Software automated testing method, device, computer equipment and storage medium

Abstract

The present application relates to the field of automated testing tools for R&D management, and specifically to a software automated testing method, device, computer equipment and storage medium. The method is to find the software to be tested and the test scenario specified by the software automated testing request after obtaining the software automated testing request; find the preset script library to obtain the RPA test execution script corresponding to the automated testing request; execute the RPA test execution script; during the execution of the RPA test execution script, call the artificial intelligence component corresponding to the test scenario to perform software testing on the software to be tested in the test scenario and obtain the software test results; generate a software test report based on the software test results. The present application is based on the RPA test execution script to execute regular and repetitive workflow tasks in the software testing process, and at the same time, combined with specific test scenarios, uses artificial intelligence components to better simulate the manual testing process, thereby effectively improving the efficiency of automated testing.

Description

Technical Field

[0001] The present application relates to the field of computer technology, and in particular to a software automation testing method, apparatus, computer equipment and storage medium. Background Art

[0002] Software testing is the process of running or measuring a software system using manual or automatic means, with the purpose of verifying whether it meets the specified requirements or clarifying the difference between the expected results and the actual results. The usual software testing process is usually that after the test cases are designed and reviewed, the testers perform the test step by step according to the procedures described in the test cases to compare the actual results with the expected results. Automated testing is a process that converts human-driven test behavior into machine execution. When encountering tasks that cannot be completed by manual testing, automated testing can take advantage of the machine's fearlessness of fatigue to complete the established test goals, such as stress testing that simulates a large number of user scenarios. The execution of automated testing requires the writing of a large number of test scripts to support simple and repetitive testing work. Each test script is a test case, and it is difficult to connect large-scale application scenarios in a procedural manner.

[0003] However, the maintenance cost of the test scripts used in automated testing is high, and they often need to be updated synchronously with the application updates, and the modifications are relatively frequent, which affects the test efficiency of automated testing. Summary of the invention

[0004] Based on this, it is necessary to provide a software automation testing method, device, computer equipment and storage medium that can more effectively improve the efficiency of automation testing in response to the above technical problems.

[0005] A software automation testing method, the method comprising:

[0006] Obtain a software automated testing request, and search for the software to be tested and the test scenario specified in the software automated testing request;

[0007] Searching a preset script library according to the software to be tested and the test scenario to obtain an RPA (Robotic process automation) test execution script corresponding to the automated test request;

[0008] Execute the RPA test execution script;

[0009] During the execution of the RPA test execution script, the artificial intelligence component corresponding to the test scenario is called to perform software testing on the software to be tested under the test scenario and obtain software testing results;

[0010] A software test report is generated according to the software test results.

[0011] In one embodiment, before searching a preset script library according to the software to be tested and the test scenario to obtain an RPA test execution script corresponding to the automated test request, the method further includes:

[0012] Based on the RPA underlying process engine and component library, the test processes corresponding to multiple test scenarios are recorded by executing scripts through the visual RPA editor, and the RPA test execution scripts corresponding to each test scenario are generated;

[0013] Build a preset script library based on the RPA test execution scripts in various test scenarios.

[0014] In one of the embodiments, during the execution of the RPA test execution script, calling the artificial intelligence component corresponding to the test scenario to perform software testing on the software to be tested under the test scenario, and obtaining the software test result includes:

[0015] Acquire the scene attributes of the test scene, determine the artificial intelligence component corresponding to the scene attribute and the calling node of the artificial intelligence component;

[0016] When the RPA test execution script is executed to the calling node, the artificial intelligence component corresponding to the scenario attribute is called to perform software testing on the software to be tested under the test scenario to obtain software testing results.

[0017] In one embodiment, the method further comprises:

[0018] When a running error occurs in the RPA test execution script, identifying the error type of the error;

[0019] When the error type is a blocking error, an error prompt message corresponding to the error type is generated and pushed based on artificial intelligence;

[0020] When the error type of the error is an operation error, an error handling solution corresponding to the operation error is found based on artificial intelligence, and the running error of the RPA test execution script is handled based on the error handling solution.

[0021] In one embodiment, the generating and pushing of an error prompt message corresponding to the error type based on artificial intelligence includes:

[0022] Find the log information corresponding to the blocking error;

[0023] Generate an error prompt message corresponding to the blocking error according to the log information;

[0024] Push the error prompt message.

[0025] In one embodiment, the processing of the running error of the RPA test execution script based on artificial intelligence and the error type of the error includes:

[0026] When the error type of the error is an operation error, identifying the error type of the operation error based on artificial intelligence;

[0027] Search the preset solution list to determine the error handling solution corresponding to the error type;

[0028] The running error of the RPA test execution script is processed based on the error processing scheme.

[0029] In one embodiment, after generating a software test report according to the software test result, the method further includes:

[0030] Obtaining software defects in the software test results;

[0031] Generate error reminder information based on the software defect;

[0032] Find the development terminal corresponding to the software defect, and push the error prompt information to the development terminal.

[0033] A software automation testing device, comprising:

[0034] A request acquisition module is used to acquire a software automated test request and search for the software to be tested and the test scenario specified in the software automated test request;

[0035] A script search module is used to search a preset script library according to the software to be tested and the test scenario, and obtain an RPA test execution script corresponding to the automated test request;

[0036] An RPA calling module is used to execute the RPA test execution script;

[0037] A software testing module is used to call the artificial intelligence component corresponding to the test scenario during the execution of the RPA test execution script, so as to perform software testing on the software to be tested under the test scenario and obtain software testing results;

[0038] The report generation module is used to generate a software test report according to the software test results.

[0039] A computer device comprises a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the following steps are implemented:

[0040] Obtain a software automated testing request, and search for the software to be tested and the test scenario specified in the software automated testing request;

[0041] Searching a preset script library according to the software to be tested and the test scenario to obtain an RPA test execution script corresponding to the automated test request;

[0042] Execute the RPA test execution script;

[0043] During the execution of the RPA test execution script, the artificial intelligence component corresponding to the test scenario is called to perform software testing on the software to be tested under the test scenario and obtain software testing results;

[0044] A software test report is generated according to the software test results.

[0045] A computer storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the following steps are implemented:

[0046] Obtain a software automated testing request, and search for the software to be tested and the test scenario specified in the software automated testing request;

[0047] Searching a preset script library according to the software to be tested and the test scenario to obtain an RPA test execution script corresponding to the automated test request;

[0048] Execute the RPA test execution script;

[0049] During the execution of the RPA test execution script, the artificial intelligence component corresponding to the test scenario is called to perform software testing on the software to be tested under the test scenario and obtain software testing results;

[0050] A software test report is generated according to the software test results.

[0051] The above-mentioned software automation testing method, device, computer equipment and storage medium, wherein the method searches for the software to be tested and the test scenario specified by the software automation testing request after obtaining the software automation testing request; searches the preset script library according to the software to be tested and the test scenario, and obtains the RPA test execution script corresponding to the automation testing request; executes the RPA test execution script; during the execution of the RPA test execution script, calls the artificial intelligence component corresponding to the test scenario to perform software testing on the software to be tested in the test scenario and obtain the software test results; generates a software test report according to the software test results. This application determines the software to be tested and the test scenario based on the software automation testing request, thereby obtaining the RPA test execution script, and executes regular and repetitive workflow tasks in the software testing process based on the RPA test execution script. At the same time, combined with specific test scenarios, artificial intelligence components are used to better simulate the manual testing process, thereby effectively improving the efficiency of automated testing. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] Figure 1 An application scenario diagram of a software automation testing method in an embodiment;

[0053] Figure 2 A flowchart of a software automation testing method in one embodiment;

[0054] Figure 3 In one embodiment Figure 2 Schematic diagram of the sub-process of step 207;

[0055] Figure 4 A schematic diagram of a flow chart of executing an error correction step in an embodiment;

[0056] Figure 5 A flowchart of a software defect prompting step in one embodiment;

[0057] Figure 6 A structural block diagram of a software automation testing device in one embodiment;

[0058] Figure 7 FIG. 4 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0059] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0060] The embodiments of the present application can acquire and process relevant data based on artificial intelligence technology. Among them, artificial intelligence (AI) is the theory, method, technology and application system that uses digital computers or machines controlled by digital computers to simulate, extend and expand human intelligence, perceive the environment, acquire knowledge and use knowledge to obtain the best results.

[0061] AI basic technologies generally include sensors, dedicated AI chips, cloud computing, distributed storage, big data processing technology, operation / interaction systems, mechatronics, etc. AI software technologies mainly include computer vision technology, robotics technology, biometrics technology, speech processing technology, natural language processing technology, and machine learning / deep learning.

[0062] This application specifically provides a software automation testing method that can be applied to Figure 1 In the application environment shown. Among them, the terminal 102 can communicate with the software automation testing server 104 through the network, and the terminal 102 can send a software automation testing request corresponding to the software to be tested to the software automation testing server 104. After receiving the software automation testing request, the software automation testing server 104 searches for the software to be tested and the test scenario specified by the software automation testing request; searches the preset script library according to the software to be tested and the test scenario, and obtains the RPA test execution script corresponding to the automated test request; executes the RPA test execution script; during the execution of the RPA test execution script, calls the artificial intelligence component corresponding to the test scenario to perform software testing on the software to be tested in the test scenario, and obtains the software test results; generates a software test report according to the software test results. Among them, the terminal 102 can be, but is not limited to, various personal computers, laptops, smart phones, tablet computers and portable wearable devices, and the software automation testing server 104 can be an independent server, or it can be a cloud server that provides cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, content delivery networks (Content Delivery Network, CDN), and basic cloud computing services such as big data and artificial intelligence platforms.

[0063] In one embodiment, Figure 2 As shown, a software automation testing method is provided, which is applied to Figure 1 The software automation test server 104 in the example is used for illustration, and the following steps are included:

[0064] Step 201: Obtain a software automated testing request, and search for the software to be tested and the test scenario specified by the software automated testing request.

[0065] Among them, automated testing is a process of converting human-driven testing behavior into machine execution. Usually, after designing test cases and passing the review, testers perform tests step by step according to the procedures described in the test cases to obtain a comparison between the actual results and the expected results. In this process, in order to save manpower, time or hardware resources and improve testing efficiency, the concept of automated testing was introduced. The processing efficiency of the software testing process is improved through machine execution. The software automated testing request is specifically used to request the automated server to perform automated testing on the specified software to be tested. The software automated testing request can be specifically generated according to the test case corresponding to the software to be tested. The test case refers to the description of the test task for a specific software product, reflecting the test plan, method, technology and strategy. Its content includes test objectives, test environment, input data, test steps, expected results, test scripts, etc. It can be simply understood that a test case is a set of test inputs, execution conditions and expected results compiled for a special goal, which is used to verify whether a specific software requirement is met. The software to be tested is the test target of the software automated testing method in this solution. The test scenario refers to a business scenario faced by the software to be tested constructed through automated testing.

[0066] This application specifically uses RPA technology to perform software automation testing to improve the efficiency of testing. RPA is a robotic process automation system, which is an application that provides another way to automate the manual operation process of end users by imitating the manual operation method of end users on computers. When testing, the test staff can generate a software automation test request based on the test case, and then send the software automation test request to the software automation test server 104 through the terminal 102. The software automation test server 104 obtains the software automation test request, searches for the software to be tested and the test scenario specified by the software automation test request, and starts the automated test. In a specific embodiment, the software to be tested is specifically an internal investment management system of an enterprise. The internal investment management system of an enterprise has the characteristics of many pages, many verification logics, and complex interactive operations. It relies more on the historical testing experience of testers, and these testing experiences are difficult to pass on. By introducing RPA robots in software automation testing, the testing processes of investment business processes in scenarios such as pre-investment project establishment, pre-examination, investment decision, approval and stamping during investment, post-investment management, and exit management can be solidified. By replacing manual testing with machine testing, the scope of regression testing can be expanded, labor costs can be reduced, and quality improvement, cost reduction, and efficiency improvement can be achieved.

[0067] Step 203: Search the preset script library according to the software to be tested and the test scenario to obtain the RPA test execution script corresponding to the automated test request.

[0068] Among them, the preset script library consists of pre-written RPA test execution scripts for different scenarios. The RPA test execution script generally refers to a series of instructions for a specific test, which can be executed by an automated testing tool, which refers to the RPA executor in this application. In order to improve the maintainability and reusability of test scripts, they must be constructed before executing the test scripts. You may find that some operations will appear in several test processes. Therefore, the goals of these operations should be determined purposefully so that their implementation can be reused. Test scripts are computer-readable instructions that automatically execute a test process (or part of a test process). Test scripts can be created (recorded) or automatically generated using a test automation tool, or programmed in a programming language, or they can be completed by combining the first three methods.

[0069] Specifically, the process of automated testing can generally be performed through a pre-written test execution script. In this step, the software automated testing server 104 can search the preset script library based on a given test scenario to obtain the corresponding RPA test execution script under the scenario. Then, software testing can be performed based on the RPA test execution script. In this process, the software automated testing server 104 can specifically control the RPA executor to obtain the test execution script, and then load the obtained RPA test execution script into the RPA executor.

[0070] Step 205: Execute the RPA test execution script.

[0071] Step 207, during the execution of the RPA test execution script, the artificial intelligence component corresponding to the test scenario is called to perform software testing on the software to be tested in the test scenario and obtain the software test results.

[0072] Among them, artificial intelligence components refer to components that use artificial intelligence technology to complete parts of the testing process that require flexible processing.

[0073] Specifically, artificial intelligence components can be used to complete test tasks in test scenarios such as text recognition and conversational robots during the test process. The RPA executor generates test data through test execution scripts, outputs test results of each test case, and completes the test tasks of related scenarios. During the test process, rule-based and repetitive workflow tasks can be processed with the help of RPA digital tools. After these workflows are linked together based on RPA test execution scripts, the manual test process can be better simulated. For example, in the full process of investment business of an enterprise, some procedural prescribed operations such as project pre-examination and investment decision-making, file upload, opinion solicitation, approval chain configuration selection, and seal application are involved. Software testing robots built with RPA technology can quickly and accurately complete the testing work of these processes. On the one hand, it can save a lot of valuable time of employees to solve higher-value and more challenging testing work, and on the other hand, it can also reduce the situation where manual regression coverage is incomplete and business use is affected after production and launch.

[0074] Step 209: Generate a software test report based on the software test results.

[0075] The test report is used to report to the tester the specific execution status of the software testing process corresponding to the software automation test request. Based on the test report, the tester can understand the specific situation of the software testing, thereby effectively determining the actual use effect of the software to be tested and judging whether it meets the expected requirements.

[0076] The above-mentioned software automation testing method, wherein the method searches for the software to be tested and the test scenario specified by the software automation testing request after obtaining the software automation testing request; searches the preset script library according to the software to be tested and the test scenario, and obtains the RPA test execution script corresponding to the automation testing request; executes the RPA test execution script; during the execution of the RPA test execution script, calls the artificial intelligence component corresponding to the test scenario to perform software testing on the software to be tested in the test scenario and obtain the software test results; generates a software test report according to the software test results. This application determines the software to be tested and the test scenario based on the software automation testing request, thereby obtaining the RPA test execution script, and executes regular and repetitive workflow tasks in the software testing process based on the RPA test execution script. At the same time, combined with specific test scenarios, artificial intelligence components are used to better simulate the manual testing process, thereby effectively improving the efficiency of automated testing.

[0077] In one of the embodiments, before step 203, it also includes: based on the RPA underlying process engine and component library, through a visual RPA editor, recording the test processes corresponding to multiple test scenarios in the form of execution scripts, and generating RPA test execution scripts corresponding to each test scenario; and building a preset script library based on the RPA test execution scripts under each test scenario.

[0078] Specifically, the tester can use the software automation testing server 104, based on the RPA underlying process engine and component library, and through the visual RPA editor, record the test processes corresponding to multiple test operation scenarios step by step by executing scripts, write corresponding test execution scripts, and then complete the collection of test scripts based on respective business scenarios. One script corresponds to one test scenario, and one scenario corresponds to multiple tests. The test script and the test scenario are intrinsically associated by name. Among them, the editing process of the visual RPA editor specifically means that the tester can use the visual integrated development environment to complete the editing of the test execution script by dragging and dropping, and generate the test execution script. In this embodiment, through the visual RPA editor, the RPA test execution script corresponding to each test scenario can be written more intuitively and effectively to ensure the efficiency of the RPA test execution script.

[0079] In one embodiment, if Figure 3 As shown, step 207 includes:

[0080] Step 302, obtain the scene attributes of the test scene, determine the artificial intelligence components corresponding to the scene attributes and the calling nodes of the artificial intelligence components.

[0081] Step 304: When the RPA test execution script is executed to the calling node, the artificial intelligence component corresponding to the scenario attribute is called to perform software testing on the software to be tested in the test scenario and obtain the software test results.

[0082] Among them, the RPA test execution script simulates manual testing according to established rules, interacts with the computer to process the job, and thus completes the software test. Therefore, several nodes can be added during the test process, and the test can be completed on these nodes with the help of artificial intelligence components. For example, when the test scenario involves intelligent order review, it can be determined that the artificial intelligence component corresponding to the scene attribute is a text recognition component, and the calling node is a single-order review node. Then when the RPA test execution script is executed to the single-order review node, the test task in the test scenario is completed by the text recognition component. When the test scenario designs scenes such as online customer service, it can be determined that the artificial intelligence component corresponding to the scene attribute is a dialogue robot component, and the calling node is a dialogue node. When the RPA test execution script is executed to the dialogue node, the corresponding test task is completed by the dialogue robot component. In this embodiment, by determining the artificial intelligence component and the calling node corresponding to the scene attribute, the accurate execution of the software test can be effectively guaranteed by the RPA component during the software testing process.

[0083] In one embodiment, if Figure 4 As shown, it also includes:

[0084] Step 401: When a running error occurs in the RPA test execution script, the error type is identified.

[0085] Step 403, when the error type is a blocking error, an error prompt message corresponding to the error type is generated and pushed based on artificial intelligence.

[0086] Step 405: When the error type is an operation error, an error handling solution corresponding to the operation error is found based on artificial intelligence, and the running error of the RPA test execution script is handled based on the error handling solution.

[0087] Specifically, the solution of the present application can also add an intelligent job processing mechanism based on artificial intelligence during the software automation testing process. When an operation error occurs in the RPA test execution script, the error type can be identified, and then the corresponding processing can be performed based on the error type to ensure the smooth progress of the software automation test. Specifically, intelligent error correction can be performed according to the error type. When encountering technical problems that cannot be corrected, such as blocking errors, an error prompt message corresponding to the error type is automatically generated and pushed based on artificial intelligence. For example, an error prompt email or an error prompt SMS can be sent to a preset test leader's mailbox, thereby prompting the test leader to manually intervene in the automated testing process to advance the next step. If it is a general operation error prompt message, it can be automatically judged and processed, that is, the error handling solution corresponding to the operation error is found based on artificial intelligence; the operation error of the RPA test execution script is processed based on the error handling solution. Thereby, the test process of the software automation test is not interrupted. Ensure the efficiency of the software automation test. In this embodiment, through intelligent error correction, the smooth progress of the software automation test process can be effectively guaranteed, thereby improving the efficiency of the software automation test.

[0088] In one embodiment, step 403 includes: searching for log information corresponding to the blocking error, generating an error prompt message corresponding to the blocking error according to the log information, and pushing the error prompt message.

[0089] The log information refers to the information recorded in the software operation log generated during the software automation testing process.

[0090] Specifically, when encountering a blocking error, it is impossible to solve the problem through artificial intelligence. Therefore, the log information corresponding to the blocking error can be found at this time, and the log information helps to locate the location where the error occurs and the specific information of the error. Then, an error prompt message corresponding to the blocking error is generated according to the log information, and the error prompt message is pushed. The error prompt message here can be pushed in the form of an email or text message, and the object of the push is specifically the test staff of the software automation test. After receiving the error prompt message, the test staff can locate the location where the error occurs and the specific information of the error based on the location in the error prompt message, so as to perform error correction processing. In the present embodiment, the error prompt message is generated according to the log information, which helps the efficiency of error repair.

[0091] In one of the embodiments, step 405 includes: when the error type of the error is an operation error, identifying the error type of the operation error based on artificial intelligence; searching a preset solution list to determine an error handling solution corresponding to the error type; and handling a running error of the RPA test execution script based on the error handling solution.

[0092] Specifically, for common operating errors, corresponding automatic processing solutions can be sorted out in advance. Then, an association is established between the operating error type and the automatic processing solution to construct a preset solution list. When the error type of the error is an operating error, the error type of the operating error is identified based on artificial intelligence. In one embodiment, the error type of the operating error can be identified based on the semantic recognition in artificial intelligence and the error information, and then the preset solution list is searched to determine the error processing solution corresponding to the error type; the running error of the RPA test execution script is processed based on the error processing solution. In this embodiment, the operating errors in the automated testing process are processed by artificial intelligence and searching the preset solution list, which can effectively improve the error processing efficiency, thereby ensuring the efficiency of software automated testing.

[0093] In one embodiment, if Figure 5 As shown, after step 209, the following steps are also included:

[0094] Step 502: Obtain software defects in the software test results.

[0095] Step 504: Generate error reminder information based on the software defect.

[0096] Step 506, searching for a development terminal corresponding to the software defect, and pushing error prompt information to the development terminal.

[0097] Specifically, in the software development process, different developers are responsible for developing different functional modules or contents in the software. The software testing process is mainly to determine whether the software to be tested will have defects in the test scenario, and what the software defects are. Then, error reminder information is generated based on the software defects to remind developers to repair the defects. In a specific embodiment, defects can be created one by one in the development collaboration space, corresponding error prompt information can be generated, and then the development terminal corresponding to the software defect can be found, and the software defect can be sent to the development terminal through the error prompt information to remind specific developers and urge the repair of the defect. In this embodiment, error reminder information is generated based on software defects, which can effectively remind the software to repair defects and improve the repair efficiency of the software to be tested.

[0098] It should be understood that although Figure 2-5 The steps in the flowchart are shown in sequence as indicated by the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified in this document, there is no strict order restriction for the execution of these steps, and these steps can be executed in other orders. Moreover, Figure 2-5 At least part of the steps may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily executed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be executed in turn or alternately with other steps or at least part of the sub-steps or stages of other steps.

[0099] In one embodiment, Figure 6 As shown, a software automation testing device is provided, comprising:

[0100] The request acquisition module 601 is used to acquire a software automation test request and search for the software to be tested and the test scenario specified by the software automation test request.

[0101] The script search module 603 is used to search the preset script library according to the software to be tested and the test scenario, and obtain the RPA test execution script corresponding to the automated test request.

[0102] The RPA calling module 605 is used to execute the RPA test execution script.

[0103] The software testing module 607 is used to call the artificial intelligence component corresponding to the test scenario during the execution of the RPA test execution script, so as to perform software testing on the software to be tested in the test scenario and obtain the software testing results.

[0104] The report generation module 609 is used to generate a software test report according to the software test results.

[0105] In one of the embodiments, a script writing module is also included, which is used to: based on the RPA underlying process engine and component library, record the test processes corresponding to multiple test scenarios by executing scripts through a visual RPA editor, and generate RPA test execution scripts corresponding to each test scenario; build a preset script library based on the RPA test execution scripts under each test scenario.

[0106] In one of the embodiments, the software testing module 607 is specifically used to: obtain the scenario attributes of the test scenario, determine the artificial intelligence components corresponding to the scenario attributes and the calling nodes of the artificial intelligence components; when the RPA test execution script is executed to the calling node, call the artificial intelligence components corresponding to the scenario attributes to perform software testing on the software to be tested in the test scenario and obtain software testing results.

[0107] In one of the embodiments, an error correction module is also included, which is used to: when a runtime error occurs in the RPA test execution script, identify the error type of the error; when the error type is a blocking error, generate and push an error prompt message corresponding to the error type based on artificial intelligence; when the error type is an operation error, find the error handling solution corresponding to the operation error based on artificial intelligence, and handle the runtime error of the RPA test execution script based on the error handling solution.

[0108] In one of the embodiments, the error correction module is specifically used to: search for log information corresponding to the blocking error; generate an error prompt message corresponding to the blocking error according to the log information; and push the error prompt message.

[0109] In one of the embodiments, the error correction module is also used to: when the error type of the error is an operation error, identify the error type of the operation error based on artificial intelligence; search a preset plan list to determine the error handling plan corresponding to the error type; and handle the running error of the RPA test execution script based on the error handling plan.

[0110] In one of the embodiments, a defect reporting module is further included, which is used to: obtain software defects in software test results; generate error prompt information based on the software defects; find the development terminal corresponding to the software defects, and push the error prompt information to the development terminal.

[0111] For the specific embodiments of the software automation testing device, please refer to the embodiments of the software automation testing method above, which will not be repeated here. Each module in the above-mentioned software automation testing device can be implemented in whole or in part by software, hardware and a combination thereof. The above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory in the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

[0112] In one embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as follows: Figure 7 As shown. The computer device includes a processor, a memory, a network interface and a database connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store software automation test data. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a software automation test method is implemented.

[0113] Those skilled in the art will understand that Figure 7 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0114] In one embodiment, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the following steps are implemented:

[0115] Obtain a software automated testing request, and search for the software to be tested and the test scenario specified in the software automated testing request;

[0116] Search the preset script library based on the software to be tested and the test scenario to obtain the RPA test execution script corresponding to the automated test request;

[0117] Execute RPA test execution script;

[0118] During the execution of the RPA test execution script, the artificial intelligence component corresponding to the test scenario is called to perform software testing on the software to be tested in the test scenario and obtain the software test results;

[0119] Generate software testing report based on software testing results.

[0120] In one embodiment, when the processor executes the computer program, the following steps are also implemented: based on the RPA underlying process engine and component library, the test processes corresponding to multiple test scenarios are recorded by executing scripts through a visual RPA editor, and an RPA test execution script corresponding to each test scenario is generated; a preset script library is constructed based on the RPA test execution scripts under each test scenario.

[0121] In one embodiment, when the processor executes the computer program, the following steps are also implemented: obtaining the scenario attributes of the test scenario, determining the artificial intelligence components corresponding to the scenario attributes and the calling nodes of the artificial intelligence components; when the RPA test execution script is executed to the calling node, the artificial intelligence components corresponding to the scenario attributes are called to perform software testing on the software to be tested in the test scenario and obtain software testing results.

[0122] In one embodiment, the processor also implements the following steps when executing the computer program: when a runtime error occurs in the RPA test execution script, the error type is identified; when the error type is a blocking error, an error prompt message corresponding to the error type is generated and pushed based on artificial intelligence; when the error type is an operation error, an error handling solution corresponding to the operation error is found based on artificial intelligence, and the runtime error of the RPA test execution script is handled based on the error handling solution.

[0123] In one embodiment, when the processor executes the computer program, the following steps are also implemented: searching for log information corresponding to the blocking error; generating an error prompt message corresponding to the blocking error according to the log information; and pushing the error prompt message.

[0124] In one embodiment, the processor also implements the following steps when executing the computer program: when the error type of the error is an operation error, identifying the error type of the operation error based on artificial intelligence; searching a preset solution list to determine the error handling solution corresponding to the error type; and processing the running error of the RPA test execution script based on the error handling solution.

[0125] In one embodiment, when the processor executes the computer program, the following steps are also implemented: obtaining software defects in the software test results; generating error prompt information based on the software defects; searching for the development terminal corresponding to the software defects, and pushing the error prompt information to the development terminal.

[0126] In one embodiment, a computer storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented:

[0127] Obtain a software automated testing request, and search for the software to be tested and the test scenario specified in the software automated testing request;

[0128] Search the preset script library based on the software to be tested and the test scenario to obtain the RPA test execution script corresponding to the automated test request;

[0129] Execute RPA test execution script;

[0130] During the execution of the RPA test execution script, the artificial intelligence component corresponding to the test scenario is called to perform software testing on the software to be tested in the test scenario and obtain the software test results;

[0131] Generate software testing report based on software testing results.

[0132] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: based on the RPA underlying process engine and component library, the test processes corresponding to multiple test scenarios are recorded by executing scripts through a visual RPA editor, and an RPA test execution script corresponding to each test scenario is generated; a preset script library is constructed based on the RPA test execution scripts under each test scenario.

[0133] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: obtaining the scenario attributes of the test scenario, determining the artificial intelligence components corresponding to the scenario attributes and the calling nodes of the artificial intelligence components; when the RPA test execution script is executed to the calling node, the artificial intelligence components corresponding to the scenario attributes are called to perform software testing on the software to be tested in the test scenario and obtain software testing results.

[0134] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: when a runtime error occurs in the RPA test execution script, the error type is identified; when the error type is a blocking error, an error prompt message corresponding to the error type is generated and pushed based on artificial intelligence; when the error type is an operation error, an error handling solution corresponding to the operation error is searched based on artificial intelligence, and the runtime error of the RPA test execution script is handled based on the error handling solution.

[0135] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: searching for log information corresponding to the blocking error; generating an error prompt message corresponding to the blocking error according to the log information; and pushing the error prompt message.

[0136] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: when the error type of the error is an operation error, identifying the error type of the operation error based on artificial intelligence; searching a preset solution list to determine the error handling solution corresponding to the error type; and handling the running error of the RPA test execution script based on the error handling solution.

[0137] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: obtaining software defects in the software test results; generating error prompt information based on the software defects; searching for the development terminal corresponding to the software defects, and pushing the error prompt information to the development terminal.

[0138] Those of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be implemented by instructing related hardware through a computer program, and the above-mentioned computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0139] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0140] The above embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention patent. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the patent of the present application shall be subject to the attached claims.

Claims

1. A software automated testing method, the method comprising: Obtain a software automated testing request, and search for the software to be tested and the test scenario specified in the software automated testing request; Searching a preset script library according to the software to be tested and the test scenario to obtain an RPA test execution script corresponding to the automated test request; Execute the RPA test execution script; Acquire the scene attributes of the test scene, determine the artificial intelligence component corresponding to the scene attribute and the calling node of the artificial intelligence component; When the RPA test execution script is executed to the calling node, the artificial intelligence component corresponding to the scenario attribute is called to perform software testing on the software to be tested under the test scenario to obtain software testing results, wherein the artificial intelligence component includes a text recognition component and a dialogue robot component; A software test report is generated according to the software test results.

2. The method according to claim 1, characterized in that Before searching the preset script library according to the software to be tested and the test scenario to obtain the RPA test execution script corresponding to the automated test request, the method further includes: Based on the RPA underlying process engine and component library, the test processes corresponding to multiple test scenarios are recorded by executing scripts through the visual RPA editor, and the RPA test execution scripts corresponding to each test scenario are generated; Build a preset script library based on the RPA test execution scripts in various test scenarios.

3. The method according to claim 1, characterized in that The method further comprises: When a running error occurs in the RPA test execution script, identifying the error type of the error; When the error type is a blocking error, an error prompt message corresponding to the error type is generated and pushed based on artificial intelligence; When the error type of the error is an operation error, an error handling solution corresponding to the operation error is found based on artificial intelligence, and the running error of the RPA test execution script is handled based on the error handling solution.

4. The method according to claim 3, characterized in that: The generating and pushing of the error prompt message corresponding to the error type based on artificial intelligence includes: Find the log information corresponding to the blocking error; Generate an error prompt message corresponding to the blocking error according to the log information; Push the error prompt message.

5. The method according to claim 3, characterized in that: When the error type of the error is an operation error, searching for an error handling solution corresponding to the operation error based on artificial intelligence, and handling the running error of the RPA test execution script based on the error handling solution includes: When the error type of the error is an operation error, identifying the error type of the operation error based on artificial intelligence; Search the preset solution list to determine the error handling solution corresponding to the error type; The running error of the RPA test execution script is processed based on the error processing scheme.

6. The method according to claim 1, characterized in that After generating a software test report according to the software test results, the method further includes: Obtaining software defects in the software test results; Generate error prompt information based on the software defect; Find the development terminal corresponding to the software defect, and push the error prompt information to the development terminal.

7. A software automated testing device, characterized in that: The device comprises: A request acquisition module is used to acquire a software automated test request and search for the software to be tested and the test scenario specified in the software automated test request; A script search module is used to search a preset script library according to the software to be tested and the test scenario, and obtain an RPA test execution script corresponding to the automated test request; An RPA calling module is used to execute the RPA test execution script; A software testing module, used to obtain the scenario attributes of the test scenario, determine the artificial intelligence component corresponding to the scenario attribute and the calling node of the artificial intelligence component; when the RPA test execution script is executed to the calling node, call the artificial intelligence component corresponding to the scenario attribute to perform software testing on the software to be tested under the test scenario and obtain software testing results, wherein the artificial intelligence component includes a text recognition component and a dialogue robot component; The report generation module is used to generate a software test report according to the software test results.

8. The device according to claim 7, characterized in that The system also includes a script writing module, which is used to: based on the RPA underlying process engine and component library, record the test processes corresponding to multiple test scenarios by executing scripts through a visual RPA editor, and generate RPA test execution scripts corresponding to each test scenario; Build a preset script library based on the RPA test execution scripts in various test scenarios.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

10. A computer storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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