CN116893960A - Code quality detection methods, devices, computer equipment and storage media - Google Patents

Abstract

The present application relates to a code quality detection method, apparatus, computer device, storage medium and computer program product. The method comprises the steps of carrying out static analysis on a code to be detected through a pre-configured static analysis tool to obtain a static analysis result, generating a test case according to the code to be detected, further operating the test case, obtaining dynamic log information in the operation process of the test case, and finally generating a quality detection result of the code to be detected according to the static analysis result and the dynamic log information. By combining static analysis with dynamic analysis, the automatic code quality detection can be realized, the code detection efficiency can be improved, and the labor cost can be reduced.

Description

Code quality detection methods, devices, computer equipment and storage media

Technical field

This application relates to the technical field of software testing, and in particular to a code quality detection method, device, computer equipment, storage medium and computer program product.

Background technique

In the software development process, software testing is an indispensable and important link. After a version of software coding is completed, the software testing process begins. First, static unit testing of the code, that is, static analysis, needs to be done. After static analysis of the code, the testers feedback coding rule issues to the software coders. Test issues are confirmed and changed by software coders.

However, the current testing method relies on sufficient connection and communication between testers and coders, which not only consumes large labor costs, but also has low testing efficiency.

Contents of the invention

Based on this, it is necessary to address the above technical problems and provide a code quality detection method, device, computer equipment, computer readable storage medium and computer program product that can improve code detection efficiency.

In the first aspect, this application provides a code quality detection method. The methods include:

Perform static analysis on the code to be detected through pre-configured static analysis tools to obtain static analysis results;

Generate test cases based on the code to be tested;

Run the test case and obtain dynamic log information during the execution of the test case;

According to the static analysis results and the dynamic log information, a quality detection result of the code to be detected is generated.

In one embodiment, generating test cases according to the code to be detected includes: based on target detection requirements, using an automatic test generation tool to generate test cases for the code to be detected.

In one embodiment, running the test case and obtaining dynamic log information during the execution of the test case includes: loading the underlying virtual machine LLVM compiler, and compiling the code to be detected through the LLVM compiler. ; Run the compiled code to be tested based on the test case, and obtain dynamic log information during the running process.

In one embodiment, running the test case and obtaining dynamic log information during the running process of the test case includes: using a target compiler to compile the code to be detected; and running all the compiled code based on the test case. Describe the code to be detected, and when the code to be detected is completed, a profiling data file is generated; the profiling data file is analyzed through a preset performance analysis tool to obtain corresponding log dynamic information.

In one embodiment, the target compiler is a compiler with a -pg compilation option.

In one embodiment, the quality inspection results include an improvement plan for the code to be inspected; after generating the quality inspection results for the code to be inspected, the method further includes: modifying the code according to the improvement plan. The code to be detected is updated to obtain the updated target code.

In a second aspect, this application also provides a code quality detection device. The device includes:

The static analysis module is used to statically analyze the code to be detected through pre-configured static analysis tools and obtain static analysis results;

A test case generation module, used to generate test cases based on the code to be tested;

A dynamic analysis module, used to run the test case and obtain dynamic log information during the execution of the test case;

A detection result generation module is configured to generate a quality detection result of the code to be detected based on the static analysis result and the dynamic log information.

In a third aspect, this application also provides a computer device. The computer device includes a memory and a processor. The memory stores a computer program. When the processor executes the computer program, the steps of the method described in the first aspect are implemented.

In a fourth aspect, this application also provides a computer-readable storage medium. The computer-readable storage medium has a computer program stored thereon, and when the computer program is executed by a processor, the steps of the method described in the first aspect are implemented.

In a fifth aspect, this application also provides a computer program product. The computer program product includes a computer program that implements the steps of the method described in the first aspect when executed by a processor.

The above-mentioned code quality detection methods, devices, computer equipment, storage media and computer program products perform static analysis on the code to be detected through pre-configured static analysis tools, obtain static analysis results, generate test cases based on the code to be detected, and then run the test cases , obtain the dynamic log information during the test case running process, and finally generate the quality detection results of the code to be detected based on the static analysis results and dynamic log information. By combining static analysis with dynamic analysis, it can realize automated code quality detection, which can not only improve the efficiency of code detection, but also reduce labor costs.

Description of the drawings

Figure 1 is a schematic flow chart of a code quality detection method in one embodiment;

Figure 2 is a schematic flowchart of the steps of obtaining dynamic log information in one embodiment;

Figure 3 is a schematic flowchart of the steps of obtaining dynamic log information in another embodiment;

Figure 4 is a structural block diagram of a code quality detection device in one embodiment;

Figure 5 is an internal structure diagram of a computer device in one embodiment.

Detailed ways

In order to make the purpose, technical solutions and advantages of the present application more clear, the present application will be further described in detail below with reference to the drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present application and are not used to limit the present application.

In one embodiment, as shown in Figure 1, a code quality detection method is provided, and the method can be applied to computer equipment. Specifically, it can include the following steps:

Step 102: Perform static analysis on the code to be detected using a pre-configured static analysis tool to obtain static analysis results.

The code to be tested may be the source code to be quality tested. Static analysis tools can be preset related configurations or plug-ins for static quality inspection of source code, for example, including but not limited to Clang-Tidy (a clang-based static code analysis framework), Cppcheck (a C/C++ code Defect static inspection tools), etc. The static analysis results are potential quality problems in the source code obtained after static quality inspection of the source code, such as grammatical errors, full name specifications, comment specifications, etc.

In this embodiment, when quality inspection is performed on the source code to be inspected, the computer device can perform static analysis on the code to be inspected through a preconfigured static analysis tool to obtain static analysis results.

Step 104: Generate test cases based on the code to be detected.

Among them, test cases refer to the description of testing tasks for a specific software product, embodying testing plans, methods, technologies and strategies. Its content includes test goals, test environment, input data, test steps, expected results, test scripts, etc., and finally forms a document. Simply put, a test case is a set of test inputs, execution conditions, and expected results compiled for a special goal, used to verify whether a specific software requirement is met.

In this embodiment, the computer device can generate corresponding test cases according to the target detection requirements of the code to be detected.

Step 106: Run the test case and obtain dynamic log information during the execution of the test case.

Among them, dynamic log information is relevant information collected during the running of test cases to characterize the dynamic detection process of the code to be detected, including, for example, execution time, memory usage, number of function calls, and other information.

In this embodiment, after the computer device generates the corresponding test case based on the above steps, it can run the test case and obtain dynamic log information during the running process of the test case.

Step 108: Generate quality detection results of the code to be detected based on the static analysis results and dynamic log information.

Since the static analysis results are the results of potential quality problems in the source code obtained after static quality inspection of the source code, the dynamic log information is the relevant information collected during the running of the test case to characterize the dynamic detection process of the code to be detected. Therefore , the computer equipment analyzes and integrates the static analysis results and dynamic log information to obtain the quality detection results of the code to be detected. Specifically, the quality inspection results can display the corresponding code quality scores and code improvement plans in the form of visual reports.

In the above code quality detection method, the pre-configured static analysis tool is used to statically analyze the code to be detected, obtain the static analysis results, generate test cases based on the code to be detected, and then run the test cases to obtain dynamic log information during the running of the test cases. , Finally, based on the static analysis results and dynamic log information, the quality detection results of the code to be detected are generated. By combining static analysis with dynamic analysis, it can realize automated code quality detection, which can not only improve the efficiency of code detection, but also reduce labor costs.

In one embodiment, in step 104, generating test cases according to the code to be detected may specifically include: based on target detection requirements, using an automatic test generation tool to generate test cases for the code to be detected. Among them, target detection requirements include but are not limited to code coverage, specific project requirements (that is, the projects to which the code to be detected is applied), etc. In this embodiment, when generating test cases, they can also be automatically generated based on the automatic test generation tool.

In one scenario, the automatic test generation tool is Google Test (Google C++ unit testing framework) as an example to further illustrate the test case generation process. In this embodiment, you can clone Google Test's GitHub (a hosting platform for open source and private software projects) repository and build a library, or install Google Test through a package manager (such as apt, yum, etc.). Then, in the project root directory, create a folder named "tests" and create a source file there to store the code to be tested, such as test_example.cpp. Then, in test_example.cpp, introduce the Google Test header file and define test cases to obtain test cases for the code to be tested. This embodiment uses an automatic test generation tool to generate test cases for the code to be detected, thereby reducing the workload of manually generating test cases and improving overall testing efficiency.

In one embodiment, as shown in Figure 2, in step 106, the test case is run to obtain dynamic log information during the running of the test case, which may include the following steps:

Step 202: Load the underlying virtual machine LLVM compiler, and compile the code to be detected through the LLVM compiler.

The LLVM (Low Level Virtual Machine) compiler is written in C++ and is used to optimize the compile-time (compile-time), link-time (link-time), and run-time ( run-time) and idle time (idle-time), remain open to developers and compatible with existing scripts.

In this embodiment, the LLVM compiler can be installed and loaded on the computer device, and the code to be detected can be compiled through the LLVM compiler. Specifically, the LLVM compiler can include clang (a lightweight compiler for C, C++, and Objective-C languages), clang++ (C++ compiler), and other tools. Then you can use the clang compiler with the Sanitizer Coverage option to compile the code to be detected and obtain the compiled code.

Step 204: Run the compiled code to be tested based on the test case, and obtain dynamic log information during the running process.

Specifically, the computer device can run the code to be tested compiled in the above steps based on the test case, thereby obtaining dynamic log information during the running process. This enables the collection of dynamic log information during code dynamic analysis through code instrumentation, further improving code detection efficiency.

In one embodiment, as shown in Figure 3, in step 106, run the test case and obtain dynamic log information during the running of the test case, which may include the following steps:

Step 302: Use the target compiler to compile the code to be detected.

Among them, the target compiler can be a compiler with the -pg compilation option. In this embodiment, the computer device can use a target compiler with the -pg compilation option to compile the code to be detected, thereby obtaining the compiled code.

Step 304: Run the compiled code to be tested based on the test case. After the code to be tested is completed, a profiling data file is generated.

Among them, the profiling data file can be collected code runtime data. Specifically, the computer device can run the code to be tested compiled in the above steps based on the test case, and when the code to be tested is completed, the profiling data file is generated. In this embodiment, the profiling data file may have a corresponding file name, such as “gmon.out”.

Step 306: Analyze the data file through a preset performance analysis tool to obtain corresponding log dynamic information.

Among them, the preset performance analysis tool can be gprof, which is a program time monitoring tool provided by GNU (a Unix-like operating system composed of free software), which can count the number of calls, time, and function call graph of each function. wait.

In this embodiment, the computer device can analyze the profiling data file generated in the above steps through a preset performance analysis tool, thereby obtaining corresponding log dynamic information. This enables the collection of dynamic log information during code dynamic analysis through performance analysis to improve code detection efficiency.

In one embodiment, in step 102, the code to be detected is statically analyzed using a preconfigured static analysis tool to obtain static analysis results, which may include:

First, the corresponding static analysis tool can be configured according to the project requirements and coding specifications. In this embodiment, the static analysis tool Clang-Tidy is used as an example for explanation. Then further create a configuration file named ".clang-tidy" and store this file in the project root directory so that Clang-Tidy can automatically read the configuration during execution. And add the checking rules that need to be enabled in the ".clang-tidy" file, such as clang-analyzer-* (an official static code analysis tool developed based on clang, used to detect code problems in advance during the compilation phase), cppcoreguidelines-* (C++ Core Guidelines), google-*, etc. Then customize the inspection rules as needed, and perform static analysis on the code to be detected based on the customized inspection rules to check for potential code quality issues, such as syntax errors, naming specifications, annotation specifications, etc., to obtain static analysis results. To achieve automatic static analysis of the code to be detected and save detection costs.

In one embodiment, the quality inspection results may also include an improvement plan for the code to be inspected; then in step 108, after generating the quality inspection results for the code to be inspected, the above method may further include: updating the code to be inspected according to the improvement plan. , get the updated object code. Among them, the improvement plan can be determined based on further analysis of static analysis results and dynamic log information, possible performance bottlenecks, and possible problematic code parts. The computer equipment can update the code to be detected according to the improvement plan, thereby obtaining the updated target code. In this way, problems in the source code can be fixed and the code quality can be improved.

In one embodiment, the above code quality detection method and related tools can also be integrated into the integrated development environment (IDE, Integrated Development Environment) and continuous integration (CI, Continuous integration) process to achieve automated source code quality assessment and optimization. , enabling code development teams to continuously monitor and improve code quality throughout the software development cycle.

It should be understood that although the steps in the flowcharts involved in the above-mentioned embodiments are shown in sequence as indicated by the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated in this article, there is no strict order restriction on the execution of these steps, and these steps can be executed in other orders. Moreover, at least some of the steps in the flowcharts involved in the above embodiments may include multiple steps or stages. These steps or stages are not necessarily executed at the same time, but may be completed at different times. The execution order of these steps or stages is not necessarily sequential, but may be performed in turn or alternately with other steps or at least part of the steps or stages in other steps.

Based on the same inventive concept, embodiments of the present application also provide a code quality detection device for implementing the above-mentioned code quality detection method. The solution to the problem provided by this device is similar to the solution recorded in the above method. Therefore, the specific limitations in the one or more code quality detection device embodiments provided below can be found in the code quality detection method mentioned above. Limitations will not be repeated here.

In one embodiment, as shown in Figure 4, a code quality detection device is provided, including: a static analysis module 402, a test case generation module 404, a dynamic analysis module 406 and a detection result generation module 408, wherein:

The static analysis module 402 is used to statically analyze the code to be detected through pre-configured static analysis tools to obtain static analysis results;

Test case generation module 404, used to generate test cases according to the code to be detected;

The dynamic analysis module 406 is used to run the test case and obtain dynamic log information during the execution of the test case;

The detection result generation module 408 is configured to generate a quality detection result of the code to be detected according to the static analysis result and the dynamic log information.

In one embodiment, the test case generation module is specifically configured to: based on target detection requirements, use an automatic test generation tool to generate test cases for the code to be detected.

In one embodiment, the dynamic analysis module is specifically used to: load the underlying virtual machine LLVM compiler, compile the code to be detected through the LLVM compiler; run the compiled code to be detected based on the test case, and obtain the execution Dynamic log information during the process.

In one embodiment, the dynamic analysis module is further configured to: use a target compiler to compile the code to be detected; run the compiled code to be detected based on the test case, and after the code to be detected is completed, generate Analyze the data file; analyze the profiling data file through a preset performance analysis tool to obtain corresponding log dynamic information.

In one embodiment, the target compiler is a compiler with a -pg compilation option.

In one embodiment, the quality inspection results include an improvement plan for the code to be detected; then the device further includes a code update module for updating the code to be detected according to the improvement plan, to obtain Updated object code.

Each module in the above code quality detection device can be implemented in whole or in part by software, hardware and combinations thereof. Each of the above modules may be embedded in or independent of the processor of the computer device in the form of hardware, or may be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

In one embodiment, a computer device is provided. The computer device may be a terminal, and its internal structure diagram may be shown in Figure 5 . The computer device includes a processor, memory, input/output interface, communication interface, display unit and input device. Among them, the processor, memory and input/output interface are connected through the system bus, and the communication interface, display unit and input device are connected to the system bus through the input/output interface. Wherein, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes non-volatile storage media and internal memory. The non-volatile storage medium stores operating systems and computer programs. This internal memory provides an environment for the execution of operating systems and computer programs in non-volatile storage media. The input/output interface of the computer device is used to exchange information between the processor and external devices. The communication interface of the computer device is used for wired or wireless communication with external terminals. The wireless mode can be implemented through WIFI, mobile cellular network, NFC (Near Field Communication) or other technologies. The computer program implements a code quality detection method when executed by a processor. The display unit of the computer equipment is used to form a visually visible picture, and may be a display screen, a projection device or a virtual reality imaging device. The display screen can be a liquid crystal display or an electronic ink display. The input device of the computer device can be a touch layer covered on the display screen, or it can be a button, trackball or touch pad provided on the computer device casing, or it can be External keyboard, trackpad or mouse, etc.

Those skilled in the art can understand that the structure shown in Figure 5 is only a block diagram of a partial structure related to the solution of the present application, and does not constitute a limitation on the computer equipment to which the solution of the present application is applied. The specific computer equipment can May include more or fewer parts than shown, or combine certain parts, or have a different arrangement of parts.

In one embodiment, a computer device is provided, including a memory and a processor. A computer program is stored in the memory. When the processor executes the computer program, it implements the following steps:

Perform static analysis on the code to be detected through pre-configured static analysis tools to obtain static analysis results;

Generate test cases based on the code to be tested;

Run the test case and obtain dynamic log information during the execution of the test case;

According to the static analysis results and the dynamic log information, a quality detection result of the code to be detected is generated.

In one embodiment, when the processor executes the computer program, it also implements the following steps: based on the target detection requirements, using an automatic test generation tool to generate test cases for the code to be detected.

In one embodiment, when the processor executes the computer program, the following steps are also implemented: loading the underlying virtual machine LLVM compiler, compiling the code to be detected through the LLVM compiler; running the compiled code to be detected based on the test case Code to obtain dynamic log information during operation.

In one embodiment, when the processor executes the computer program, the processor also implements the following steps: using a target compiler to compile the code to be tested; and running the compiled code to be tested based on the test case. When the code to be tested is completed. Finally, a profiling data file is generated; the profiling data file is analyzed through a preset performance analysis tool to obtain corresponding log dynamic information.

In one embodiment, the quality inspection results include an improvement plan for the code to be detected; when the processor executes the computer program, the following steps are also implemented: update the code to be detected according to the improvement plan to obtain an update the target code after.

In one embodiment, a computer-readable storage medium is provided with a computer program stored thereon. When the computer program is executed by a processor, the following steps are implemented:

Perform static analysis on the code to be detected through pre-configured static analysis tools to obtain static analysis results;

Generate test cases based on the code to be tested;

Run the test case and obtain dynamic log information during the execution of the test case;

According to the static analysis results and the dynamic log information, a quality detection result of the code to be detected is generated.

In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: based on the target detection requirements, an automatic test generation tool is used to generate test cases for the code to be detected.

In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: loading the underlying virtual machine LLVM compiler, compiling the code to be detected through the LLVM compiler; running the compiled code to be tested based on the test case Detect the code and obtain dynamic log information during operation.

In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: using a target compiler to compile the code to be tested; and running the compiled code to be tested based on the test case. When the code to be tested is run After completion, a profiling data file is generated; the profiling data file is analyzed through a preset performance analysis tool to obtain corresponding log dynamic information.

In one embodiment, the quality inspection results include an improvement plan for the code to be detected; when the computer program is executed by the processor, the following steps are also implemented: updating the code to be detected according to the improvement plan, to obtain Updated object code.

In one embodiment, a computer program product is provided, comprising a computer program that when executed by a processor implements the following steps:

Perform static analysis on the code to be detected through pre-configured static analysis tools to obtain static analysis results;

Generate test cases based on the code to be tested;

Run the test case and obtain dynamic log information during the execution of the test case;

According to the static analysis results and the dynamic log information, a quality detection result of the code to be detected is generated.

In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: based on the target detection requirements, an automatic test generation tool is used to generate test cases for the code to be detected.

In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: loading the underlying virtual machine LLVM compiler, compiling the code to be detected through the LLVM compiler; running the compiled code to be tested based on the test case Detect the code and obtain dynamic log information during operation.

In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: using a target compiler to compile the code to be tested; and running the compiled code to be tested based on the test case. When the code to be tested is run After completion, a profiling data file is generated; the profiling data file is analyzed through a preset performance analysis tool to obtain corresponding log dynamic information.

In one embodiment, the quality inspection results include an improvement plan for the code to be detected; when the computer program is executed by the processor, the following steps are also implemented: updating the code to be detected according to the improvement plan, to obtain Updated object code.

Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage. In the media, when executed, the computer program may include the processes of the above method embodiments. Any reference to memory, database or other media used in the embodiments provided in this application may include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive memory (ReRAM), magnetic variable memory (Magnetoresistive Random) Access Memory (MRAM), Ferroelectric Random Access Memory (FRAM), Phase Change Memory (PCM), graphene memory, etc. Volatile memory may include random access memory (Random Access Memory, RAM) or external cache memory. By way of illustration but not limitation, RAM can be in various forms, such as static random access memory (Static Random Access Memory, SRAM) or dynamic random access memory (Dynamic Random Access Memory, DRAM). The databases involved in the various embodiments provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include blockchain-based distributed databases, etc., but are not limited thereto. The processors involved in the various embodiments provided in this application may be general-purpose processors, central processing units, graphics processors, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to this.

The technical features of the above embodiments can be combined in any way. To simplify the description, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, all possible combinations should be used. It is considered to be within the scope of this manual.

The above-described embodiments only express several implementation modes of the present application, and their descriptions are relatively specific and detailed, but should not be construed as limiting the patent scope of the present application. It should be noted that, for those of ordinary skill in the art, several modifications and improvements can be made without departing from the concept of the present application, and these all fall within the protection scope of the present application. Therefore, the scope of protection of this application should be determined by the appended claims.

Claims (10)

1. A method for detecting code quality, the method comprising:

performing static analysis on the code to be detected through a pre-configured static analysis tool to obtain a static analysis result;

generating a test case according to the code to be detected;

running the test case and acquiring dynamic log information in the running process of the test case;

and generating a quality detection result of the code to be detected according to the static analysis result and the dynamic log information.

2. The method of claim 1, wherein the generating test cases from the code to be detected comprises:

and generating a test case for the code to be detected through an automatic test generation tool based on the target detection requirement.

3. The method of claim 1, wherein the running the test case, obtaining dynamic log information during the running of the test case, comprises:

loading an LLVM compiler of a bottom virtual machine, and compiling the code to be detected through the LLVM compiler;

and running the compiled code to be detected based on the test case, and acquiring dynamic log information in the running process.

4. The method of claim 1, wherein the running the test case, obtaining dynamic log information during the running of the test case, comprises:

compiling the code to be detected by adopting a target compiler;

running the compiled code to be detected based on the test case, and generating a profiling data file after the code to be detected is run;

analyzing the analysis data file through a preset performance analysis tool to obtain corresponding log dynamic information.

5. The method of claim 4, wherein the target compiler is a compiler with a-pg compilation option.

6. The method according to any one of claims 1 to 5, wherein the quality detection result comprises an improvement to the code to be detected; after the quality detection result of the code to be detected is generated, the method further comprises:

and updating the code to be detected according to the improved scheme to obtain updated target code.

7. A code quality detection apparatus, the apparatus comprising:

the static analysis module is used for carrying out static analysis on the code to be detected through a pre-configured static analysis tool to obtain a static analysis result;

the test case generation module is used for generating a test case according to the code to be detected;

the dynamic analysis module is used for running the test case and acquiring dynamic log information in the running process of the test case;

and the detection result generation module is used for generating a quality detection result of the code to be detected according to the static analysis result and the dynamic log information.

8. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor implements the steps of the method of any of claims 1 to 6 when the computer program is executed.

9. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the method of any of claims 1 to 6.

10. A computer program product comprising a computer program, characterized in that the computer program, when being executed by a processor, implements the steps of the method of any of claims 1 to 6.