A method, apparatus, device, medium, and product for application testing.

Abstract

This invention provides a method, apparatus, device, medium, and product for application testing. The method includes: establishing a specified user model for a specified user; when the application enters the specified user mode, invoking the specified user model to simulate the user's operational behavior to test the application; acquiring behavioral data of the operational behavior and evaluating the behavioral data; and generating test results for the specified user mode based on the evaluation results. This invention enables application testing by establishing user models for specified users, such as the elderly, and simulating their operational behavior, thereby improving the accuracy and stability of application testing.

Description

Technical Field

[0001] This invention relates to the field of application testing technology, and in particular to a method, apparatus, device, medium, and product for application testing. Background Technology

[0002] In today's information age, smart devices and various application software (APPs) have been deeply integrated into people's daily lives, greatly improving the convenience of life and the accessibility of information.

[0003] Despite the wide variety of apps on the market with diverse functions, most apps are designed primarily for young users. Their interface design, operation flow, and interaction methods are often more in line with the usage habits of young people. This can lead to various inconveniences for specific users such as the elderly when using these apps, such as small fonts making it difficult to read, complex interface layouts making it difficult to quickly locate the required functions, and cumbersome operation processes that are prone to errors. Summary of the Invention

[0004] In view of the above problems, a method, apparatus, device, medium, and product for application testing are proposed to overcome or at least partially solve the above problems, including:

[0005] A method for testing an application, the method comprising:

[0006] Establish a specified user model for a specified user;

[0007] When the application enters the specified user mode for the specified user, the specified user model is invoked to simulate the operation behavior of the specified user in order to test the application;

[0008] Acquire behavioral data of the operation and evaluate the behavioral data;

[0009] Based on the evaluation results, test results are generated for the specified user mode.

[0010] Optionally, it also includes:

[0011] Obtain the constraints associated with the specified user;

[0012] Check whether the application meets the constraints;

[0013] Based on the test results, test results are generated for the specified user mode.

[0014] Optionally, the constraints include constraints on visual elements in the application, and generating test results for the specified user mode based on the detection results includes:

[0015] When a visual element in the application does not meet the constraints of the visual element, a test result is generated indicating that the visual element in the specified user mode is abnormal.

[0016] Optionally, the operational behavior includes operational behavior on controllable elements in the application, and the evaluation of the behavioral data includes:

[0017] Based on the behavioral data, determine the operation result on the controllable elements in the application;

[0018] Based on the operation results, determine the probability value of erroneous operation on the controllable element;

[0019] The error operation probability value is compared with the preset probability value to obtain the evaluation result.

[0020] Optionally, generating test results for the specified user mode based on the evaluation results includes:

[0021] When the probability value of the erroneous operation is greater than a preset probability value, a test result indicating that the controllable element in the specified user mode is abnormal is generated.

[0022] Optionally, establishing a specified user model for a specified user includes:

[0023] Retrieve historical user data for a specified user;

[0024] Based on the historical user data, establish a specific user model for the specified user.

[0025] Optionally, it also includes:

[0026] Based on the test results, an optimization scheme is generated for the specified user mode.

[0027] Optionally, the designated user is an elderly user.

[0028] An application testing apparatus, the apparatus comprising:

[0029] The specified user model creation module is used to create a specified user model for a specified user.

[0030] The simulated behavior testing module is used to simulate the operation behavior of the specified user when the application enters the specified user mode for the specified user, so as to test the application.

[0031] The behavior evaluation module is used to acquire behavior data of the operation and evaluate the behavior data.

[0032] The first test result generation module is used to generate test results for the specified user mode based on the evaluation results.

[0033] An electronic device includes a processor, a memory, and a computer program stored in the memory and capable of running on the processor, wherein the computer program, when executed by the processor, implements the method described above.

[0034] A computer-readable storage medium on which a computer program is stored, which, when executed by a processor, implements the method described above.

[0035] A computer program product includes a computer program that, when executed by a processor, implements the method described above.

[0036] The embodiments of the present invention have the following advantages:

[0037] In this embodiment of the invention, a specified user model is established for a specified user; when the application enters the specified user mode for the specified user, the specified user model is invoked to simulate the operation behavior of the specified user in order to test the application; behavioral data of the operation behavior is obtained and evaluated; and test results for the specified user mode are generated based on the evaluation results. This realizes the testing of the application by establishing a user model for specified users such as the elderly and simulating their operation behavior, thereby improving the accuracy and stability of application testing. Attached Figure Description

[0038] To more clearly illustrate the technical solution of the present invention, the accompanying drawings used in the description of the present invention will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0039] Figure 1 This is a flowchart of the steps of an application testing method provided in some embodiments of the present invention;

[0040] Figure 2 This is a flowchart illustrating an application testing method provided in some embodiments of the present invention;

[0041] Figure 3 This is a flowchart of the steps of another application testing method provided in some embodiments of the present invention;

[0042] Figure 4 This is a flowchart of the steps of another application testing method provided in some embodiments of the present invention;

[0043] Figure 5 This is a structural block diagram of an application testing apparatus provided in some embodiments of the present invention. Detailed Implementation

[0044] To make the above-mentioned objects, features, and advantages of the present invention more apparent and understandable, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without inventive effort are within the scope of protection of the present invention.

[0045] In related technologies, application testing can be divided into two types: the first is automated application testing, which can only verify the correctness and consistency of page elements in the application and cannot test for the specific needs of a specific user; the second is manual experience testing, which requires a lot of human resources to conduct specific experience testing for the needs of different groups of people, which will lead to the inability to quickly verify that the app meets the age-friendliness requirements and iterate to a new version during the app iteration process.

[0046] Therefore, in this embodiment of the invention, an application testing method for a specific user (such as an elderly user) is proposed. Based on a well-established AI (Artificial Intelligence) workflow, the user model of the application is continuously improved by collecting real experience data of the specified user to simulate the behavior of the specified user. By combining the application with the specified user pattern to design an interaction draft, a user experience evaluation algorithm is completed, and the page elements are identified and evaluated to determine whether they meet the needs of the specified user.

[0047] In this embodiment of the invention, the above-described solution effectively improves the efficiency of age-friendly user experience testing. Furthermore, the test coverage and effectiveness provided by this solution are more accurate and stable than manual experience testing, thereby increasing user satisfaction and usage of the app and enhancing its market competitiveness.

[0048] The present invention will be further described below with reference to the accompanying drawings:

[0049] Reference Figure 1 The diagram illustrates a flowchart of the steps of an application testing method provided by some embodiments of the present invention, which may specifically include the following steps:

[0050] Step 101: Establish a specified user model for the specified user.

[0051] In some embodiments of the present invention, the designated user is an elderly user.

[0052] In some embodiments of the present invention, the step of establishing a specified user model for a specified user includes: obtaining historical user data of the specified user; and establishing a specified user model for the specified user based on the historical user data.

[0053] As examples, event tracking (event analysis) can be implemented in applications to obtain historical user data for specific users. This historical user data can include behavioral records specific to elderly users, such as purchase history, browsing history, search history, personal information (e.g., age, gender, location), and data such as page views, popularity, and trending searches.

[0054] Tracking analysis refers to a data collection method that involves attaching data collection code to the functional code of an application that needs to collect data in order to capture user behavior or events on the application.

[0055] Once enough historical user data has been collected, this data can be used to build a model for that specific user. This model is an abstract representation designed to summarize and reflect the characteristics, preferences, and behavioral patterns of the specified user.

[0056] As examples, when building a specific user model for a specific user, useful information and patterns can be extracted from the raw data (historical user data) through methods such as statistical analysis, machine learning, and data mining, and then integrated into a structured model.

[0057] In some examples, a dedicated age-friendly testing module can be added to the application's automated testing system. This module's specified user model will include common operations and preferences of elderly users, such as font size and control size, common feedback issues, and common errors. By continuously refining this model, automated testing tools can more accurately simulate the behavior of elderly users.

[0058] Step 102: When the application enters the specified user mode for the specified user, the specified user model is invoked to simulate the operation behavior of the specified user in order to test the application.

[0059] In practical applications, applications can be set up with specific user modes for designated users, such as an elderly mode. Users can control the application to enter the specified user mode by clicking a designated button in the interactive interface.

[0060] After the application enters the specified user mode, the system will call the specified user model that has been pre-built for that specified user. This specified user model can contain various information about the specified user's operation behavior, such as commonly used functions, click paths, input habits, etc.

[0061] When a specified user model is invoked, the system can automatically or through test scripts simulate the specified user's actions, such as automatically clicking buttons, entering text, browsing pages (scrolling pages), etc.

[0062] By simulating the actions of a specified user, various tests can be performed on the application, generating test results specific to the user's behavior.

[0063] Step 103: Obtain behavioral data of the operation and evaluate the behavioral data.

[0064] As examples, acquiring behavioral data related to the aforementioned operational behaviors refers to collecting or recording behavioral data generated when a specified user model simulates the operational behaviors of a specified user during application testing. This behavioral data may include, but is not limited to, clicks, swipes, inputs, selections, browsing paths, and dwell times simulated by the specified user model.

[0065] After acquiring behavioral data, this data can be evaluated to analyze its characteristics, patterns, trends, etc., thereby identifying areas for improvement in the application.

[0066] In some embodiments of the present invention, the operation behavior includes operation behavior on controllable elements in the application, and evaluating the behavior data includes: determining the operation result of the controllable elements in the application based on the behavior data; determining the erroneous operation probability value of the controllable elements based on the operation result; and comparing the erroneous operation probability value with a preset probability value to obtain an evaluation result.

[0067] In practical implementation, behavioral data of operational behaviors can be used to determine the specific operations performed by a specified user model on various manipulable elements (such as buttons, links, input boxes, etc.) in the application, as well as the results of these operations. For example, if a specified user model simulates a specified user clicking a button, this click behavior can be recorded, and the resulting behavior (such as page redirection, pop-up dialog box, data submission, etc.) can be determined.

[0068] After determining the operation results, it is possible to assess whether these operations are likely to constitute erroneous operations. For example, this can be determined by comparing the simulated operation results with the expected, correct operation results; if the user's operation does not match the expectation, it is considered an erroneous operation; then, based on the frequency or pattern of these erroneous operations, an erroneous operation probability value can be calculated, which is the probability that a given user will perform an erroneous operation.

[0069] After obtaining the probability value of erroneous operation, the calculated probability value of erroneous operation can be compared with a preset probability value.

[0070] As some examples, preset probability values ​​can be set according to the specific requirements of the application or industry standards, representing an acceptable threshold for erroneous operations; for example, the preset probability value can be 10%.

[0071] If the calculated probability of an error is higher than the preset probability, it indicates a problem with the design or implementation of the controllable element, or that the specified user is prone to making mistakes when using the element. Conversely, if the probability of an error is lower than the preset probability, it indicates that the element's design is reasonable, and the specified user is unlikely to make mistakes when using it.

[0072] By comparing the probability value of incorrect operation with the preset probability value, an evaluation result can be obtained for the controllable elements in the application, such as unreasonable button design.

[0073] As some examples, the probability value of erroneous operation can be the probability of misoperation or the probability of failure.

[0074] Step 104: Based on the evaluation results, generate test results for the specified user mode.

[0075] After obtaining the evaluation results, test results can be generated for a specific user mode (elderly user mode). The test results can indicate the performance of a specific user in a specific mode, such as whether there are any problems or defects, whether the expected goals are met, and other feedback.

[0076] By generating test results, developers, testers, or product managers can understand how the application performs in specific user scenarios and make improvements or optimizations accordingly.

[0077] In some embodiments of the present invention, generating test results for the specified user mode based on the evaluation results includes: generating test results indicating that the controllable elements in the specified user mode are abnormal when the probability value of the erroneous operation is greater than a preset probability value.

[0078] After comparing the erroneous operation probability value with a preset probability value, if the erroneous operation probability value exceeds the preset probability value, a test result can be generated to indicate an anomaly in the controllable elements of a specified user mode. This test result indicates that there is an anomaly in the controllable elements (such as buttons, links, input boxes, etc.) in the specified user mode. This anomaly indicates that the user has difficulty operating these elements correctly, or that these elements are prone to misoperation in the specified user mode.

[0079] In some embodiments of the present invention, the method further includes: obtaining constraints related to the specified user; detecting whether the application satisfies the constraints; and generating test results for the specified user mode based on the detection results.

[0080] As examples, constraints refer to the conditions used to evaluate visual elements in an application during testing. Constraints can be rules regarding the layout, size, color, font, and interactive behavior of visual elements. For instance, if an elderly person needs larger text, and the current 16px text is unsuitable, a constraint could be that the text can only be adjusted within the range of 16-50px.

[0081] In some examples, because it is necessary to develop user experience evaluation algorithms, developers can add a large number of constraints to the aging-in-place testing module. By combining the characteristics of the specified user model mentioned above with custom configurations and constraint inputs, the test parameters of the algorithm can be adjusted, such as multi-dimensional constraints like font size, control size, contrast, color, and control complexity.

[0082] Among them, the user experience evaluation algorithm refers to a business algorithm used to judge whether the function of a specified user mode is truly suitable for the specified user. For example, the elderly mode enlarges the size of button controls, enlarges the size of text, and increases color contrast. However, determining the appropriate button size, text size, and color contrast for the elderly, as well as whether button-type functions or slider-type functions are easier for the elderly to operate, requires continuous debugging and calculation to find the best effect.

[0083] The automated testing system obtains the constraints related to a specified user, detects whether the application meets the constraints, generates test results, and generates test results for the specified user mode based on the test results.

[0084] In some embodiments of the present invention, the constraints include constraints on visual elements in the application, and generating test results for the specified user mode based on the detection results includes: generating test results indicating that the visual elements in the specified user mode are abnormal when the visual elements in the application do not meet the constraints of the visual elements.

[0085] Here, "not meeting the constraints" refers to the discovery during testing that certain visual elements in the application do not comply with the specified constraints. For example, a button might be placed in the wrong location, or a text box might be larger than the range specified by the constraints.

[0086] When a visual element is detected as not meeting its constraints, the automated testing system can generate test results indicating anomalies in the visual elements within a specified user mode. These test results can identify which visual elements are problematic and which constraints they violate. The test results may also include a detailed description of the problem, screenshots, suggested fixes, or any information that helps developers understand and resolve the issue.

[0087] In some embodiments of the present invention, the method further includes: generating an optimization scheme for the specified user mode based on the test results.

[0088] The optimization plan may include adjusting the application's interface design, improving interaction logic, adding new features, or fixing existing problems, in order to improve the satisfaction of specific users with the application.

[0089] Developing optimization plans for specific user patterns based on test results helps ensure that optimization measures accurately address the issues identified in the tests, thereby improving user experience and system performance.

[0090] In this embodiment of the invention, a specified user model is established for a specified user; when the application enters the specified user mode for the specified user, the specified user model is invoked to simulate the operation behavior of the specified user in order to test the application; behavioral data of the operation behavior is obtained and evaluated; and test results for the specified user mode are generated based on the evaluation results. This realizes the testing of the application by establishing a user model for specified users such as the elderly and simulating their operation behavior, thereby improving the accuracy and stability of application testing.

[0091] The following is in conjunction with the appendix Figure 2 The present invention will be described by way of example:

[0092] Step 201: Research and collect user data.

[0093] Step 202, User data preprocessing (filtering high-quality and usable data, and removing junk and useless data).

[0094] Step 203: Data aggregation and model building.

[0095] By collecting and integrating feedback from designated users and analyzing embedded data within the application, a user model (elderly user model) is constructed using a large amount of real-world experience data. Then, an age-appropriate testing module is added to the automated testing system. This module's user model includes common operations and preferences of elderly users, such as font size and control size, as well as common feedback issues and errors. By continuously refining this model, the automated testing tools can more accurately simulate the behavior of elderly users.

[0096] Step 204, User Experience Evaluation Algorithm Design.

[0097] Step 205: Combine model data, custom configuration, and constraint input.

[0098] A user experience evaluation algorithm was developed, and numerous constraints were added to the aging-in-place testing module. By combining the characteristics of the specified user model and developing custom configurations and constraint inputs, the algorithm's test parameters were adjusted, including multi-dimensional constraints such as font size, control size, contrast, color, and control complexity.

[0099] For example, if an elderly person needs larger text, the existing 16px text is not suitable. The constraint can be that the text can only be adjusted within the range of 16-50px.

[0100] Step 206: Combine the generated test case scripts.

[0101] Step 207: Feedback on test results.

[0102] Step 208: Development, modification, and optimization.

[0103] Combining the aforementioned elderly user model and user experience evaluation algorithm, a test case script was designed to simulate the behavior of elderly users. This script can invoke the elderly user model to simulate the operating habits of elderly users, such as clicking buttons, entering text, and scrolling pages. By simulating the operations of elderly users, the script tests whether the app provides a good age-friendly experience in actual use.

[0104] For example, based on historical data of a specified user, it is found that elderly people over 60 years old spend more than five minutes on the air conditioner's timer page, and the timer button trigger rate is low, while the blank area has a high accidental touch rate. This accidental touch rate can be calculated and summarized, added to the specified user model data, and the configuration of the timer button can be read to obtain the button size. Repeated automated test experiments can be conducted on this model to verify how large the click area is needed to reduce the accidental touch rate without affecting other functions. If there are product specifications that prohibit the use of circular buttons, this constraint can be added before conducting the test.

[0105] For example, is the clickable area of ​​the verification button large enough for elderly users to click? Are the input boxes easy to type in, and is the contrast between the text and background colors clear enough? During testing, the number of clicks, operation time, and error rate generated by the execution of the test case script can also be collected. By analyzing this data, the age-friendliness of the APP can be evaluated, and areas for improvement can be identified. For example, if the test case script takes too long to execute on a certain page, or if multiple abnormal clicks occur, the layout and operation of that page need to be simplified.

[0106] Reference Figure 3 The diagram illustrates a flowchart of another application testing method provided by some embodiments of the present invention, which may specifically include the following steps:

[0107] Step 301: Obtain historical user data for the specified user.

[0108] In some embodiments of the present invention, the designated user is an elderly user.

[0109] As examples, event tracking (event analysis) can be implemented in applications to obtain historical user data for specific users. This historical user data can include behavioral records specific to elderly users, such as purchase history, browsing history, search history, personal information (e.g., age, gender, location), and data such as page views, popularity, and trending searches.

[0110] Tracking analysis refers to a data collection method that involves attaching data collection code to the functional code of an application that needs to collect data in order to capture user behavior or events on the application.

[0111] Step 302: Based on the historical user data, establish a specified user model for the specified user.

[0112] Once enough historical user data has been collected, this data can be used to build a model for that specific user. This model is an abstract representation designed to summarize and reflect the characteristics, preferences, and behavioral patterns of the specified user.

[0113] As examples, when building a specific user model for a specific user, useful information and patterns can be extracted from the raw data (historical user data) through methods such as statistical analysis, machine learning, and data mining, and then integrated into a structured model.

[0114] In some examples, a dedicated age-friendly testing module can be added to the application's automated testing system. This module's specified user model will include common operations and preferences of elderly users, such as font size and control size, common feedback issues, and common errors. By continuously refining this model, automated testing tools can more accurately simulate the behavior of elderly users.

[0115] Step 303: When the application enters the specified user mode for the specified user, the specified user model is invoked to simulate the operation behavior of the specified user in order to test the application.

[0116] In practical applications, applications can be set up with specific user modes for designated users, such as an elderly mode. Users can control the application to enter the specified user mode by clicking a designated button in the interactive interface.

[0117] After the application enters the specified user mode, the system will call the specified user model that has been pre-built for that specified user. This specified user model can contain various information about the specified user's operation behavior, such as commonly used functions, click paths, input habits, etc.

[0118] When a specified user model is invoked, the system can automatically or through test scripts simulate the specified user's actions, such as automatically clicking buttons, entering text, browsing pages (scrolling pages), etc.

[0119] By simulating the actions of a specified user, various tests can be performed on the application, generating test results specific to the user's behavior.

[0120] Step 304: Obtain behavioral data of the operation and evaluate the behavioral data.

[0121] As examples, acquiring behavioral data related to the aforementioned operational behaviors refers to collecting or recording behavioral data generated when a specified user model simulates the operational behaviors of a specified user during application testing. This behavioral data may include, but is not limited to, clicks, swipes, inputs, selections, browsing paths, and dwell times simulated by the specified user model.

[0122] After acquiring behavioral data, this data can be evaluated to analyze its characteristics, patterns, trends, etc., thereby identifying areas for improvement in the application.

[0123] In some embodiments of the present invention, the operation behavior includes operation behavior on controllable elements in the application, and evaluating the behavior data includes: determining the operation result of the controllable elements in the application based on the behavior data; determining the erroneous operation probability value of the controllable elements based on the operation result; and comparing the erroneous operation probability value with a preset probability value to obtain an evaluation result.

[0124] In practical implementation, behavioral data of operational behaviors can be used to determine the specific operations performed by a specified user model on various manipulable elements (such as buttons, links, input boxes, etc.) in the application, as well as the results of these operations. For example, if a specified user model simulates a specified user clicking a button, this click behavior can be recorded, and the resulting behavior (such as page redirection, pop-up dialog box, data submission, etc.) can be determined.

[0125] After determining the operation results, it is possible to assess whether these operations are likely to constitute erroneous operations. For example, this can be determined by comparing the simulated operation results with the expected, correct operation results; if the user's operation does not match the expectation, it is considered an erroneous operation; then, based on the frequency or pattern of these erroneous operations, an erroneous operation probability value can be calculated, which is the probability that a given user will perform an erroneous operation.

[0126] After obtaining the probability value of erroneous operation, the calculated probability value of erroneous operation can be compared with a preset probability value.

[0127] As some examples, preset probability values ​​can be set according to the specific requirements of the application or industry standards, representing an acceptable threshold for erroneous operations; for example, the preset probability value can be 10%.

[0128] If the calculated probability of an error is higher than the preset probability, it indicates a problem with the design or implementation of the controllable element, or that the specified user is prone to making mistakes when using the element. Conversely, if the probability of an error is lower than the preset probability, it indicates that the element's design is reasonable, and the specified user is unlikely to make mistakes when using it.

[0129] By comparing the probability value of incorrect operation with the preset probability value, an evaluation result can be obtained for the controllable elements in the application, such as unreasonable button design.

[0130] As some examples, the probability value of erroneous operation can be the probability of misoperation or the probability of failure.

[0131] Step 305: Based on the evaluation results, generate test results for the specified user mode.

[0132] After obtaining the evaluation results, test results can be generated for a specific user mode (elderly user mode). The test results can indicate the performance of a specific user in a specific mode, such as whether there are any problems or defects, whether the expected goals are met, and other feedback.

[0133] By generating test results, developers, testers, or product managers can understand how the application performs in specific user scenarios and make improvements or optimizations accordingly.

[0134] In some embodiments of the present invention, generating test results for the specified user mode based on the evaluation results includes: generating test results indicating that the controllable elements in the specified user mode are abnormal when the probability value of the erroneous operation is greater than a preset probability value.

[0135] After comparing the erroneous operation probability value with a preset probability value, if the erroneous operation probability value exceeds the preset probability value, a test result can be generated to indicate an anomaly in the controllable elements of a specified user mode. This test result indicates that there is an anomaly in the controllable elements (such as buttons, links, input boxes, etc.) in the specified user mode. This anomaly indicates that the user has difficulty operating these elements correctly, or that these elements are prone to misoperation in the specified user mode.

[0136] In some embodiments of the present invention, the method further includes: obtaining constraints related to the specified user; detecting whether the application satisfies the constraints; and generating test results for the specified user mode based on the detection results.

[0137] As examples, constraints refer to the conditions used to evaluate visual elements in an application during testing. Constraints can be rules regarding the layout, size, color, font, and interactive behavior of visual elements. For instance, if an elderly person needs larger text, and the current 16px text is unsuitable, a constraint could be that the text can only be adjusted within the range of 16-50px.

[0138] In some examples, because it is necessary to develop user experience evaluation algorithms, developers can add a large number of constraints to the aging-in-place testing module. By combining the characteristics of the specified user model mentioned above with custom configurations and constraint inputs, the test parameters of the algorithm can be adjusted, such as multi-dimensional constraints like font size, control size, contrast, color, and control complexity.

[0139] Among them, the user experience evaluation algorithm refers to a business algorithm used to judge whether the function of a specified user mode is truly suitable for the specified user. For example, the elderly mode enlarges the size of button controls, enlarges the size of text, and increases color contrast. However, determining the appropriate button size, text size, and color contrast for the elderly, as well as whether button-type functions or slider-type functions are easier for the elderly to operate, requires continuous debugging and calculation to find the best effect.

[0140] The automated testing system obtains the constraints related to a specified user, detects whether the application meets the constraints, generates test results, and generates test results for the specified user mode based on the test results.

[0141] In some embodiments of the present invention, the constraints include constraints on visual elements in the application, and generating test results for the specified user mode based on the detection results includes: generating test results indicating that the visual elements in the specified user mode are abnormal when the visual elements in the application do not meet the constraints of the visual elements.

[0142] Here, "not meeting the constraints" refers to the discovery during testing that certain visual elements in the application do not comply with the specified constraints. For example, a button might be placed in the wrong location, or a text box might be larger than the range specified by the constraints.

[0143] When a visual element is detected as not meeting its constraints, the automated testing system can generate test results indicating anomalies in the visual elements within a specified user mode. These test results can identify which visual elements are problematic and which constraints they violate. The test results may also include a detailed description of the problem, screenshots, suggested fixes, or any information that helps developers understand and resolve the issue.

[0144] In some embodiments of the present invention, the method further includes: generating an optimization scheme for the specified user mode based on the test results.

[0145] The optimization plan may include adjusting the application's interface design, improving interaction logic, adding new features, or fixing existing problems, in order to improve the satisfaction of specific users with the application.

[0146] Developing optimization plans for specific user patterns based on test results helps ensure that optimization measures accurately address the issues identified in the tests, thereby improving user experience and system performance.

[0147] In this embodiment of the invention, by acquiring historical user data of a specified user, a specified user model is established based on the historical user data; when the application enters the specified user mode, the specified user model is invoked to simulate the operation behavior of the specified user in order to test the application; behavioral data of the operation behavior is acquired and evaluated; and test results for the specified user mode are generated based on the evaluation results. This realizes the testing of the application by establishing user models for specified users such as the elderly and simulating their operation behavior, thereby improving the accuracy and stability of application testing.

[0148] Reference Figure 4 The diagram illustrates a flowchart of another application testing method provided by some embodiments of the present invention, which may specifically include the following steps:

[0149] Step 401: Establish a specified user model for the specified user.

[0150] In some embodiments of the present invention, the designated user is an elderly user.

[0151] In some embodiments of the present invention, the step of establishing a specified user model for a specified user includes: obtaining historical user data of the specified user; and establishing a specified user model for the specified user based on the historical user data.

[0152] As examples, event tracking (event analysis) can be implemented in applications to obtain historical user data for specific users. This historical user data can include behavioral records specific to elderly users, such as purchase history, browsing history, search history, personal information (e.g., age, gender, location), and data such as page views, popularity, and trending searches.

[0153] Tracking analysis refers to a data collection method that involves attaching data collection code to the functional code of an application that needs to collect data in order to capture user behavior or events on the application.

[0154] Once enough historical user data has been collected, this data can be used to build a model for that specific user. This model is an abstract representation designed to summarize and reflect the characteristics, preferences, and behavioral patterns of the specified user.

[0155] As examples, when building a specific user model for a specific user, useful information and patterns can be extracted from the raw data (historical user data) through methods such as statistical analysis, machine learning, and data mining, and then integrated into a structured model.

[0156] In some examples, a dedicated age-friendly testing module can be added to the application's automated testing system. This module's specified user model will include common operations and preferences of elderly users, such as font size and control size, common feedback issues, and common errors. By continuously refining this model, automated testing tools can more accurately simulate the behavior of elderly users.

[0157] Step 402: When the application enters the specified user mode for the specified user, the specified user model is invoked to simulate the operation behavior of the specified user in order to test the application.

[0158] In practical applications, applications can be set up with specific user modes for designated users, such as an elderly mode. Users can control the application to enter the specified user mode by clicking a designated button in the interactive interface.

[0159] After the application enters the specified user mode, the system will call the specified user model that has been pre-built for that specified user. This specified user model can contain various information about the specified user's operation behavior, such as commonly used functions, click paths, input habits, etc.

[0160] When a specified user model is invoked, the system can automatically or through test scripts simulate the specified user's actions, such as automatically clicking buttons, entering text, browsing pages (scrolling pages), etc.

[0161] By simulating the actions of a specified user, various tests can be performed on the application, generating test results specific to the user's behavior.

[0162] Step 403: Obtain behavioral data of the operation and evaluate the behavioral data.

[0163] As examples, acquiring behavioral data related to the aforementioned operational behaviors refers to collecting or recording behavioral data generated when a specified user model simulates the operational behaviors of a specified user during application testing. This behavioral data may include, but is not limited to, clicks, swipes, inputs, selections, browsing paths, and dwell times simulated by the specified user model.

[0164] After acquiring behavioral data, this data can be evaluated to analyze its characteristics, patterns, trends, etc., thereby identifying areas for improvement in the application.

[0165] In some embodiments of the present invention, the operation behavior includes operation behavior on controllable elements in the application, and evaluating the behavior data includes: determining the operation result of the controllable elements in the application based on the behavior data; determining the erroneous operation probability value of the controllable elements based on the operation result; and comparing the erroneous operation probability value with a preset probability value to obtain an evaluation result.

[0166] In practical implementation, behavioral data of operational behaviors can be used to determine the specific operations performed by a specified user model on various manipulable elements (such as buttons, links, input boxes, etc.) in the application, as well as the results of these operations. For example, if a specified user model simulates a specified user clicking a button, this click behavior can be recorded, and the resulting behavior (such as page redirection, pop-up dialog box, data submission, etc.) can be determined.

[0167] After determining the operation results, it is possible to assess whether these operations are likely to constitute erroneous operations. For example, this can be determined by comparing the simulated operation results with the expected, correct operation results; if the user's operation does not match the expectation, it is considered an erroneous operation; then, based on the frequency or pattern of these erroneous operations, an erroneous operation probability value can be calculated, which is the probability that a given user will perform an erroneous operation.

[0168] After obtaining the probability value of erroneous operation, the calculated probability value of erroneous operation can be compared with a preset probability value.

[0169] As some examples, preset probability values ​​can be set according to the specific requirements of the application or industry standards, representing an acceptable threshold for erroneous operations; for example, the preset probability value can be 10%.

[0170] If the calculated probability of an error is higher than the preset probability, it indicates a problem with the design or implementation of the controllable element, or that the specified user is prone to making mistakes when using the element. Conversely, if the probability of an error is lower than the preset probability, it indicates that the element's design is reasonable, and the specified user is unlikely to make mistakes when using it.

[0171] By comparing the probability value of incorrect operation with the preset probability value, an evaluation result can be obtained for the controllable elements in the application, such as unreasonable button design.

[0172] As some examples, the probability value of erroneous operation can be the probability of misoperation or the probability of failure.

[0173] Step 404: Based on the evaluation results, generate test results for the specified user mode.

[0174] After obtaining the evaluation results, test results can be generated for a specific user mode (elderly user mode). The test results can indicate the performance of a specific user in a specific mode, such as whether there are any problems or defects, whether the expected goals are met, and other feedback.

[0175] By generating test results, developers, testers, or product managers can understand how the application performs in specific user scenarios and make improvements or optimizations accordingly.

[0176] In some embodiments of the present invention, generating test results for the specified user mode based on the evaluation results includes: generating test results indicating that the controllable elements in the specified user mode are abnormal when the probability value of the erroneous operation is greater than a preset probability value.

[0177] After comparing the erroneous operation probability value with a preset probability value, if the erroneous operation probability value exceeds the preset probability value, a test result can be generated to indicate an anomaly in the controllable elements of a specified user mode. This test result indicates that there is an anomaly in the controllable elements (such as buttons, links, input boxes, etc.) in the specified user mode. This anomaly indicates that the user has difficulty operating these elements correctly, or that these elements are prone to misoperation in the specified user mode.

[0178] In some embodiments of the present invention, the method further includes: obtaining constraints related to the specified user; detecting whether the application satisfies the constraints; and generating test results for the specified user mode based on the detection results.

[0179] As examples, constraints refer to the conditions used to evaluate visual elements in an application during testing. Constraints can be rules regarding the layout, size, color, font, and interactive behavior of visual elements. For instance, if an elderly person needs larger text, and the current 16px text is unsuitable, a constraint could be that the text can only be adjusted within the range of 16-50px.

[0180] In some examples, because it is necessary to develop user experience evaluation algorithms, developers can add a large number of constraints to the aging-in-place testing module. By combining the characteristics of the specified user model mentioned above with custom configurations and constraint inputs, the test parameters of the algorithm can be adjusted, such as multi-dimensional constraints like font size, control size, contrast, color, and control complexity.

[0181] Among them, the user experience evaluation algorithm refers to a business algorithm used to judge whether the function of a specified user mode is truly suitable for the specified user. For example, the elderly mode enlarges the size of button controls, enlarges the size of text, and increases color contrast. However, determining the appropriate button size, text size, and color contrast for the elderly, as well as whether button-type functions or slider-type functions are easier for the elderly to operate, requires continuous debugging and calculation to find the best effect.

[0182] The automated testing system obtains the constraints related to a specified user, detects whether the application meets the constraints, generates test results, and generates test results for the specified user mode based on the test results.

[0183] In some embodiments of the present invention, the constraints include constraints on visual elements in the application, and generating test results for the specified user mode based on the detection results includes: generating test results indicating that the visual elements in the specified user mode are abnormal when the visual elements in the application do not meet the constraints of the visual elements.

[0184] Here, "not meeting the constraints" refers to the discovery during testing that certain visual elements in the application do not comply with the specified constraints. For example, a button might be placed in the wrong location, or a text box might be larger than the range specified by the constraints.

[0185] When a visual element is detected as not meeting its constraints, the automated testing system can generate test results indicating anomalies in the visual elements within a specified user mode. These test results can identify which visual elements are problematic and which constraints they violate. The test results may also include a detailed description of the problem, screenshots, suggested fixes, or any information that helps developers understand and resolve the issue.

[0186] Step 405: Based on the test results, generate an optimization scheme for the specified user mode.

[0187] The optimization plan may include adjusting the application's interface design, improving interaction logic, adding new features, or fixing existing problems, in order to improve the satisfaction of specific users with the application.

[0188] Developing optimization plans for specific user patterns based on test results helps ensure that optimization measures accurately address the issues identified in the tests, thereby improving user experience and system performance.

[0189] In this embodiment of the invention, a specified user model is established for a specified user; when the application enters the specified user mode, the specified user model is invoked to simulate the operation behavior of the specified user to test the application; behavioral data of the operation behavior is obtained and evaluated; based on the evaluation results, test results for the specified user mode are generated; based on the test results, an optimization scheme for the specified user mode is generated. This realizes the testing of the application by establishing a user model for specified users such as the elderly and simulating their operation behavior, thereby improving the accuracy and stability of application testing.

[0190] It should be noted that, for the sake of simplicity, the method embodiments are all described as a series of actions. However, those skilled in the art should understand that the embodiments of the present invention are not limited to the described order of actions, because according to the embodiments of the present invention, some steps can be performed in other orders or simultaneously. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are preferred embodiments, and the actions involved are not necessarily essential to the embodiments of the present invention.

[0191] Reference Figure 5 The diagram illustrates a structural schematic of an application testing apparatus provided in some embodiments of the present invention, which may specifically include the following modules:

[0192] The specified user model creation module 501 is used to create a specified user model for a specified user.

[0193] The simulated behavior testing module 502 is used to call the specified user model to simulate the operation behavior of the specified user when the application enters the specified user mode for the specified user, so as to test the application.

[0194] The behavior evaluation module 503 is used to acquire the behavior data of the operation behavior and evaluate the behavior data;

[0195] The test result generation module 504 is used to generate test results for the specified user mode based on the evaluation results.

[0196] In some embodiments of the present invention, the apparatus further includes:

[0197] The constraint acquisition module is used to acquire the constraints related to the specified user.

[0198] A constraint condition determination module is used to detect whether the application satisfies the constraint conditions;

[0199] The test result generation module is used to generate test results for the specified user mode based on the test results.

[0200] In some embodiments of the present invention, the constraints include constraints on visual elements in the application, and the test result generation module 504 includes:

[0201] The visualization element determination submodule is used to generate test results indicating that the visualization element in the specified user mode is abnormal when the visualization element in the application does not meet the constraints of the visualization element.

[0202] In some embodiments of the present invention, the operational behavior includes operational behavior on controllable elements in the application, and the behavior evaluation module 503 includes:

[0203] The operation result determination submodule is used to determine the operation result on the controllable elements in the application based on the behavior data;

[0204] The probability value determination submodule is used to determine the probability value of an erroneous operation on the controllable element based on the operation result.

[0205] The probability value comparison submodule is used to compare the probability value of the erroneous operation with the preset probability value to obtain the evaluation result.

[0206] In some embodiments of the present invention, the test result generation module 504 includes:

[0207] The erroneous operation determination submodule is used to generate a test result indicating that the controllable element in the specified user mode is abnormal when the probability value of the erroneous operation is greater than a preset probability value.

[0208] In some embodiments of the present invention, the designated user model establishment module 501 includes:

[0209] The historical user data acquisition submodule is used to acquire historical user data for a specified user.

[0210] The specified user model building submodule is used to build a specified user model for the specified user based on the historical user data.

[0211] In some embodiments of the present invention, the apparatus further includes:

[0212] The optimization scheme generation module is used to generate an optimization scheme for the specified user mode based on the test results.

[0213] In some embodiments of the present invention, the designated user is an elderly user.

[0214] In this embodiment of the invention, a specified user model is established for a specified user; when the application enters the specified user mode for the specified user, the specified user model is invoked to simulate the operation behavior of the specified user in order to test the application; behavioral data of the operation behavior is obtained and evaluated; and test results for the specified user mode are generated based on the evaluation results. This realizes the testing of the application by establishing a user model for a specified user and simulating its operation behavior, thereby improving the accuracy and stability of application testing.

[0215] Some embodiments of the present invention also provide an electronic device, including a processor, a memory, and a computer program stored in the memory and capable of running on the processor, wherein the computer program, when executed by the processor, implements the method described above.

[0216] Some embodiments of the present invention also provide a computer-readable storage medium on which a computer program is stored, and which, when executed by a processor, implements the method described above.

[0217] Some embodiments of the present invention also provide a computer program product, including a computer program that, when executed by a processor, implements the method described above.

[0218] As the device embodiment is basically similar to the method embodiment, the description is relatively simple, and relevant parts can be found in the description of the method embodiment.

[0219] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties. Furthermore, the collection, use and processing of the relevant data must comply with the relevant laws, regulations and standards of the relevant countries and regions, and corresponding operation portals are provided for users to choose to authorize or refuse.

[0220] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. The same or similar parts between the various embodiments can be referred to each other.

[0221] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, apparatus, or computer program products. Therefore, embodiments of the present invention can take the form of entirely hardware embodiments, entirely software embodiments, or embodiments combining software and hardware aspects. Furthermore, embodiments of the present invention can take the form of computer program products implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0222] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, terminal devices (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing terminal device to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing terminal device, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0223] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing terminal device to operate in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0224] These computer program instructions can also be loaded onto a computer or other programmable data processing terminal equipment, causing a series of operational steps to be performed on the computer or other programmable terminal equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable terminal equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0225] Although preferred embodiments of the present invention have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments as well as all changes and modifications falling within the scope of the embodiments of the present invention.

[0226] Finally, it should be noted that in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or terminal device that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or terminal device. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or terminal device that includes the aforementioned element.

[0227] The above provides a detailed description of the method, apparatus, device, medium, and product for application testing. Specific examples have been used to illustrate the principles and implementation methods of the present invention. The descriptions of the above embodiments are only for the purpose of helping to understand the method and core ideas of the present invention. At the same time, those skilled in the art will recognize that, based on the ideas of the present invention, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of the present invention.

Claims

1. A method for testing an application, characterized in that, The method includes: Establish a specified user model for a specified user; the specified user model is constructed based on the specified user's historical user data, the specified user model reflects the specified user's characteristics, preferences and behavioral patterns, and the historical user data is a record of the specified user's behavior; When the application enters the specified user mode for the specified user, the specified user model is invoked to simulate the operation behavior of the specified user in order to test the application; Acquire behavioral data of the operation behavior, which includes the operation behavior on controllable elements in the application; Based on the behavioral data, the operation result on the controllable element in the application is determined; the operation result is used to evaluate whether the operation constitutes an erroneous operation. Based on the operation results, the probability value of erroneous operation on the controllable element is determined; the probability value of erroneous operation is calculated from the frequency or pattern of erroneous operation, and the probability of erroneous operation is the probability of misoperation or the probability of failure. The error operation probability value is compared with the preset probability value to obtain the evaluation result for the controllable element; Based on the evaluation results, test results are generated for the specified user mode; The step of generating test results for the specified user mode based on the evaluation results includes: When the probability value of the erroneous operation is greater than a preset probability value, a test result indicating that the controllable element in the specified user mode is abnormal is generated.

2. The method according to claim 1, characterized in that, Also includes: Obtain the constraints associated with the specified user; Detect whether the application satisfies the constraints; Based on the test results, test results are generated for the specified user mode.

3. The method according to claim 2, characterized in that, The constraints include constraints on visual elements in the application, and generating test results for the specified user mode based on the detection results includes: When a visual element in the application does not meet the constraints of the visual element, a test result indicating that the visual element in the specified user mode is abnormal is generated.

4. The method according to any one of claims 1 to 3, characterized in that, The step of establishing a specified user model for a specified user includes: Retrieve historical user data for a specified user; Based on the historical user data, establish a specific user model for the specified user.

5. The method according to any one of claims 1 to 3, characterized in that, Also includes: Based on the test results, an optimization scheme is generated for the specified user mode.

6. The method according to claim 1, characterized in that, The designated user is an elderly user.

7. An apparatus for testing applications, characterized in that, The device includes: A specified user model building module is used to build a specified user model for a specified user; the specified user model is built based on the historical user data of the specified user, and the specified user model reflects the characteristics, preferences and behavioral patterns of the specified user, and the historical user data is a record of behavior for the specified user; The simulated behavior testing module is used to simulate the operation behavior of the specified user when the application enters the specified user mode for the specified user, so as to test the application. The operation result determination submodule is used to acquire the behavior data of the operation behavior, which includes the operation behavior on the controllable elements in the application; determine the operation result on the controllable elements in the application based on the behavior data; and use the operation result to evaluate whether the operation behavior constitutes an erroneous operation. The probability value determination submodule is used to determine the erroneous operation probability value of the controllable element based on the operation result; the erroneous operation probability value is calculated from the occurrence frequency or pattern of erroneous operation, and the erroneous operation probability is the probability of misoperation or the probability of failure. The probability value comparison submodule is used to compare the probability value of the erroneous operation with a preset probability value to obtain an evaluation result for the controllable element. The test result generation module is used to generate test results for the specified user mode based on the evaluation results; The test result generation module includes: The erroneous operation determination submodule is used to generate a test result indicating that the controllable element in the specified user mode is abnormal when the probability value of the erroneous operation is greater than a preset probability value.

8. An electronic device, characterized in that, It includes a processor, a memory, and a computer program stored in the memory and capable of running on the processor, wherein the computer program, when executed by the processor, implements the method as described in any one of claims 1 to 6.

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

10. A computer program product, characterized in that, It includes a computer program that, when executed by a processor, implements the method as described in any one of claims 1 to 6.

Images