Self-adaptive test method and device based on instant messaging tool, medium and product

Abstract

The embodiment of the invention discloses a self-adaptive testing method and device based on an instant messaging tool, a medium and a product. The method comprises the following steps: acquiring input information of a tester in an instant messaging tool, and verifying the input information; if verification is passed, the input information is sent to an artificial intelligence platform for keyword analysis, and a keyword set and a keyword set type are obtained; determining a target test resource based on the keyword set and the keyword set type; and the target test resource executes a test task based on the keyword set, and feeds back a test result to the instant messaging tool. According to the method, the intellectualization of the test process can be realized, and the test threshold is reduced, so that the test personnel can participate in the test work more easily.

Description

Technical Field

[0001] The present disclosure relates to the field of software testing technology, and in particular to an adaptive testing method, device, medium, and product based on instant messaging tools. Background Art

[0002] During software development and testing, regression testing and interface monitoring are crucial steps in ensuring software quality and stability. However, performing regression testing or triggering interface monitoring often requires manually executing test scripts or setting up scheduled tasks. This manual operation is not only time-consuming and labor-intensive, but also prone to errors, reducing testing efficiency.

[0003] Furthermore, each business line has its own independent efficiency tools or scripts, often developed and maintained by specific teams. When new members join or when collaborating across teams, testers are unfamiliar with each other's business lines and efficiency tools, leading to unfamiliarity with test data generation scripts. This lack of familiarity not only increases the learning curve but also makes test data generation and usage time-consuming and inefficient, severely impacting overall testing efficiency. Summary of the Invention

[0004] In view of this, the embodiments of the present disclosure provide an adaptive testing method, device, medium and product based on instant messaging tools, which can realize the intelligence of the testing process, lower the threshold of testing, and enable testers to participate in testing work more easily.

[0005] In a first aspect, the present disclosure provides an adaptive testing method based on an instant messaging tool, which adopts the following technical solutions: Obtaining the input information of the tester in the instant messaging tool and verifying the input information; If the verification is passed, the input information is sent to the artificial intelligence platform for keyword analysis to obtain the keyword set and keyword set type; determining target test resources based on the keyword set and the keyword set type; The target test resource performs a test task based on the keyword set and feeds back the test result to the instant messaging tool.

[0006] Optionally, obtaining the input information of the tester in the instant messaging tool and verifying the input information includes: In response to the tester's input operation in the instant messaging tool, obtaining input information and recording session metadata generated by the input operation; Matching the input information with words in a preset list; If the input information contains any word in the preset list, performing an integrity check on the session metadata; If the session metadata does not lack necessary features, determining that the verification of the input information passes; If the session metadata lacks necessary features, it is determined that the verification of the input information has failed.

[0007] Optionally, sending the input information to an artificial intelligence platform for keyword parsing to obtain a keyword set and a keyword set type includes: Build multiple keyword extraction rules based on preset test object types; Convert each keyword extraction rule into a rule flow chart and send it to the artificial intelligence platform; The artificial intelligence platform extracts keywords from the received input information according to the rule flow chart; If the extraction is successful according to any of the rule flow charts, a keyword set is obtained, and the type of the keyword set is determined to be the test object type of the rule flow chart.

[0008] Optionally, determining target test resources based on the keyword set and the keyword set type includes: If the keyword set type is UI test or interface test, then based on the keyword set, determine the target test resource from multiple preset test scripts; If the keyword set type is tool-type testing, target test resources are determined from a plurality of preset test tools based on the keyword set.

[0009] Optionally, the adaptive testing method based on instant messaging tools further includes: When the input information is verified, the session metadata is stored in a database, and a unique code of the session metadata is set in the database; When the input information is sent to the artificial intelligence platform, the unique code is also sent to the artificial intelligence platform.

[0010] Optionally, after determining the target test resource from a plurality of preset test tools based on the keyword set, the method further includes: Obtaining a set of necessary parameters for the target test resource; Based on the necessary parameter set, performing a necessary parameter check on the keyword set; If necessary parameters are missing from the keyword set, the missing parameters are counted and fed back to the instant messaging tool based on the unique code, triggering the instant messaging tool to provide a reminder for supplementary information; In response to the tester's data supplement operation in the instant messaging tool, obtain supplementary information and record the current conversation ID; Based on the current session ID, the keyword set and the supplementary information are combined into a new keyword set, and necessary parameters are checked on the new keyword set.

[0011] Optionally, the counting of missing parameters and feeding back the missing parameters to an instant messaging tool based on the unique code to trigger the instant messaging tool to provide an information supplement reminder include: Based on the unique code, querying target session metadata from the database; Sending the target session metadata and the missing parameters to an instant messaging tool; The instant messaging tool sends an information supplement reminder based on the target session metadata and the missing parameters.

[0012] In a second aspect, the present disclosure also provides an adaptive testing system based on an instant messaging tool, which adopts the following technical solutions: The verification module is used to obtain the input information of the tester in the instant messaging tool and verify the input information; if the verification passes, the parsing module is executed; A parsing module, configured to send the input information to an artificial intelligence platform for keyword parsing to obtain a keyword set and keyword set type; a determination module, configured to determine a target test resource based on the keyword set and the keyword set type; A feedback module is used for the target test resource to perform a test task based on the keyword set and to feed back the test result to the instant messaging tool.

[0013] In a third aspect, the embodiments of the present disclosure further provide a computer device that adopts the following technical solution: The computer device comprises: at least one processor; and, a memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor. The instructions are executed by the at least one processor to enable the at least one processor to execute any of the above-mentioned adaptive testing methods based on instant messaging tools.

[0014] In a fourth aspect, an embodiment of the present disclosure further provides a computer-readable storage medium, which stores computer instructions, and the computer instructions are used to enable a computer to execute any of the above-mentioned adaptive testing methods based on instant messaging tools.

[0015] In a fifth aspect, an embodiment of the present disclosure further provides a computer program product, comprising a computer program / instruction, which implements the steps of any of the above methods when executed by a processor.

[0016] The adaptive testing method based on instant messaging tools provided in the embodiments of the present disclosure allows testers to input information through instant messaging tools without having to specifically open the test system interface. Testers can initiate tests at any time within their daily instant messaging apps (such as DingTalk and WeChat), greatly improving the convenience of testing. Verifying the input information ensures that it meets the requirements of subsequent tests, preventing test failures or erroneous results caused by incorrect input, thereby improving the accuracy and reliability of the test. After the input information passes verification, keyword parsing is performed using the artificial intelligence platform's natural language processing capabilities. This not only automatically extracts keywords from the input information, constructs keyword sets, and determines keyword set types, but also simplifies the operational process, reducing the burden on testers to learn and use complex tools. Based on keyword sets and keyword set types, target test resources relevant to the test requirements can be accurately selected from a wide range of test resources. This precise matching ensures that the most appropriate test resources are used to execute the test tasks, improving the relevance and effectiveness of the test. When the test requirements change, the target test resources only need to be redefined based on the new keyword sets and keyword set types, eliminating the need for complex manual configuration. This method can quickly adapt to changing test requirements, improving response speed and flexibility. Test results can be directly fed back to instant messaging tools, allowing testers to obtain test results immediately. This real-time feedback mechanism enables testers to understand the test status in a timely manner, and testers do not need to switch between multiple systems or interfaces, which facilitates testers' management and analysis of test results and improves work efficiency.

[0017] The above description is only an overview of the technical solution of the present disclosure. In order to more clearly understand the technical means of the present disclosure, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present disclosure more obvious and easy to understand, the following specifically cites preferred embodiments and describes them in detail with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the technical solutions of the embodiments of the present disclosure, the following briefly introduces the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments of the present disclosure. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0019] Figure 1 A flowchart of an adaptive testing method based on instant messaging tools provided in an embodiment of the present disclosure; Figure 2 A flow chart of a method for verifying input information provided in an embodiment of the present disclosure; Figure 3 A flow chart of a method for verifying input information provided in an embodiment of the present disclosure; Figure 4 A flowchart of a method for checking necessary parameters of a keyword set provided by an embodiment of the present disclosure; Figure 5 A flowchart of the information supplement method provided in an embodiment of the present disclosure; Figure 6 A flowchart of a test method based on word driving provided in an embodiment of the present disclosure; Figure 7 A block diagram of the principle of an adaptive testing system based on instant messaging tools provided in an embodiment of the present disclosure; Figure 8 A schematic diagram of the structure of a computer device provided in an embodiment of the present disclosure. DETAILED DESCRIPTION

[0020] The embodiments of the present disclosure are described in detail below with reference to the accompanying drawings.

[0021] It should be clear that the following embodiments of the present disclosure are described through specific concrete examples, and those skilled in the art can easily understand other advantages and effects of the present disclosure from the contents disclosed in this specification. Obviously, the described embodiments are only a part of the embodiments of the present disclosure, rather than all the embodiments. The present disclosure can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed in various ways based on different viewpoints and applications without departing from the spirit of the present disclosure. It should be noted that the following embodiments and features in the embodiments can be combined with each other in the absence of conflict. Based on the embodiments in the present disclosure, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present disclosure.

[0022] It should be noted that various aspects of the embodiments within the scope of the appended claims are described below. It should be apparent that the aspects described herein can be embodied in a wide variety of forms, and any specific structure and / or function described herein is merely illustrative. Based on this disclosure, it should be understood by those skilled in the art that an aspect described herein can be implemented independently of any other aspect, and two or more of these aspects can be combined in various ways. For example, any number of aspects described herein can be used to implement the device and / or practice the method. In addition, other structures and / or functionalities other than one or more of the aspects described herein can be used to implement this device and / or practice this method.

[0023] It should also be noted that the illustrations provided in the following embodiments are only schematic illustrations of the basic concept of the present disclosure. The illustrations only show components related to the present disclosure and are not drawn according to the number, shape and size of components in actual implementation. In actual implementation, the type, quantity and proportion of each component can be changed at will, and the component layout type may also be more complicated.

[0024] Additionally, in the following description, specific details are provided to provide a thorough understanding of the examples. However, one skilled in the art will appreciate that the aspects described can be practiced without these specific details.

[0025] Reference Figure 1 The present disclosure provides an adaptive testing method based on an instant messaging tool, comprising the following steps: S1: Obtain the tester's input information in the instant messaging tool and verify the input information; if the verification passes, execute S2; if the verification fails, execute S3; S2: Send the input information to the artificial intelligence platform for keyword analysis to obtain the keyword set and keyword set type; S3: Feedback verification failure reminder via instant messaging tool; S4: Determine target test resources based on keyword sets and keyword set types; S5: The target test resource performs the test task based on the keyword set and feeds back the test results to the instant messaging tool.

[0026] The adaptive testing method based on instant messaging tools provided in this disclosure allows testers to input information through instant messaging tools without having to open the test system interface. Testers can initiate tests at any time within their daily instant messaging software (such as DingTalk and WeChat), greatly improving testing convenience. Verifying input information ensures that it meets the requirements of subsequent tests, preventing test failures or erroneous results caused by incorrect input, thereby improving test accuracy and reliability.

[0027] After the input information is verified, the artificial intelligence platform's own natural language processing capabilities are used to perform keyword analysis. This can not only automatically extract keywords from the input information, form a keyword set and determine the keyword set type, but also simplify the operation process and reduce the burden on testers to learn and use complex tools.

[0028] Based on keyword sets and keyword set types, you can accurately filter out target test resources relevant to test requirements from a wide range of test resources. This precise matching ensures that the most appropriate test resources are used to execute test tasks, improving the relevance and effectiveness of tests. When test requirements change, you only need to redefine target test resources based on the new keyword sets and keyword set types, without the need for complex manual configuration. This method can quickly adapt to changing test requirements, improving response speed and flexibility.

[0029] Test results can be directly fed back to instant messaging tools, allowing testers to obtain test results immediately. This real-time feedback mechanism enables testers to understand the test status in a timely manner, and testers do not need to switch between multiple systems or interfaces, which facilitates testers' management and analysis of test results and improves work efficiency.

[0030] In summary, this method realizes the intelligence of the testing process, lowers the threshold of testing, and enables testers to participate in testing work more easily.

[0031] In S1, refer to Figure 2 The flow chart of the input information verification method shown in the figure, "obtaining the input information of the tester in the instant messaging tool and verifying the input information" includes the following steps: S11: In response to the tester's input operation in the instant messaging tool, obtain input information and record session metadata generated by the input operation; S12: Match the input information with the words in the preset list; if the input information contains any word in the preset list, execute S13; if the input information does not contain any word in the preset list, execute S15; S13: Perform integrity check on the session metadata; if the session metadata does not lack necessary features, execute S14; if the session metadata lacks necessary features, execute S15; S14: Determine whether the verification of the input information is successful; S15: Determine that the verification of the input information fails.

[0032] Based on the above solution, when the tester performs input operations in the instant messaging tool, the chatbot in the instant messaging tool automatically records the conversation metadata generated by the input operations. Under normal circumstances, the conversation metadata should include the conversation ID, user ID, and conversation type. The conversation ID is a specific code or string that uniquely identifies each conversation. The user ID is a unique tag used to identify each user in the instant messaging tool. The conversation type is a classification of different communication scenarios and methods in the instant messaging tool, such as one-on-one chat and group chat.

[0033] Build a callback service and set the callback interface of the service. The instant messaging tool sends the tester's input information to the callback service through the callback interface. The chatbot sends the session metadata generated by the tester's input operation to the callback service through the callback interface.

[0034] Based on the preset test object types, a preset list is constructed, which stores the vocabulary required for each test object. For example, the preset test object types include UI testing, interface testing, and utility testing. If the tester needs to perform UI testing, their input information needs to include vocabulary such as button and menu. If the tester needs to perform interface testing, their input information needs to include vocabulary such as request and response. If the tester needs to perform utility testing, their input information needs to include vocabulary such as JUnit.

[0035] The preset list is stored in the callback service. Upon receiving the input and conversation metadata, the callback service performs appropriate validation. If the input contains any word from the preset list, it indicates that the input is the tester's test requirement data. If the input does not contain any of the words in the preset list, it indicates that the input is the tester's daily conversation data and requires no processing. This method allows for rapid determination of whether the tester has a test requirement, facilitating the timely processing of subsequent test requirements.

[0036] If it is determined through detecting the input information that the tester has a test requirement in this input operation, the integrity check of the session metadata generated by the input operation is performed. For example, it is detected whether the session metadata contains the conversation ID, user ID and conversation type and the corresponding values. If they are all included, it means that the session metadata is not missing the necessary features, and the subsequent test tasks can continue to be executed. It is determined that the verification of the input information has passed, and the callback service sends the input information to the artificial intelligence platform; if it is detected that the session metadata is missing any one of the conversation ID, user ID and conversation type, it means that the session metadata is missing the necessary features. Accordingly, the subsequent test tasks cannot continue, it is determined that the verification of the input information has failed, and a verification failure reminder is fed back to the tester through the instant messaging tool.

[0037] In S2, to facilitate subsequent feedback on test progress to auditors, when the input information passes verification, the session metadata is stored in the database, and a unique code for the session metadata is set in the database. When the input information is sent to the AI ​​platform, the unique code is also sent to the AI ​​platform. That is, the input information and the unique code are sent together, and the AI ​​platform automatically establishes an association between the two. This method can record the session metadata that auditors need to test. Even if multiple auditors are testing simultaneously, by storing and managing a large amount of session metadata, using the unique code as the identifier for each record, it is easy to query and determine to which auditor to feedback the test progress and results. For example, feedback to the tester that the connection to the AI ​​platform has been successful can be provided.

[0038] When the artificial intelligence platform receives input information, it will automatically analyze it and refer to Figure 3 The flowchart for keyword parsing shown in the figure shows that "sending input information to the AI ​​platform for keyword parsing and obtaining keyword sets and keyword set types" includes the following steps: S21: Based on the preset test object type, build multiple keyword extraction rules; S22: Convert each keyword extraction rule into a rule flow chart and send it to the artificial intelligence platform; S23: The artificial intelligence platform extracts keywords from the received input information according to the rule flow chart; S24: If the extraction is successful according to any rule flowchart, a keyword set is obtained, and the keyword set type is determined to be a test object type of the rule flowchart.

[0039] In S21, during software testing, in order to accurately and efficiently extract keywords from the tester's input, a variety of targeted keyword extraction rules are constructed based on different preset test object types. These test object types include UI testing, interface testing, and tool testing. Based on the rules corresponding to these types, not only can the keyword set be obtained when the extraction is successful, but the test object type to which these keyword sets belong can also be clearly identified. In addition, the rules for different test object types will lead to different subsequent operations after achieving their goals.

[0040] When building keyword extraction rules for UI testing, the focus is on content related to interface elements, layout features, visual effects, and user operations. For example, various controls on the interface, such as buttons, text boxes, and drop-down menus, are important components of user interaction with the interface, and their names and properties are often key information; interface layout features, such as alignment and spacing, affect the overall aesthetics and usability of the interface; visual elements, such as color, font, and icons, provide an intuitive visual experience for users; and user operations on the interface, such as clicking, sliding, and typing, reflect the user's interaction with the interface.

[0041] When building keyword extraction rules for interface testing, we focus on the interface's relevant attributes and operations. For example, the interface's name, URL, request method (such as GET, POST, PUT, etc.), request parameters, response status code, and response data format are basic attributes of the interface and are crucial for accurately describing and calling the interface. We also focus on interface performance metrics, such as response time and throughput, as well as security-related information, such as authentication methods and data encryption.

[0042] When building keyword extraction rules for tool-based testing, we focus on the tool's functional features, usage scenarios, and performance. For example, we'll include the tool's name, version number, supported test types (such as functional testing and performance testing), tool operation steps, and tool configuration parameters. This information helps testers fully understand the tool's usage and scope of application. We also focus on the tool's effectiveness and efficiency during actual use, such as test execution time and resource usage.

[0043] In S22, each keyword extraction rule is converted into a rule flowchart by manually creating a rule flowchart or using the Business Process Modeling Notation (BPMN) technology. The nodes in the rule flowchart represent the key steps in the rule execution process, such as input information, condition judgment, keyword extraction, test execution, data creation, etc. The edges represent the execution sequence between the key steps, so that the rule flowchart can clearly display the complete execution logic of the keyword extraction rule.

[0044] Each rule flowchart is sent to the artificial intelligence platform by dragging and dropping the mouse, selecting and uploading files, or calling the interface, and the artificial intelligence platform stores these rule flowcharts.

[0045] In S23 and S24, after receiving the input information, the AI ​​platform performs keyword extraction based on the stored rule flow charts. This process can be performed by matching each rule flow chart sequentially or by working in parallel with multiple rule flow charts simultaneously. When processing the input information, once keyword extraction is successfully completed according to any rule flow chart, not only can the corresponding keyword set be accurately obtained, but the type of these keyword sets can also be clearly identified based on the test object type corresponding to the rule flow chart.

[0046] Some AI platforms may not support the parallel use of multiple rule flow charts. To improve keyword parsing efficiency, statistics are collected at preset intervals on the usage of historical keyword set types. The most frequently used keyword set types are analyzed and sorted from high to low by usage rate. This sorted order is then sent to the AI ​​platform. After receiving input information, the AI ​​platform uses the rule flow charts sequentially to extract keywords from the input information based on this sorted order.

[0047] In S4, if the keyword set type is UI test or interface test, it means that the auditor's requirement is to execute the test case by calling the test script. At this time, based on the keyword set, the target test resources can be determined from multiple preset test scripts. This is because the keyword set contains parameters such as task nouns, business types, and test case ids. Through the task nouns, the back-end interface can be called to start the test script on the corresponding server. The test script executes the corresponding test case according to the business type and test case id to obtain a test report.

[0048] Based on the above, if the keyword set type is UI testing or interface testing, for the artificial intelligence platform, it will call the task startup interface based on the keyword to transmit different task parameters. The corresponding test script will call the corresponding automation program according to the parameters to execute the corresponding test case.

[0049] If the keyword set type is tool testing, it means that the auditor's requirement is to produce test data that meets the testing requirements. In this case, based on the keyword set, the target test resource can be determined from multiple preset test tools. This is because the artificial intelligence platform will conduct detailed research and organization of all preset test tools, clarifying each test tool's functions, applicable scenarios, and supported business types. By matching this information with the keyword set, the most suitable test tool is selected as the target test resource. In addition, if the keyword set itself contains the name of the required test tool, then the test tool will be determined as the target test resource.

[0050] Each test tool may have different parameters for producing test data. Therefore, in order to ensure the smooth production of test data, it is necessary to check the necessary parameters of the keyword set after determining the target test resources. Figure 4 The flowchart of the method for checking the necessary parameters of the keyword set is shown, which includes the following steps: S41: Obtain necessary parameter sets of target test resources; S42: Based on the necessary parameter set, perform necessary parameter check on the keyword set; if the necessary parameters are missing in the keyword set, execute S43; if the necessary parameters are not missing in the keyword set, execute S46; S43: Count the missing parameters, and based on the unique code, feed back the missing parameters to the instant messaging tool, triggering the instant messaging tool to provide a reminder for supplementary information; S44: In response to the tester's data supplement operation in the instant messaging tool, obtain supplementary information and record the current conversation ID; S45: Based on the current conversation ID, the keyword set and the supplementary information are combined into a new keyword set, and the process returns to step S42 to perform necessary parameter checks on the new keyword set. S46: Based on the keyword set, an interface request is sent to the target test resource.

[0051] In S41, the necessary parameter sets of each test tool are sent to the artificial intelligence platform by dragging the mouse, selecting and uploading files, or calling the interface. The artificial intelligence platform stores these necessary parameter sets. This operation can be performed simultaneously with the operation of sending the rule flow chart to the artificial intelligence platform.

[0052] In S42-S46, the keyword set is matched with each required parameter in the required parameter set. If the keyword set contains all the required parameters in the required parameter set, it means that the keyword set contains the values ​​corresponding to these required parameters. At this time, the interface address of the target test resource is extracted from the preset knowledge base. The interface address is concatenated with each required parameter and its corresponding value according to a preset format (e.g., a concatenation format that follows HTTP request rules) to form a complete request URL. Based on this complete request URL, an interface request is sent to the target test resource, thereby invoking the interface of the corresponding function.

[0053] If the keyword set does not cover all the necessary parameters in the necessary parameter set, it means that some necessary parameter values ​​are missing. In this case, the artificial intelligence platform needs to feedback the missing parameters to the tester. In order to facilitate feedback, the artificial intelligence platform can use instant messaging tools to complete it. Figure 5The flowchart of the information supplementation method shown, "Counting missing parameters, feeding back the missing parameters to the instant messaging tool based on a unique code, and triggering the instant messaging tool to prompt for information supplementation," includes the following steps: S431: Query target session metadata from the database based on the unique code; S432: Send the target session metadata and missing parameters to the instant messaging tool; S433: The instant messaging tool sends a supplementary reminder based on the target session metadata and the missing parameters.

[0054] Based on the above, the AI ​​platform sends the missing parameters and the corresponding unique code to the callback service. The callback service uses the unique code to query the target session metadata from multiple session metadata in the database. The callback service then sends the target session metadata, the missing parameters, and the unique code to the instant messaging tool. The instant messaging tool accurately locates the corresponding tester based on the target session metadata and clarifies the communication scenario with the tester, whether it is a one-on-one chat window or a group chat interface with multiple participants. The instant messaging tool then pushes the missing parameters to the tester in a clear and easy-to-understand dialogue format. For example, it sends a message in the chat box similar to "This test task is missing the following required parameters: [specific missing parameter list], please provide relevant information to continue the subsequent process," thereby reminding the tester to supplement the information.

[0055] When a tester receives a reminder to supplement information in an instant messaging tool, they perform the supplementary data operation within the tool. The current conversation ID corresponding to this supplementary data operation is automatically recorded and sent along with the current conversation ID and unique code to the callback service. Upon receiving this information, the callback service updates the corresponding session metadata in the database based on the unique code and sends the unique code, keyword set, and current conversation ID to the backend. Upon receiving the information, the backend extracts the supplementary information corresponding to the current conversation ID from the instant messaging tool, combines it with the original keyword set to create a new keyword set, and stores it. The new keyword set and unique code are then sent to the AI ​​platform, which performs another parameter check on the new keyword set. If any necessary parameters are still missing, the tester is sent another supplementary information reminder via the instant messaging tool. After the tester supplements the data again, the backend combines the new supplementary information with the previously stored keyword set and stores the new keyword set instead of the original one. This process repeats until the AI ​​platform passes the necessary parameter check.

[0056] This process establishes a closed-loop data supplementation and verification mechanism to ensure the completeness of the keyword set parameters required for testing. Instant messaging tools facilitate data supplementation for testers, and each step collaborates through unique codes and conversation IDs to ensure accurate data transmission and updates. Through multiple data combinations and checks, the keyword set is continuously refined until the necessary parameters are met, ensuring the smooth progress of subsequent testing processes.

[0057] In S5, if the target test resource is a test script for UI testing, the backend will automatically call the test script and generate a corresponding test report to comprehensively evaluate the interactivity, aesthetics, and usability of the software user interface, providing a strong basis for interface optimization and improvement. If the target test resource is a test script for interface testing, the backend will still automatically call the test script to carry out testing, thereby ensuring that the interface functions, performance, security, etc. between different modules in the software system meet the expected requirements, helping testers to promptly discover problems with the interface and ensure the stable operation of the interface. If the target test resource is a test tool for tool-type testing, the target test resource will respond to the interface request and produce test data that meets the test requirements based on the necessary parameters in the request, providing necessary data support for software testing.

[0058] Reference Figure 6 This diagram illustrates a flow chart for a context-driven testing approach. Instant messaging is integrated on the client side, while callback services, the backend, and various test resources are integrated on the server side. Using this illustrated approach, testers simply send a single message via instant messaging, clearly stating the desired action and the conditions. The input includes target data, required parameters, and their corresponding values. This allows testers to specify a test script or test tool. Alternatively, the AI ​​platform can automatically select test scripts or test tools that meet their needs and use them as target test resources. The backend then automatically calls the target test resource's interface to execute the test. This approach combines efficiency-enhancing tools from various business lines with currently popular AI capabilities to create a context-driven efficiency tool. This significantly reduces the learning curve for testers and effectively improves overall testing efficiency, lowering regression testing costs and allowing testers to focus on the requirements themselves. Furthermore, upon successful invocation of the target test resource, a unique code provides detailed feedback to the tester, including information about the test script or test tool successfully invoked and the estimated time to complete the remaining steps, allowing testers to fully and promptly monitor the test progress. The final test results can be fed back to the tester through a unique code, or the test results can be fed back to a designated location based on actual needs. For example, the tester can communicate and collaborate with other team members in a group chat, which facilitates discussion and analysis of the test results within the team and promotes collaboration and communication between teams.

[0059] Reference Figure 7 The present disclosure provides an adaptive testing system based on an instant messaging tool, comprising: The verification module 101 is used to obtain the input information of the tester in the instant messaging tool and verify the input information; if the verification passes, the parsing module is executed; Parsing module 102, used to send input information to the artificial intelligence platform for keyword parsing, and obtain keyword sets and keyword set types; A determination module 103, configured to determine target test resources based on the keyword set and the keyword set type; The feedback module 104 is used for the target test resource to perform the test task based on the keyword set and feed back the test result to the instant messaging tool.

[0060] The various variations and specific examples of the adaptive testing method based on instant messaging tools provided above are also applicable to the adaptive testing system based on instant messaging tools provided in the present disclosure. Through the above detailed description of the adaptive testing method based on instant messaging tools, those skilled in the art can clearly understand the implementation method of the adaptive testing system based on instant messaging tools. For the sake of brevity of the specification, it will not be described in detail here.

[0061] A computer device according to an embodiment of the present disclosure includes a memory and a processor. The memory is used to store non-transitory computer-readable instructions. Specifically, the memory may include one or more computer program products, which may include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. The volatile memory may include, for example, random access memory (RAM) and / or cache memory. The non-volatile memory may include, for example, read-only memory (ROM), a hard disk, flash memory, etc.

[0062] The processor can be a central processing unit (CPU) or other form of processing unit with data processing capabilities and / or instruction execution capabilities, and can control other components in the computer device to perform desired functions. In one embodiment of the present disclosure, the processor is used to execute the computer-readable instructions stored in the memory, causing the computer device to perform all or part of the steps of the adaptive testing method based on instant messaging tools described in various embodiments of the present disclosure.

[0063] Those skilled in the art should understand that in order to solve the technical problem of how to obtain a good user experience, this embodiment may also include well-known structures such as a communication bus and an interface, and these well-known structures should also be included in the scope of protection of this disclosure.

[0064] like Figure 8The present invention provides a schematic diagram of the structure of a computer device according to an embodiment of the present invention. Figure 8 The computer device shown is only an example and should not limit the functions and scope of use of the embodiments of the present disclosure.

[0065] like Figure 8 As shown, a computer device may include a processor (e.g., a central processing unit, a graphics processing unit, etc.), which can perform various appropriate actions and processes based on programs stored in a read-only memory (ROM) or programs loaded from a storage device into a random access memory (RAM). The RAM also stores various programs and data required for the operation of the computer device. The processor, ROM, and RAM are connected to each other via a bus. An input / output (I / O) interface is also connected to the bus.

[0066] Typically, the following devices can be connected to the I / O interface: input devices such as sensors or visual information acquisition devices; output devices such as display screens; storage devices such as tapes and hard disks; and communication devices. The communication device can allow the computer device to communicate with other devices (such as edge computing devices) wirelessly or by wire to exchange data. Figure 8 A computer device having various devices is shown, but it should be understood that it is not required to implement or possess all of the devices shown. More or fewer devices may be implemented or possessed instead.

[0067] In particular, according to an embodiment of the present disclosure, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present disclosure includes a computer program product, which includes a computer program carried on a non-transitory computer-readable medium, and the computer program includes a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network via a communication device, or installed from a storage device, or installed from a ROM. When the computer program is executed by a processor, all or part of the steps of the adaptive testing method based on an instant messaging tool of the embodiment of the present disclosure are executed.

[0068] For detailed description of this embodiment, please refer to the corresponding description in the aforementioned embodiments, which will not be repeated here.

[0069] According to an embodiment of the present disclosure, a computer-readable storage medium stores non-transitory computer-readable instructions. When the non-transitory computer-readable instructions are executed by a processor, all or part of the steps of the adaptive testing method based on instant messaging tools described in the embodiments of the present disclosure are executed.

[0070] The above-mentioned computer-readable storage media include, but are not limited to, optical storage media (e.g., CD-ROMs and DVDs), magneto-optical storage media (e.g., MOs), magnetic storage media (e.g., magnetic tapes or mobile hard disks), media with built-in rewritable non-volatile memory (e.g., memory cards), and media with built-in ROM (e.g., ROM cartridges).

[0071] For detailed description of this embodiment, please refer to the corresponding description in the aforementioned embodiments, which will not be repeated here.

[0072] The basic principles of the present disclosure have been described above in conjunction with specific embodiments. However, it should be noted that the advantages, strengths, and effects mentioned in this disclosure are merely illustrative and not restrictive, and should not be construed as necessarily possessed by each embodiment of the present disclosure. Furthermore, the specific details disclosed above are provided for illustrative purposes and to facilitate understanding, rather than as limitations. These details do not limit the present disclosure to necessarily being implemented using these specific details.

[0073] In the present disclosure, relational terms such as first and second, etc. are merely used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply that there is any such actual relationship or order between these entities or operations. The block diagrams of the devices, devices, equipment, and systems involved in the present disclosure are merely illustrative examples and are not intended to require or imply that they must be connected, arranged, or configured in the manner shown in the block diagrams. As will be appreciated by those skilled in the art, these devices, devices, equipment, and systems can be connected, arranged, or configured in any manner. Words such as "including," "comprising," "having," and the like are open-ended words, meaning "including but not limited to," and can be used interchangeably therewith. The words "or" and "and" used herein refer to the words "and / or" and can be used interchangeably therewith, unless the context clearly indicates otherwise. The word "such as" used herein refers to the phrase "such as but not limited to," and can be used interchangeably therewith.

[0074] Additionally, as used herein, "or" used in a list of items beginning with "at least one" indicates a separate list, so that, for example, a list of "at least one of A, B, or C" means A or B or C, or AB or AC or BC, or ABC (i.e., A and B and C). Furthermore, the word "exemplary" does not mean that the example described is preferred or better than other examples.

[0075] It should also be noted that in the system and method of the present disclosure, each component or each step can be decomposed and / or recombined. Such decomposition and / or recombination should be regarded as equivalent solutions of the present disclosure.

[0076] Various changes, substitutions, and modifications may be made to the technology described herein without departing from the teachings defined by the appended claims. Moreover, the scope of the claims of this disclosure is not limited to the specific aspects of the processes, machines, manufactures, compositions of things, means, methods, and actions described above. Currently existing or later developed processes, machines, manufactures, compositions of things, means, methods, or actions that perform substantially the same function or achieve substantially the same results as the corresponding aspects described herein may be utilized. Accordingly, the appended claims include within their scope such processes, machines, manufactures, compositions of things, means, methods, or actions.

[0077] The above description of the disclosed aspects is provided to enable any person skilled in the art to make or use the present disclosure. Various modifications to these aspects will be readily apparent to those skilled in the art, and the general principles defined herein may be applied to other aspects without departing from the scope of the present disclosure. Therefore, the present disclosure is not intended to be limited to the aspects shown herein, but rather to be accorded the widest scope consistent with the principles and novel features disclosed herein.

[0078] The above description has been provided for the purpose of illustration and description. In addition, this description is not intended to limit the embodiments of the present disclosure to the forms disclosed herein. Although a number of example aspects and embodiments have been discussed above, those skilled in the art will recognize certain variations, modifications, alterations, additions, and sub-combinations thereof.

Claims

1. An adaptive testing method based on instant messaging tools, characterized in that: include: Obtaining the input information of the tester in the instant messaging tool and verifying the input information; If the verification is passed, the input information is sent to the artificial intelligence platform for keyword analysis to obtain the keyword set and keyword set type; determining target test resources based on the keyword set and the keyword set type; The target test resource performs a test task based on the keyword set and feeds back the test result to the instant messaging tool.

2. The adaptive testing method based on instant messaging tools according to claim 1, characterized in that: The obtaining of the input information of the tester in the instant messaging tool and verifying the input information includes: In response to the tester's input operation in the instant messaging tool, obtaining input information and recording session metadata generated by the input operation; Matching the input information with words in a preset list; If the input information contains any word in the preset list, performing an integrity check on the session metadata; If the session metadata does not lack necessary features, determining that the verification of the input information passes; If the session metadata lacks necessary features, it is determined that the verification of the input information has failed.

3. The adaptive testing method based on instant messaging tools according to claim 1, characterized in that: The step of sending the input information to the artificial intelligence platform for keyword analysis to obtain a keyword set and keyword set type includes: Build multiple keyword extraction rules based on preset test object types; Convert each keyword extraction rule into a rule flow chart and send it to the artificial intelligence platform; The artificial intelligence platform extracts keywords from the received input information according to the rule flow chart; If the extraction is successful according to any of the rule flow charts, a keyword set is obtained, and the type of the keyword set is determined to be the test object type of the rule flow chart.

4. The adaptive testing method based on instant messaging tools according to claim 2, characterized in that: The determining of target test resources based on the keyword set and the keyword set type includes: If the keyword set type is UI test or interface test, then based on the keyword set, determine the target test resource from multiple preset test scripts; If the keyword set type is tool-type testing, target test resources are determined from a plurality of preset test tools based on the keyword set.

5. The adaptive testing method based on instant messaging tools according to claim 4, characterized in that: Also includes: When the input information is verified, the session metadata is stored in a database, and a unique code of the session metadata is set in the database; When the input information is sent to the artificial intelligence platform, the unique code is also sent to the artificial intelligence platform.

6. The adaptive testing method based on instant messaging tools according to claim 5, characterized in that: After determining target test resources from a plurality of preset test tools based on the keyword set, the method further includes: Obtaining a set of necessary parameters for the target test resource; Based on the necessary parameter set, performing a necessary parameter check on the keyword set; If necessary parameters are missing from the keyword set, the missing parameters are counted and fed back to the instant messaging tool based on the unique code, triggering the instant messaging tool to provide additional information reminders; In response to the tester's data supplement operation in the instant messaging tool, obtain supplementary information and record the current conversation ID; Based on the current session ID, the keyword set and the supplementary information are combined into a new keyword set, and necessary parameters are checked on the new keyword set.

7. The adaptive testing method based on instant messaging tools according to claim 6, characterized in that: The counting of missing parameters, based on the unique code, feeding back the missing parameters to the instant messaging tool, triggering the instant messaging tool to provide an information supplement reminder, includes: Based on the unique code, querying target session metadata from the database; Sending the target session metadata and the missing parameters to an instant messaging tool; The instant messaging tool sends an information supplement reminder based on the target session metadata and the missing parameters.

8. A computer device, characterized in that: The computer device comprises: at least one processor; and, a memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the adaptive testing method based on instant messaging tools according to any one of claims 1 to 7.

9. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a computer to execute the adaptive testing method based on instant messaging tools according to any one of claims 1 to 7.

10. A computer program product comprising computer instructions, characterized in that When the computer instructions are executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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