the test case library contains the number dimension and has high priority;
s80, if yes, reserving adding and executing; if not, discarding;
and S90, repeatedly executing the steps S60-S80 until the loop nesting is finished.
2. The method for dynamic nesting of software test cases according to claim 1, wherein in step S00, said test point is a minimum molecule of said functional point.
3. The method of claim 1, wherein in step S00, the horizontal functional association is that the same or similar functional points occur in different modules, and the vertical functional association is that the state of the corresponding functional points changes, so that the state of the subsequent flow changes.
4. The method of claim 1, wherein in step S10, the case function module number a is a range number and a directional number, the function point number b is a unified number given to an overall function point analyzed by the function point, the overall function point appears in other modules, and the flow number c is a unified number given to a flow and a functional whole affecting a subsequent flow analyzed by the function point.
5. The method for dynamic nesting of software test cases according to claim 1, wherein in step S20, said priorities include high, medium, and low.
6. The method for dynamically nesting software test cases according to claim 5, wherein the medium-high priority is a main-flow key function case, the medium-high priority is a test case except for the high priority and the low priority, and the low priority is a function case which has no influence or little influence on system use or is mostly covered by the medium-high priority test case.
7. The method for dynamic nesting of software test cases according to any one of claims 1 to 6, wherein in step S10, the other number used for distinguishing is a feature number d.
8. A software test case dynamic nesting device, comprising:
the acquisition and carding module is used for acquiring all test points covered by all tested modules and carding the transverse and longitudinal functional association of each test point;
wherein the horizontal function association is that the same or similar function points appear in different modules, and the vertical function association is that the state change of the subsequent flow is caused by the state change of the corresponding function points;
the numbering module is used for numbering each test point according to the carding result, and the numbering comprises a use case function module numbering a, a function point numbering b, a flow numbering c and a feature numbering d;
the test cases and the generation module thereof are used for designing and generating a test case library for each test point and setting priority for each test case; combining the numbers into each test case and outputting the numbers;
the execution module starts from the functional point of the tested defect and extracts the case functional module number a, the functional point number b and the flow number c of the functional point during regression testing; extracting a test case with at least one priority matched with any one or more of a case functional module number a, a functional point number b and a flow number c from a test case library, and executing the test case;
the nesting module is used for ending the functional point regression test if the execution is successful; if the execution fails, acquiring different number dimensions in the number strategies of the failed case numbers a, b and c and the number strategies when the test case is generated, and finishing the continuous execution of the other cases; taking the acquired number dimension as a core, entering a test case library to determine whether the test case to be added contains the number dimension and has high priority; if yes, keeping adding and executing; if not, discarding; repeatedly executing until the loop nesting is finished;
and the output module is used for outputting the test result.
9. An electronic device comprising a memory and a processor, wherein the memory has stored therein a computer program, the processor being arranged to run the computer program to perform the software test case dynamic nesting method of any of claims 1 to 7.
10. A readable storage medium, characterized in that the readable storage medium has stored therein a computer program comprising program code for controlling a process to execute a process comprising the software test case dynamic nesting method according to any one of claims 1 to 7.
CN202310070856.5A 2023-02-07 2023-02-07 Dynamic nesting method and device for software test cases and application of dynamic nesting method and device Active CN115809203B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202310070856.5A CN115809203B (en) 2023-02-07 2023-02-07 Dynamic nesting method and device for software test cases and application of dynamic nesting method and device

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202310070856.5A CN115809203B (en) 2023-02-07 2023-02-07 Dynamic nesting method and device for software test cases and application of dynamic nesting method and device

Publications (2)

Publication Number Publication Date
CN115809203A CN115809203A (en) 2023-03-17
CN115809203B true CN115809203B (en) 2023-04-25

Family

ID=85487529

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202310070856.5A Active CN115809203B (en) 2023-02-07 2023-02-07 Dynamic nesting method and device for software test cases and application of dynamic nesting method and device

Country Status (1)

Country Link
CN (1) CN115809203B (en)

Families Citing this family (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116662210B (en) * 2023-07-28 2023-09-29 杭州罗莱迪思科技股份有限公司 Interface regression testing method, device and application
CN117435514B (en) * 2023-12-21 2024-03-01 杭州罗莱迪思科技股份有限公司 Extraction method for smoke emission test case

Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101916222A (en) * 2010-08-09 2010-12-15 哈尔滨工程大学 Software testing method based on combination of control flow graph traversal and slice forward traversal
CN104461887A (en) * 2014-12-11 2015-03-25 吴翔虎 Embedded software black-box test case generation method based on dynamic model
CN108694123A (en) * 2018-05-14 2018-10-23 中国平安人寿保险股份有限公司 A kind of regression testing method, computer readable storage medium and terminal device
CN109062794A (en) * 2018-07-24 2018-12-21 北京奇艺世纪科技有限公司 A kind of the determination method, apparatus and electronic equipment of software evaluating result
CN110134588A (en) * 2019-04-16 2019-08-16 江苏大学 A kind of priorities of test cases sort method and test macro based on code and combined covering
CN111666221A (en) * 2020-07-03 2020-09-15 西安邮电大学 Software test data set amplification method based on longicorn stigma search

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101916222A (en) * 2010-08-09 2010-12-15 哈尔滨工程大学 Software testing method based on combination of control flow graph traversal and slice forward traversal
CN104461887A (en) * 2014-12-11 2015-03-25 吴翔虎 Embedded software black-box test case generation method based on dynamic model
CN108694123A (en) * 2018-05-14 2018-10-23 中国平安人寿保险股份有限公司 A kind of regression testing method, computer readable storage medium and terminal device
CN109062794A (en) * 2018-07-24 2018-12-21 北京奇艺世纪科技有限公司 A kind of the determination method, apparatus and electronic equipment of software evaluating result
CN110134588A (en) * 2019-04-16 2019-08-16 江苏大学 A kind of priorities of test cases sort method and test macro based on code and combined covering
CN111666221A (en) * 2020-07-03 2020-09-15 西安邮电大学 Software test data set amplification method based on longicorn stigma search

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
赵建平等.《一种轻量级软件自动化测试框架》.《火力与指挥控制》.2014,第39卷(第7期),第179-183页. *

Also Published As

Publication number Publication date
CN115809203A (en) 2023-03-17

Similar Documents

Publication Publication Date Title
CN115809203B (en) Dynamic nesting method and device for software test cases and application of dynamic nesting method and device
CN107273269B (en) Log analysis method and device
CN112100957B (en) Method, emulator, storage medium for debugging a logic system design
CN113391859B (en) Loading method, loading system and testing machine for improving loading performance of Pattern file
CN117033251B (en) Regression testing method and device for multi-version system of mobile electronic equipment
CN112526319A (en) Chip testing method and device, processor chip and server
CN115729817A (en) Method and device for generating and optimizing test case library, electronic equipment and storage medium
CN113488401B (en) Chip testing method and device
CN101017496A (en) Method and apparatus for automatically formatting data based on a best match test result type
CN111767210A (en) Policy testing method and device, computer equipment and storage medium
CN114355171B (en) Reconfigurable chip performance bottleneck detection platform, detection method and electronic equipment
CN115982053A (en) Method, device and application for detecting software source code defects
JP6715198B2 (en) Memory inspection device
CN115686535A (en) Inspection method and device for Kubernets cluster and application
CN114755552A (en) Semiconductor device testing method and device, electronic device, and storage medium
US20180060280A1 (en) Nonparametric method for measuring clustered level of time rank in binary data
KR20190062879A (en) Method and Apparatus for Analyzing Memory Using Characteristic of Spare Pivot Fault
US8726206B1 (en) Deadlock detection method and related machine readable medium
CN110442370B (en) Test case query method and device
CN109343792B (en) Storage space configuration method and device, computer equipment and storage medium
CN116662210B (en) Interface regression testing method, device and application
CN110023913A (en) The method and apparatus of test software
JP2014049165A (en) Semiconductor device, and memory test method
US20120109561A1 (en) Wafer test apparatus, wafer test method, and program
US6721915B2 (en) Memory testing method

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant