CN117520184A - Test system for developing computer software - Google Patents
Test system for developing computer software Download PDFInfo
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- CN117520184A CN117520184A CN202311559704.8A CN202311559704A CN117520184A CN 117520184 A CN117520184 A CN 117520184A CN 202311559704 A CN202311559704 A CN 202311559704A CN 117520184 A CN117520184 A CN 117520184A
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- 238000012360 testing method Methods 0.000 title claims abstract description 103
- 238000004458 analytical method Methods 0.000 claims abstract description 21
- 230000010354 integration Effects 0.000 claims abstract description 12
- 238000007726 management method Methods 0.000 claims description 23
- 238000000034 method Methods 0.000 claims description 21
- 230000008569 process Effects 0.000 claims description 19
- 238000011161 development Methods 0.000 claims description 10
- 230000000007 visual effect Effects 0.000 claims description 8
- 230000007547 defect Effects 0.000 claims description 7
- 238000012549 training Methods 0.000 claims description 6
- 230000002159 abnormal effect Effects 0.000 claims description 5
- 238000013473 artificial intelligence Methods 0.000 claims description 5
- 238000005516 engineering process Methods 0.000 claims description 4
- 238000012545 processing Methods 0.000 claims description 4
- 238000013468 resource allocation Methods 0.000 claims description 4
- 238000005259 measurement Methods 0.000 claims description 3
- 238000012544 monitoring process Methods 0.000 claims description 2
- 238000003062 neural network model Methods 0.000 claims description 2
- 238000005457 optimization Methods 0.000 claims description 2
- 238000013135 deep learning Methods 0.000 abstract description 3
- 238000013522 software testing Methods 0.000 abstract description 3
- 238000004422 calculation algorithm Methods 0.000 description 2
- 238000010586 diagram Methods 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 230000008439 repair process Effects 0.000 description 2
- 230000005856 abnormality Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 230000006870 function Effects 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 238000003909 pattern recognition Methods 0.000 description 1
- 238000012552 review Methods 0.000 description 1
- 238000010998 test method Methods 0.000 description 1
- 230000001960 triggered effect Effects 0.000 description 1
Classifications
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F11/00—Error detection; Error correction; Monitoring
- G06F11/36—Preventing errors by testing or debugging software
- G06F11/3668—Software testing
- G06F11/3672—Test management
- G06F11/3684—Test management for test design, e.g. generating new test cases
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F11/00—Error detection; Error correction; Monitoring
- G06F11/36—Preventing errors by testing or debugging software
- G06F11/3668—Software testing
- G06F11/3672—Test management
- G06F11/3676—Test management for coverage analysis
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- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Computer Hardware Design (AREA)
- Quality & Reliability (AREA)
- Physics & Mathematics (AREA)
- General Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Debugging And Monitoring (AREA)
Abstract
The invention discloses a test system for developing computer software, which comprises an acquisition module, a test plan module, a test environment configuration module, a use case management module, a coverage rate analysis module, a test execution module, a result management module, an anomaly tracking and repairing module, a continuous integration module and an automation management module. According to the invention, the test cases are optimized through deep learning, and the machine is used for analyzing code coverage rate and the like, so that the efficiency and accuracy of software testing are improved.
Description
Technical Field
The invention relates to the technical field related to computer software development and test, in particular to a test system for computer software development.
Background
Software development is the process of building a software system or software parts of a system according to user requirements. Software development is a system project that includes demand capture, demand analysis, design, implementation, and testing. Software is typically implemented in a programming language. Development can be performed typically using software development tools.
In the development process of computer software, software testing has become an important means for guaranteeing the quality of software. Most of the existing computer software development tests are completed by manual intervention, the automatic level is not high, the test efficiency is low, the intelligent level is not high, and the increasingly complex and multilateral software requirements cannot be met.
Disclosure of Invention
Accordingly, in order to solve the above-mentioned drawbacks, the present invention provides a test system for developing computer software.
In order to achieve the above purpose, the present invention adopts the following technical scheme: a test system for developing computer software comprises an acquisition module, a test plan module, a test environment configuration module, a use case management module, a coverage rate analysis module, a test execution module, a result management module, an abnormality tracking and repairing module, a continuous integration module and an automation management module.
Preferably, the acquisition module collects various data in the development process, and generates a corresponding index report after processing and analysis;
preferably, the test plan module manages test targets and generates a detailed test plan;
preferably, the test environment configuration module acquires the software running environment requirement information, and sets and configures various environment parameters required by the software running environment requirement information
Preferably, the use case management module generates relevant test cases by using artificial intelligence and manages the corresponding use cases, and can be added, deleted and modified;
preferably, the coverage rate analysis module analyzes the code coverage rate in the test process by using a machine vision technology and trains and optimizes the machine vision technology;
preferably, the test execution module performs test operation by using generation and monitors a test process and a result;
preferably, the result management module manages and records each test result, analyzes the test result, positions abnormal problems, provides a visual report, and sends the visual report to a main responsible person for checking;
preferably, the anomaly tracking and repairing is performed according to the anomaly defect report, and the defect tracking is performed and the adjustment and optimization are performed by using a related tool;
preferably, the continuous integration module integrates the testing process into software development to realize continuous integration and testing, and performs data measurement and application management when codes are changed;
preferably, the automation management module automatically manages the test flow and the resource allocation according to preset rules and strategies.
Preferably, the data in the development process includes, but is not limited to, code type, code line number, code quality, and development time.
Preferably, the test environment configuration may be through a cloud environment comprising virtual machines and containers, each simulating a different operating system and network configuration, installing and configuring the required software tools.
Preferably, the test plan includes, but is not limited to, test type, resources required, test time.
Preferably, the generating test cases by using artificial intelligence may include building a neural network model according to requirements and characteristic analysis of software; training and optimizing the model by using training data, and comprehensively considering the functional modules and possible input and output conditions of the software to generate a comprehensive and efficient test case.
The invention has the beneficial effects that: the test cases are optimized through deep learning, and analysis such as code coverage rate and the like is carried out by using a machine, so that the efficiency and accuracy of software testing are improved.
Drawings
FIG. 1 is a schematic diagram of the structure of the present invention;
FIG. 2 is a schematic flow diagram of one embodiment of the present invention;
FIG. 3 is a schematic flow chart of the coverage analysis of the present invention.
Detailed Description
In order to further explain the technical scheme of the invention, the following is explained in detail through specific examples.
In one embodiment, as shown in fig. 1, the invention provides a test system for developing computer software, which comprises an acquisition module, a test plan module, a test environment configuration module, a use case management module, a coverage rate analysis module, a test execution module, a result management module, an anomaly tracking and repairing module, a continuous integration module and an automation management module.
The acquisition module collects various data parameters in the development process, including code types, code line numbers, code quality, development time and the like, processes related data, and analyzes and generates various index data blog reports.
The test plan module determines main targets and parameters of the test according to the collected software data information, and generates a corresponding test plan mainly comprising test types, resource allocation, test time, conditions and the like.
The test environment configuration module acquires the software running environment requirement information, and sets and configures various environment parameters including various parameters such as software, hardware, network and the like. For testing environments that are complex and diverse, a cloud environment comprising virtual machines and containers can be passed between, each simulating a different operating system and network configuration, installing and configuring the required software tools.
The case management module automatically generates corresponding test cases by using artificial intelligence, the test cases can be managed and optimized, and related editing operations can be executed according to actual conditions. And building a proper algorithm model according to the characteristics of software functions and the like and a deep learning algorithm, training and optimizing the model, importing relevant data parameters of the software into the model to generate test cases, and carrying out proper debugging and optimizing by combining with the analysis of actual running results.
The coverage rate analysis module utilizes machine vision to conduct code coverage rate analysis, and analysis data can be used for optimizing test cases. As shown in fig. 3, first, the execution path of the code is tracked and identified by the code instrumentation technique; then, identifying and classifying the code execution path using image processing and pattern recognition techniques; further, through processing the image, the characteristics and the attributes of the measured object can be extracted and compared with the preset rule; finally, machine vision collects data in the testing process in real time, and indexes such as code line coverage rate, condition coverage rate, path coverage rate and the like are calculated through analysis of the testing data and actual output data, and summarizing analysis is carried out.
The test execution module is used for generating and executing test operation and monitoring a test process and a result;
the result management module manages and records each test result, analyzes the test result, positions abnormal problems, provides a visual report, and sends the visual report to a main responsible person for checking; the visual report content comprises a test target, a test range, a test method, a test result, existing abnormal conditions and recommended measures, test time, participators and the like.
The software defects analyzed by the test are tracked by the anomaly tracking and repairing, and are adjusted and optimized by using related tools, and the repairing result is verified, so that the anomaly defects are ensured to be treated.
The continuous integration module integrates the testing process into software development to realize continuous integration and testing, and when codes are changed, the continuous integration module can be triggered to construct a testing module, and the corresponding execution operation is touched to enter an automatic testing analysis stage.
The automatic management module generates script information, generates preset rules and strategies, and each strategy formulates corresponding model data to carry out automatic management test flow and resource allocation.
In one embodiment, as shown in fig. 2, the working principle of the present invention may include the following steps:
s1, acquiring various data such as software requirements and related code information;
s2, generating corresponding test requirements according to software requirements, and generating corresponding automation management script information to set rules and strategies;
s3, generating corresponding test cases by combining software functional characteristics and demand conditions;
s4, coverage rate analysis is carried out, test cases are debugged, and coverage rate measurement is carried out after each debugging until coverage rate setting requirements are met;
s5, executing test operation by adopting the optimized test case;
s6, introducing the testing process into software development for continuous integration;
s7, storing analysis results of each execution, and generating a visual report for relevant personnel to take and review;
s8, optimizing automatic management according to the execution process data;
s9, tracking the abnormal defect data in the result, and generating corresponding treatment measures according to the analyzed conclusion and suggestion;
s10, a corresponding tool is called to execute repair operation, and repair is verified.
The foregoing is merely a preferred example of the present invention, and the present invention is not limited thereto, but it is to be understood that modifications and equivalents of some of the technical features described in the foregoing embodiments may be made by those skilled in the art, although the present invention has been described in detail with reference to the foregoing embodiments. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (5)
1. A test system for computer software development, characterized in that: the system comprises an acquisition module, a test plan module, a test environment configuration module, a use case management module, a coverage rate analysis module, a test execution module, a result management module, an anomaly tracking and repairing module, a continuous integration module and an automation management module;
the acquisition module is used for collecting various data in the development process, and generating a corresponding index report after processing and analyzing;
the test plan module manages test targets and generates a detailed test plan;
the test environment configuration module acquires the software running environment demand information and sets and configures various environment parameters required by the software running environment demand information;
the use case management module generates relevant test cases by utilizing artificial intelligence and manages the corresponding use cases, and can be added, deleted and modified;
the coverage rate analysis module is used for analyzing the code coverage rate in the test process by using a machine vision technology and training and optimizing the machine vision technology;
the test execution module is used for executing test operation by using generation and monitoring a test process and a result;
the result management module is used for managing and recording each test result, analyzing the test result, positioning abnormal problems, providing a visual report and sending the visual report to a main responsible person for checking;
the anomaly tracking and repairing are carried out, and defect tracking is carried out according to the anomaly defect report, and adjustment and optimization are carried out by utilizing a related tool;
the continuous integration module integrates the testing process into software development to realize continuous integration and testing, and performs data measurement and application management when the codes are changed;
and the automatic management module is used for automatically managing the test flow and the resource allocation according to preset rules and strategies.
2. A test system for computer software development as claimed in claim 1, wherein: the data in the development process include, but are not limited to, code type, code line number, code quality, development time.
3. A test system for computer software development as claimed in claim 1, wherein: the test environment configuration may be through a cloud environment comprising virtual machines and containers, each simulating a different operating system and network configuration, installing and configuring the required software tools.
4. A test system for computer software development as claimed in claim 1, wherein: the test plan includes, but is not limited to, test type, resources required, test time.
5. A test system for computer software development as claimed in claim 1, wherein: the generating test cases using artificial intelligence may include building a neural network model based on demand and characteristic analysis of the software; training and optimizing the model by using training data, and comprehensively considering the functional modules and possible input and output conditions of the software to generate a comprehensive and efficient test case.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
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| CN202311559704.8A CN117520184A (en) | 2023-11-22 | 2023-11-22 | Test system for developing computer software |
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| CN202311559704.8A CN117520184A (en) | 2023-11-22 | 2023-11-22 | Test system for developing computer software |
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| CN117520184A true CN117520184A (en) | 2024-02-06 |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117806980A (en) * | 2024-03-01 | 2024-04-02 | 西安中朗智控科技有限公司 | Automatic test case generating device based on large language model |
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- 2023-11-22 CN CN202311559704.8A patent/CN117520184A/en active Pending
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117806980A (en) * | 2024-03-01 | 2024-04-02 | 西安中朗智控科技有限公司 | Automatic test case generating device based on large language model |
| CN117806980B (en) * | 2024-03-01 | 2024-05-28 | 西安中朗智控科技有限公司 | Automatic test case generating device based on large language model |
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