A software quality integrated management method and system

Abstract

The application relates to the technical field of software development, in particular to a software quality integrated management method and system. The system comprises a requirement management module, a data processing module, a correlation relationship module, an execution record module, a quality analysis module, a test management module and a quality evaluation module. The requirement management module is used for determining requirements and formulating a test plan. The data processing module is used for collecting quality management data in a software development process and labeling the data. The correlation relationship module is used for establishing a correlation relationship between the data. The execution record module is used for recording operations in software development, testing and repairing processes and generating an execution log. The quality analysis module is used for constructing a quality evaluation model, calculating a software quality score and determining a software quality grade. The test management module is used for generating and executing test cases according to requirements to obtain evaluation data. The quality evaluation module is used for integrating and analyzing the evaluation data and comprehensively evaluating software quality. The technical scheme can efficiently and comprehensively realize quality management in the software development process and realize rapid tracing and positioning of quality problems.

Description

Technical Field

[0001] This invention relates to the field of software development technology, and specifically to an integrated software quality management method and system. Background Technology

[0002] With the rapid development of information technology, the software development industry is facing unprecedented challenges and opportunities. The complexity of software products is constantly increasing, and users' demands for software quality are also rising. Traditional software quality management methods often rely on manual and decentralized management approaches, leading to inefficient quality control during the software development process, difficulties in tracing problems, and the inability to timely and accurately assess the overall quality level of the software.

[0003] In existing technologies, software quality management is typically divided into several independent and relatively fragmented phases, such as requirements analysis, test planning, code development, test execution, and defect fixing. While this phased management approach helps to standardize the software development process to some extent, it also results in poor information flow between phases, severe data silos, and difficulty in forming a complete quality management loop.

[0004] First, in terms of requirements management, existing technologies often rely on traditional document management methods, such as Word and Excel. These tools have many inconveniences in terms of requirements changes, version control, and requirements traceability, and it is difficult to guarantee the completeness and consistency of requirements.

[0005] Secondly, in terms of data processing and establishing relationships, existing technologies lack efficient methods for data collection, organization, and analysis, making it difficult to fully utilize quality management data during the software development process. Furthermore, the relationships between data are often overlooked, making it difficult to quickly locate and fix problems when they arise.

[0006] Furthermore, in terms of test management, existing technologies often rely on manual writing of test cases, and test plans lack scientific rigor and systematicity, resulting in low testing efficiency and insufficient test coverage. In addition, the maintenance and management of test cases also face numerous difficulties.

[0007] Finally, in terms of quality assessment, existing technologies often rely on manual, experience-based evaluation methods, lacking objective and comprehensive quality assessment models and methods. This makes software quality assessment results often subjective and uncertain, making them difficult to use as a basis for decision-making. Summary of the Invention

[0008] The purpose of this invention is to propose an integrated software quality management method and system. This technical solution can efficiently and comprehensively realize quality management in the software development process, enable rapid tracing and location of quality problems, and provide objective and comprehensive quality assessment results, thus providing strong support for decision-making in the software development process.

[0009] To achieve the above objectives, in a first aspect, embodiments of this disclosure provide an integrated software quality management system, comprising:

[0010] The requirements management module is used to identify requirements and develop test plans based on those requirements.

[0011] The data processing module is used to collect quality management data during the software development process and to tag the quality management data, including defect type, priority, and repair status.

[0012] The relationship module is used to establish relationships between data.

[0013] The execution log module is used to record operations during the software development, testing, and repair process, and to generate execution logs.

[0014] The quality analysis module is used to build a quality assessment model that includes multiple quality elements and their weights; calculate the software quality score based on actual quality data; and determine the software quality level based on preset thresholds.

[0015] The test management module is used to generate and execute test cases according to requirements and obtain evaluation data;

[0016] The quality assessment module is used to integrate and analyze assessment data to conduct a comprehensive evaluation of software quality.

[0017] The beneficial effects of the basic solution are as follows: The requirements management module clarifies software development goals and enables the creation of test plans, ensuring the relevance and effectiveness of testing. The relationship module establishes connections between data, allowing for close integration of various stages in the software development process and improving team collaboration efficiency.

[0018] The data processing module collects and tags quality management data, providing a rich information foundation for quality analysis. Detailed tag classifications (such as defect type, priority, and repair status) help accurately pinpoint problems and optimize resource allocation. The quality analysis module uses this data to build a quality assessment model, calculates software quality scores based on actual quality data, and determines the quality level, providing a scientific basis for decision-making.

[0019] The test management module generates and executes test cases based on requirements, ensuring comprehensive verification of software functionality. A combination of automated and manual testing effectively uncovers potential defects. The quality assessment module integrates and analyzes assessment data, focusing not only on fixing individual defects but also on evaluating the overall software quality. This helps identify systemic issues and improves the overall stability and reliability of the software.

[0020] The execution log module records in detail the operations during the software development, testing, and repair process, generating execution logs that provide traceable evidence for subsequent auditing and improvement. Through continuous quality monitoring and evaluation, bottlenecks and deficiencies in the process can be identified in a timely manner, driving process optimization and improving development efficiency.

[0021] This system utilizes a quality assessment model within its quality analysis module to periodically evaluate software quality and adjust quality strategies based on the assessment results, achieving continuous improvement. Simultaneously, through data accumulation and analysis, it can identify trends and patterns in quality issues, providing early warnings and preventative measures for software development.

[0022] As a feasible preferred solution, the data processing module is used to achieve real-time data acquisition and updating using API interfaces or data crawling technology, and to achieve automated execution of custom rules and automatic labeling using a rule engine.

[0023] As a feasible and preferred solution, the association module establishes relationships between data through graph databases or relational databases, uses graph algorithms to analyze and mine the data relationships, and provides a visual traceability interface to display the context and related information of the problem.

[0024] As a feasible and preferred solution, the quality analysis module constructs a quality assessment model based on industry standards and internal experience, and regularly updates and optimizes the model based on newly collected data and feedback.

[0025] As a feasible and preferred solution, the test management module automatically executes test cases using the CI / CD pipeline and collects data during the testing process in real time; at the same time, it periodically performs statistical analysis on the test cases to identify high-risk test cases for focused testing.

[0026] As a feasible and preferred solution, the requirements management module integrates multiple requirements communication methods, including video conferencing, email, and online collaboration platforms; the requirements management module is also used to automatically classify and prioritize requirements when formulating test plans.

[0027] As a feasible and preferred solution, the requirements management module uses natural language processing technology to identify and parse the requirements mentioned in the communication, and trains a custom NER model based on existing labeled data, including examples of various functional points, performance indicators and compatibility requirements.

[0028] As a feasible and preferred option, the requirement management module is also used to parse sentence structure, determine the dependency relationships between words, and analyze the contextual relationships of functional requirements and performance indicators, as well as the dependencies between requirements, through dependency syntax analysis.

[0029] As a feasible and preferred solution, the demand management module is also used to construct or adopt an existing sentiment dictionary to determine the sentiment polarity of user feedback and perform fine-grained emotion analysis.

[0030] User feedback is scored based on emotional intensity, and the urgency and importance of the needs are comprehensively assessed in conjunction with the frequency of their occurrence. Positive weights are then generated to adjust the priority ranking of the needs. At the same time, different positive weights are assigned to needs that are related based on the degree of their interdependence.

[0031] Secondly, this disclosure also provides a software quality integrated management method, which utilizes the aforementioned software quality integrated management system. Attached Figure Description

[0032] Figure 1 This is a schematic diagram of the architecture of an integrated software quality management system.

[0033] Figure 2 This is a schematic diagram of the structure of an electronic device according to an embodiment of the present invention. Detailed Implementation

[0034] To make the technical solution and advantages of this application clearer, the technical solution of the present invention will be further described in detail below with reference to the accompanying drawings. It is understood that the specific embodiments described herein are only some embodiments of the present invention, and are only used to explain this application, not to limit it. It should be noted that the technical features or combinations of technical features described in the following embodiments should not be considered isolated; they can be combined with each other to achieve better technical effects. The same reference numerals appearing in the accompanying drawings of the following embodiments represent the same features or components, and can be applied to different embodiments.

[0035] Furthermore, unless otherwise defined, the technical or scientific terms used in this invention description shall have the ordinary meaning understood by one of ordinary skill in the art to which this invention pertains.

[0036] The present invention will now be described in further detail with reference to the accompanying drawings:

[0037] Reference numerals: Electronic device 500, processor 501, communication interface 502, memory 503.

[0038] Example 1

[0039] Reference Figure 1 A software quality integrated management system includes a requirements management module, a data processing module, a relationship module, an execution record module, a quality analysis module, a test management module, an execution analysis module, and a quality assessment module.

[0040] The requirements management module includes a target submodule, an archiving submodule, and a planning submodule.

[0041] The target submodule is used to define the software's functional requirements (such as user interface design and business logic processing), performance requirements (such as response time and load capacity), and compatibility requirements. The target submodule integrates various communication methods for requirements, including video conferencing, email, and online collaboration platforms.

[0042] The archiving submodule is used to organize the results of requirements communication into a structured requirements specification document, including detailed information such as functional requirements, performance requirements, and compatibility requirements. A version control system (such as Git) is used to manage the version of the requirements specification document to ensure that each requirement is clear, traceable, and testable.

[0043] The planning submodule, based on the requirements specification, formulates testing strategies, including test types (unit testing, integration testing, system testing), test methods (such as black-box testing, white-box testing, etc.), and test tools. It automatically categorizes and prioritizes requirements, uses project management tools to develop test plans, and clarifies detailed information such as test phases, test resources, test environment, test tools, and test milestones.

[0044] The data processing module includes an acquisition submodule and a tag submodule.

[0045] The Acquisition submodule is used to automatically collect quality management data from project management tools, code repositories, continuous integration / continuous deployment (CI / CD) platforms, etc., during the software development process. This includes, but is not limited to, code commit records, defect reports, test coverage, etc. It uses API interfaces or data crawling technology to achieve real-time acquisition and updating of data.

[0046] The tagging submodule is used to label the collected data using custom rules or machine learning algorithms, including defect type (such as functional defect, performance defect), priority (high, medium, low), repair status (to be repaired, repaired), etc., to facilitate subsequent analysis. It uses the rule engine to realize the automated execution of custom rules and automatic labeling.

[0047] The association module, based on data tags, establishes relationships between data through graph databases or relational databases, such as the association between defects and code files, and the association between test cases and requirements, to enable rapid tracing of quality issues. It uses graph algorithms to analyze and mine data relationships, enabling rapid tracing of quality issues, facilitating developers to quickly locate and fix problems, and providing a visual tracing interface that displays the context and related information of the problem.

[0048] The execution log module is used to automatically record every step of the software development, testing, and repair process using scripts or API interfaces, generating detailed execution logs including operation time, operator, and operation content, ensuring the transparency and traceability of the process.

[0049] The quality analysis module includes a model building submodule and a rating submodule.

[0050] The model building submodule, based on industry standards and internal experience, constructs a quality assessment model that includes multiple quality elements (such as code quality, test coverage, and user satisfaction) and their weights. It uses a data processing library to quantify and calculate the quality elements and determine their weights. The model is regularly updated and optimized based on newly collected data and feedback, enabling real-time updates and adaptive behavior.

[0051] Based on industry standards and internal experience, quantitative standards are set for each quality element. A data processing library is used to clean, transform, and calculate the collected data. The weight of each quality element is determined through expert scoring, questionnaires, and historical data analysis; the total weight should be 1 or 100.

[0052] The rating submodule is used to input actual quality data into the model, automatically calculate the software quality score through the algorithm, and determine the software quality level according to the preset threshold: excellent (above 90 points), good (80-89 points), average (70-79 points), and poor (below 70 points).

[0053] The test management module includes a simulation submodule and a cycle submodule.

[0054] The simulation submodule is used to generate test cases simulating user behavior based on the requirements information in the requirements document, using automated testing tools (such as Selenium and JMeter). It utilizes script recording functionality to automate the generation and execution of test cases, obtaining evaluation data. Quality elements are identified, including code quality (such as lines of code, comment ratio, code duplication rate, code complexity, etc.), test coverage (such as unit test coverage, integration test coverage, system test coverage, etc.), user satisfaction (such as data collected through questionnaires, user feedback, etc.), and other quality elements such as performance, security, and maintainability.

[0055] The lifecycle submodule is used to establish a database of test cases through project management tools, enabling the tracking and management of the entire lifecycle of test cases, including design, review, execution, updating, and maintenance. It predicts the probability of defect occurrence, optimizes the allocation and prioritization of test cases, performs statistical analysis on test cases, and identifies high-risk test cases for focused testing.

[0056] The execution analysis module includes an execution submodule and an analysis submodule.

[0057] The execution submodule utilizes containerization technology to build a test environment consistent with the production environment, improving the reliability of test results. It uses CI / CD pipelines to automatically execute test cases, collect data in real time during the test process, such as test time, test results, error logs, etc., and generate test reports.

[0058] The analysis submodule is used to combine test results with requirements documents to analyze the implementation status, performance, and compatibility between functions, compare test results with expected results, and identify potential defects.

[0059] The quality assessment module includes a comprehensive assessment submodule and a report generation submodule.

[0060] The evaluation submodule is used to integrate and analyze evaluation data using a data processing library, and to comprehensively evaluate the software quality by combining factors such as test results, user feedback, and historical quality data.

[0061] The reporting submodule is used to automatically generate quality reports that include quality scores, a list of major defects, and improvement suggestions, and provides a visual presentation.

[0062] Example 2

[0063] The key technical difference between this embodiment and the previous embodiments lies in that the target sub-module of the requirements management module is further used to identify and parse the requirements mentioned in the communication through Natural Language Processing (NLP) technology, and to organize and summarize them to assist in setting target requirements. Named Entity Recognition (NER) is a task of NLP, through which key information such as functional points, performance indicators, and compatibility requirements can be identified.

[0064] The target submodule trains a custom NER model based on existing labeled data, including examples of various functional points, performance indicators and compatibility requirements. The results obtained from the NER model are used to form structured requirement information by removing duplicate entities and merging similar entities.

[0065] The target submodule can identify specific functionalities, such as "users should be able to log in to the system" and "the system should support file uploads." Once confirmed, these identified functionalities will be directly converted into test items in subsequent test cases. The target submodule can also identify performance-related descriptions, such as "response time must be within 2 seconds" and "the system should be able to handle 1000 concurrent users." Once confirmed, these identified performance metrics will serve as the basis for performance testing in subsequent test cases. The target submodule can directly identify compatibility-related descriptions, such as "supports iOS and Android platforms" and "compatible with IE11 and above browsers." Once confirmed, these compatibility requirements will guide the execution of test cases in different testing environments.

[0066] The target submodule will also parse sentence structure, determine the dependency relationships between words, and use dependency parsing to help understand the contextual relationships between functional requirements and performance indicators, as well as the dependencies between requirements. The target submodule first performs preprocessing on the requirement document or identified text, such as word segmentation and stop word removal, to improve the accuracy of the analysis. Then, it extracts the required dependency relationship information by writing parsing code, and the analysis results are represented in a tree structure.

[0067] The target submodule can identify the subject-verb-object structure of functional requirements, thus enabling a more accurate understanding of the specific content of the requirements. For example, in "Users should be able to log in to the system," "users" is the subject, "should be able to log in" is the verb, and "system" is the object. By analyzing these dependencies, the requirement can be understood more clearly. The target submodule can identify the relationship between performance metrics and functional requirements. For example, in "Response time must be within 2 seconds," "response time" is the subject, and "must be within 2 seconds" is the condition. By analyzing these dependencies, the constraint of performance metrics on functional requirements can be understood. The target submodule can identify the dependencies between requirements. For example, in "After a file upload is successful, the system should send a notification," "successful file upload" is a precondition for "sending a notification." By analyzing these dependencies, the logical order and dependencies between requirements can be understood.

[0068] Based on the above technical features, the target submodule can extract key requirement information and analyze and understand the dependencies between requirements.

[0069] Example 3

[0070] The technical feature that distinguishes this embodiment from the above embodiments is that the target submodule is also used to construct or adopt an existing sentiment dictionary to judge the sentiment polarity (positive, negative, neutral) of user feedback, as well as to perform fine-grained emotion analysis (such as joy, anger, sadness, etc.).

[0071] The target submodule will perform sentiment analysis on the words used in user voice communication or feedback, score the emotional intensity of user feedback, and comprehensively assess the urgency and importance of the need based on the frequency of its occurrence. It will then generate positive weights to adjust the priority ranking of these needs. Furthermore, based on the dependencies between needs, related needs will also receive positive weights according to the degree of their association. Specifically, needs more closely related to the user feedback need, as shown in the dependency tree structure, will receive more positive weights, while more distantly related needs will receive less. The priority ranking of needs will also affect the priority ranking of subsequent test cases.

[0072] The target submodule predicts potential future demand hotspots based on the changing trends of demand priorities, helping to grasp market trends. Existing technologies generally plan the software's direction directly based on the number of user-submitted demands. This application overcomes this inertia by predicting based on the changing trends of demand priorities. Even if the total number of demands is still small, if their priority weight increases significantly within a certain period, they can be identified, such as the urgent needs of some minority groups. This allows the planning submodule to proactively plan subsequent actions. Furthermore, by incorporating sentiment analysis, different weights can be assigned to consumer feedback, making demand priority analysis not limited to the quantity of demands.

[0073] Example 4

[0074] The key difference between this embodiment and the previous embodiments lies in that the requirement management module further performs detailed analysis on each requirement, identifying its prerequisites (i.e., other requirements that must be met before the requirement can be implemented). If a prerequisite is not met, the process continues tracing upwards until an implemented prerequisite is found or the requirement is identified as the top-level requirement. The hierarchical relationship between each requirement and its prerequisites is recorded, forming a requirement hierarchy diagram.

[0075] Based on the requirement hierarchy diagram, calculate the depth of each requirement up to the top-level requirement (or the implemented prerequisite requirement). The depth of the hierarchy reflects the position of the requirement in the requirement chain and the number of prerequisites that need to be met to realize that requirement.

[0076] By utilizing software usage data and user behavior logs, the frequency of use for each implemented prerequisite requirement is statistically analyzed. Usage frequency reflects the activity and importance of the requirement in actual use.

[0077] Calculate the importance score of the current requirement based on the usage frequency of previously implemented requirements and their hierarchical relationship with the current requirement. Then, perform a weighted sum based on the usage frequency of the previous requirements according to the hierarchical depth.

[0078] For each requirement, a technical assessment is conducted, including the required technical resources, development time, and potential risks. Based on the assessment results, each requirement is assigned an implementation difficulty level (e.g., low, medium, high). The implementation difficulty level is then converted into a specific score (e.g., low = 1, medium = 3, high = 5). The implementation difficulty score is adjusted appropriately according to the depth of the hierarchy to reflect the cumulative difficulty in the requirement chain.

[0079] A comprehensive score is calculated for each requirement by combining importance and implementation difficulty scores. The comprehensive score is obtained by weighted summation, where the weights can be adjusted based on factors such as organizational strategy and resource availability.

[0080] Demands are ranked based on their overall scores, with higher-scoring demands having higher priority. The ranking results should be updated regularly to reflect changes in demand, technological advancements, and resource allocation.

[0081] By following the above methods, we can obtain a more objective assessment of urgency and importance, without being affected by the frequency of user feedback. This avoids situations where niche needs are mistakenly considered important needs due to the high frequency of user feedback.

[0082] This disclosure also provides an integrated software quality management method, which utilizes the aforementioned integrated software quality management system.

[0083] Those skilled in the art will understand that all or part of the processes in the integrated software quality management method can be implemented by a computer program instructing related hardware. The program can be stored in a non-volatile computer-readable storage medium. When executed, the program can include the processes of various embodiments of the integrated software quality management method. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), RAMbus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0084] This application also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, it implements the steps of the aforementioned integrated software quality management method. In this application embodiment, the processor is the control center of the computer system; it can be a physical machine processor or a virtual machine processor.

[0085] Reference Figure 2 The electronic device 500 includes at least one processor 501, at least one communication interface 502, at least one memory 503, and at least one bus 504. The bus 504 is used for communication between these components, the communication interface 502 is used for signaling or data communication with other node devices, and the memory 503 stores machine-readable instructions executable by the processor 501. When the electronic device 500 is running, the processor 501 communicates with the memory 503 via the bus 504, and when the machine-readable instructions are invoked by the processor 501, the steps of the integrated software quality management method described above are executed.

[0086] The above content is merely an embodiment of the present invention. Commonly known structures and characteristics of the solutions are not described in detail here. Those skilled in the art are aware of all common technical knowledge in the field prior to the application date or priority date, are aware of all existing technologies in that field, and have the ability to apply conventional experimental methods prior to that date. Those skilled in the art can improve and implement this solution based on the guidance provided in this application and their own capabilities. Some typical known structures or methods should not be obstacles for those skilled in the art to implement this application. It should be noted that those skilled in the art can make several modifications and improvements without departing from the structure of the present invention. These should also be considered within the scope of protection of the present invention, and will not affect the effectiveness of the implementation of the present invention or the practicality of the patent. The scope of protection claimed in this application should be determined by the content of its claims, and the specific embodiments described in the specification can be used to interpret the content of the claims.

Claims

1. A software quality integrated management system, characterized in that: include: The requirements management module is used to identify requirements and develop test plans based on those requirements. The requirements management module uses natural language processing technology to identify and parse the requirements mentioned in the communication, and trains a custom NER model based on existing labeled data, including examples of various functional points, performance indicators and compatibility requirements. The requirement management module is also used to parse sentence structure, determine the dependency relationship between words, and analyze the contextual relationship between functional requirements and performance indicators, as well as the dependency relationship between requirements, through dependency syntax analysis. The demand management module is also used to build or adopt existing sentiment dictionaries to judge the sentiment polarity of user feedback and perform fine-grained emotion analysis. User feedback is scored based on emotional intensity, and the urgency and importance of the needs are comprehensively assessed in combination with the frequency of the needs. Positive weights are generated to adjust the priority ranking of the needs, and different positive weights are assigned to related needs based on the degree of their interdependence. The requirements management module is also used to perform detailed analysis on each requirement and identify its predecessor requirements. If a predecessor requirement has not been implemented, it continues to trace upwards until an implemented predecessor requirement is found or the requirement is identified as the top-level requirement. The module records the hierarchical relationship between each requirement and its predecessor requirements to form a requirement hierarchy diagram. Based on the demand hierarchy diagram, calculate the depth of each demand up to the top-level demand; the depth of the hierarchy reflects the position of the demand in the demand chain and the number of prerequisites that need to be met to realize the demand. Utilize software usage data, user behavior logs, etc., to statistically analyze the usage frequency of each fulfilled prerequisite requirement; Frequency of use reflects the activity and importance of demand in actual use; Calculate the importance score of the current requirement based on the frequency of use of the previously implemented requirements and their hierarchical relationship with the current requirement; The usage frequency of the preceding requirements is weighted and summed according to the hierarchy depth. For each requirement, a technical assessment is conducted, and based on the assessment results, an implementation difficulty level is assigned to each requirement; the implementation difficulty level is converted into a specific score; the implementation difficulty score is adjusted appropriately according to the depth of the hierarchy to reflect the cumulative difficulty in the requirement chain; A comprehensive score is calculated for each requirement by combining importance and implementation difficulty scores; the comprehensive score is obtained by weighted summation. The requirements are ranked according to their overall scores, with higher-scoring requirements having higher priority. The ranking results should be updated regularly. The data processing module is used to collect quality management data during the software development process and to tag the quality management data, including defect type, priority, and repair status. The relationship module is used to establish relationships between data. The execution log module is used to record operations during the software development, testing, and repair process, and to generate execution logs. The quality analysis module is used to build a quality assessment model that includes multiple quality elements and their weights; calculate the software quality score based on actual quality data; and determine the software quality level based on preset thresholds. The test management module is used to generate and execute test cases according to requirements and obtain evaluation data; The quality assessment module is used to integrate and analyze assessment data to conduct a comprehensive evaluation of software quality.

2. The integrated software quality management system according to claim 1, characterized in that: The data processing module is used to acquire and update data in real time using API interfaces or data crawling technology, and to use a rule engine to automate the execution of custom rules and the automatic labeling of tags.

3. The integrated software quality management system according to claim 1, characterized in that: The relationship module establishes relationships between data through graph databases or relational databases, uses graph algorithms to analyze and mine these relationships, and provides a visual traceability interface to display the context and related information of the problem.

4. The integrated software quality management system according to claim 1, characterized in that: The quality analysis module builds a quality assessment model based on industry standards and internal experience, and regularly updates and optimizes the model based on newly collected data and feedback.

5. The integrated software quality management system according to claim 1, characterized in that: The test management module uses the CI / CD pipeline to automatically execute test cases and collect data in real time during the testing process; at the same time, it periodically performs statistical analysis on the test cases to identify high-risk test cases for focused testing.

6. The integrated software quality management system according to claim 1, characterized in that: The requirements management module integrates various communication methods, including video conferencing, email, and online collaboration platforms; when formulating test plans, the requirements management module is also used to automatically classify and prioritize requirements.

7. A software quality integrated management method, characterized in that, The software quality integrated management system described in any one of claims 1-6 is used.

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