Test data processing method and device and electronic equipment

Abstract

The invention provides a test data processing method and device and electronic equipment, and the method comprises the steps: obtaining the demand information of a target demand from a service platform based on a preset query statement and preset configuration information; carrying out analytic statistics on all the obtained demand information to obtain statistical information of multiple dimensions; and generating a data file containing a function list and a test summary based on preset configuration information, the obtained all demand information and the multi-dimensional statistical information. By adopting the method and the device, the problems of relatively high labor cost and relatively low reliability of a test summary and function list writing mode in the prior art can be relieved.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and in particular to a test data processing method, device and electronic equipment. Background Art

[0002] In the software testing industry, conducting test summaries and writing function lists are important tasks in software testing. Test summaries are a review, inspection, analysis and evaluation of a certain period of time, a certain project (or certain tasks) after it has come to an end (or is completed) through data collection (or text summary), thus forming a document containing the test process and test results. A detailed test summary should contain sufficient defect analysis information, evaluation of product quality and test process, and methods and processes for optimizing software testing. Function lists are important documents for software releases, which can help implementers understand the release content and relevant requirements implementation precautions.

[0003] For software products with strong regionalization and projectization, test summaries corresponding to different regions and modules (i.e. programs written in specific languages) are formed after testing is completed. This is particularly important for monitoring product development and testing processes and improving product quality; and a list of functions for different regions and modules is formed to facilitate the implementation of upgrade requirements according to respective regions.

[0004] In the prior art, when conducting test summaries and compiling function lists, the usual method is to query the service platform to obtain the full amount of test requirement data, test defect (bug) data, test task lists, etc., and copy them into an Excel document, and manually organize the information in the Excel document to obtain information such as the total number of defects, regions, modules, and defect analysis. Due to the huge amount of iterative test data, this method has a high labor cost and low reliability, and cannot meet the needs of rapid software iteration and release. Summary of the invention

[0005] In view of this, an object of the present invention is to provide a test data processing method, device and electronic device to alleviate the above-mentioned problems existing in the prior art.

[0006] In a first aspect, an embodiment of the present invention provides a test data processing method, the method comprising: obtaining demand information of a target demand from a service platform based on a preset query statement and preset configuration information; wherein the preset configuration information comprises demand query conditions and a file save path, and the demand information comprises demand identification information, demand personnel information, demand time information, test task link information, demand description information, defect information, region information and module information; analyzing and counting all acquired demand information to obtain statistical information of multiple dimensions; wherein the multiple dimensions comprise the number of demands, the time of demand, the number of defects, the region and the module; generating a data file containing a function list and a test summary based on the preset configuration information, all acquired demand information and the statistical information of multiple dimensions.

[0007] In the second aspect, an embodiment of the present invention also provides a test data processing device, which includes: an acquisition module, which is used to obtain demand information of target demand from a service platform based on a preset query statement and preset configuration information; wherein the preset configuration information includes demand query conditions and file save paths, and the demand information includes demand identification information, demand personnel information, demand time information, test task link information, demand description information, defect information, region information and module information; a processing module, which is used to analyze and count all the acquired demand information to obtain statistical information of multiple dimensions; wherein the multiple dimensions include demand quantity, demand time, defect quantity, region and module; a generation module, which is used to generate a data file containing a function list and a test summary based on the preset configuration information, all the acquired demand information and statistical information of multiple dimensions.

[0008] In a third aspect, an embodiment of the present invention further provides an electronic device, comprising a processor and a memory, wherein the memory stores computer executable instructions that can be executed by the processor, and the processor executes the computer executable instructions to implement the test data processing method described in the first aspect above.

[0009] A test data processing method, device and electronic device provided by an embodiment of the present invention obtains target demand information from a service platform based on preset query statements and preset configuration information; analyzes and counts all acquired demand information to obtain statistical information of multiple dimensions; generates a data file containing a function list and a test summary based on the preset configuration information, all acquired demand information and statistical information of multiple dimensions. Using the above technology, it is possible to automatically analyze and count the demand information obtained from the service platform, and then automatically generate a data file containing a function list and a test summary, thereby alleviating the problem of high labor cost and low reliability of the existing method of conducting test summaries and writing function lists, and meeting the needs of rapid iterative release of software.

[0010] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or understood by practicing the present invention. The purpose and other advantages of the present invention are realized and obtained by the structures particularly pointed out in the description, claims and drawings.

[0011] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, preferred embodiments are given below and described in detail with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] In order to more clearly illustrate the specific implementation methods of the present invention or the technical solutions in the prior art, the drawings required for use in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some implementation methods of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0013] Figure 1 A flow chart of a test data processing method according to an embodiment of the present invention;

[0014] Figure 2 An example diagram of a function list in an embodiment of the present invention;

[0015] Figure 3 This is an example diagram of a test summary in an embodiment of the present invention;

[0016] Figure 4 An example diagram of a process for automatically generating a function list and a test summary in an embodiment of the present invention;

[0017] Figure 5 A schematic diagram of the structure of a test data processing device according to an embodiment of the present invention;

[0018] Figure 6 The figure is a schematic diagram of the structure of an electronic device in an embodiment of the present invention. DETAILED DESCRIPTION

[0019] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution of the present invention will be clearly and completely described in combination with the embodiments below. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0020] At present, in the prior art, when summarizing tests and compiling function lists, the usual method is to query the service platform to obtain the full amount of test requirement data, test defect (bug) data, test task list, etc., and copy them into an Excel document, and manually organize the information in the Excel document to obtain information such as the total number of defects, region, module, and defect analysis. Due to the huge amount of iterative test data, this method has a high labor cost and low reliability, and cannot meet the needs of rapid iterative release of software.

[0021] Based on this, the present invention provides a test data processing method, device and electronic device, which can alleviate the above-mentioned problems existing in the prior art.

[0022] To facilitate understanding of this embodiment, a test data processing method disclosed in an embodiment of the present invention is first described in detail. Figure 1 As shown, the method may include the following steps:

[0023] Step S102, based on the preset query statement and the preset configuration information, the demand information of the target demand is obtained from the service platform.

[0024] Among them, the above-mentioned preset configuration information may include demand query conditions, file save paths, etc., and the above-mentioned demand information may include demand identification information, demand personnel information, demand time information, test task link information, demand description information, defect information, region information, module information, etc., without limitation.

[0025] The above-mentioned requirement identification information may refer to information used to identify the requirement. The above-mentioned requirement personnel information may refer to the person who handles the requirement (such as the person who solves the requirement, the person who closes the requirement, the person to whom the requirement is assigned). The above-mentioned requirement time information may refer to information used to characterize the time aspect of the requirement (such as the requirement submission date, the requirement closing date, the requirement resolution date, etc.). The above-mentioned test task link information may refer to information used to characterize the data download address of the test task. The above-mentioned requirement description information may refer to information used to explain the requirement. The above-mentioned defect information may refer to information used to reflect the attributes of the defect (such as defect type, defect name, etc.). The above-mentioned regional information may refer to information used to characterize regional affiliation. The above-mentioned module information may refer to information used to characterize module affiliation.

[0026] The above-mentioned preset query statement may refer to a statement supported by the service platform used by the user to find the relevant demand content. The above-mentioned demand query condition may refer to the condition satisfied by the relevant demand content that the user needs to query, which may be specifically defined in the statement format supported by the service platform, and is not limited to this. The above-mentioned file save path may refer to the storage location of the data file containing the function list and test summary that the user needs to generate.

[0027] Step S104, analyzing and collecting statistics on all acquired demand information to obtain statistical information in multiple dimensions.

[0028] The above-mentioned multiple dimensions may include demand quantity, demand time, defect quantity, region, module, etc., without limitation.

[0029] The statistical information of the above-mentioned requirement quantity dimension may include the total number of all requirements and the number of some requirements that meet the specified conditions, etc., without limitation. The statistical information of the above-mentioned requirement time dimension may include information obtained by counting the requirement submission date, requirement closing date, requirement resolution date, etc. (such as iteration cycle, requirement processing time, etc.), without limitation. The statistical information of the above-mentioned defect quantity dimension may include the total number of all defects and the number of some defects that meet the specified conditions, etc., without limitation. The statistical information of the above-mentioned region dimension may include relevant information on requirements, defects, etc. of each region counted by region, without limitation. The statistical information of the above-mentioned module dimension may include relevant information on requirements, defects, etc. of each module counted by module, without limitation.

[0030] Step S106, generating a data file including a function list and a test summary based on the preset configuration information, all acquired demand information, and statistical information of multiple dimensions.

[0031] The above-mentioned data file may refer to a file used to record all the data contents contained in the function list and the test summary. It may usually have a certain data structure to facilitate relevant personnel to view, process and perform other operations. The specific format can be determined according to actual needs and is not limited to this.

[0032] A test data processing method provided by an embodiment of the present invention obtains target demand information from a service platform based on preset query statements and preset configuration information; analyzes and counts all acquired demand information to obtain statistical information of multiple dimensions; generates a data file containing a function list and a test summary based on the preset configuration information, all acquired demand information, and statistical information of multiple dimensions. Using the above technology, it is possible to automatically analyze and count the demand information obtained from the service platform, and then automatically generate a data file containing a function list and a test summary, thereby alleviating the problem of high labor cost and low reliability in the prior art of conducting test summaries and writing function lists, and meeting the needs of rapid iterative release of software.

[0033] As a possible implementation, the preset query statement may include multiple preset fields and multiple preset regular expressions; based on this, the step S102 (i.e., obtaining the demand information of the target demand from the service platform based on the preset query statement and the preset configuration information) may include:

[0034] Step 1: Based on multiple preset fields and demand query conditions, demand identification information of the target demand is obtained from the service platform.

[0035] Step 2: Based on the demand identification information of the target demand, first information corresponding to the demand identification information of the target demand is obtained from the service platform.

[0036] Step 3, based on multiple preset fields and multiple preset regular expressions, obtain the region information, module information, requirement description information, requirement personnel information, defect information and time information of the target requirement from the first information.

[0037] As a possible implementation, the plurality of preset fields may include a preset first field representing the test task type, a preset second field representing the requirement description, a preset third field representing the requirement personnel, and a fourth field representing the requirement time. Based on this, the operation method of the above step 3 may include:

[0038] Step 31: Acquire target required region information and module information from the first information based on a preset first regular expression.

[0039] Step 32: Based on a preset second field and a preset second regular expression, obtain requirement description information of the target requirement from the first information.

[0040] Step 33: Based on the preset third field and the preset third regular expression, obtain the target demand's required personnel information from the first information.

[0041] Step 34: Based on the preset first field, defect information of the target requirement is obtained from the first information.

[0042] Step 35: Based on the preset fourth field, obtain the time information of the target requirement from the first information.

[0043] For ease of understanding, the operation of steps 1 to 3 above is described below by taking a specific application as an example.

[0044] In the case where the service platform uses Team Foundation Server (TFS), you can obtain the requirement list from TFS through the set WIQL (Work Item Query Language) and configuration information (including TFS account and password, requirement query conditions, file save path, etc.). Each requirement in the requirement list contains all the information that complies with TFS (i.e. requirement information). All the information obtained from TFS includes but is not limited to the following fields (represented by data dictionary data):

[0045] data['id'](requirement number);

[0046] data['fields']['System.Title'] (required title, including region and module);

[0047] data['fields']['Microsoft.VSTS.Common.ResolvedBy'](requirement resolver);

[0048] data['fields']['Microsoft.VSTS.Common.ClosedBy'](requirement closed by);

[0049] data['fields']['System.AssignedTo'](demand assigned person);

[0050] data['fields']['Microsoft.VSTS.Common.ResolvedDate'](requirement resolution date);

[0051] data['relations']['url'](test task link);

[0052] data['relations']['rel'](test task type);

[0053] data['fields']['Microsoft.VSTS.Common.Discipline'](requirement description).

[0054] You can obtain the required information by matching the above specific fields with regular expressions, including requirement number, requirement title, requirement resolution date, requirement description, bug information, etc. You can use the following operation methods:

[0055] (1) Traverse the field ['relations']['rel'] of the current requirement to extract the number after ' / ' in the field (that is, part of the value of the field) to obtain the requirement number, and then use the TFS API to extract the relevant information of the current requirement that matches the requirement number.

[0056] (2) Use the regular expression '.*?

(.*?)

[0057] (3) Traverse the current required field ['fields']['System.Description'] and use the string positioning method to intercept the string str1 after '[Tester Description]', and then use ' 'Split str1 to get a string list; traverse the obtained string list and use the regular expression '<.*? >' to match each string to find all html tags (starting with '<', ending with '>' and appearing in pairs) and remove them. After removing all html tags, the string with a length greater than 1 is the required description information (i.e., requirement description information).

[0058] (4) Match the fields ['fields']['Microsoft.VSTS.Common.ResolvedBy'] and ['fields']['Microsoft.VSTS.Common.ClosedBy'] respectively and use the regular expression '(.*?\)).*' to extract the developer information and tester information.

[0059] (5) Get the requirement information whose value of the field ['relations']['rel'] is System.LinkTypes.Hierarchy-Forward, and traverse this part of the requirement information to extract the relevant information that matches the input requirement number as bug information through the TFS API.

[0060] (6) Traverse all the fields ['fields']['System.Title'] of the bug information and extract the region information and module information by matching the regular expression '.*? [(.*?)].*'.

[0061] (7) Other required information is directly obtained through field matching. For the sake of brevity, this will not be elaborated here.

[0062] As a possible implementation, the above step S104 (i.e., analyzing and counting all acquired demand information to obtain statistical information in multiple dimensions) may include:

[0063] Step A1, statistically analyzing all acquired demand identification information to obtain the total number of demands.

[0064] Continuing with the previous example, after obtaining the demand information, the initial value of the total demand variable is set to 0. When traversing all the demand information, the value of the total demand variable is increased by 1 for each demand number traversed, until all the demand information is traversed and the value of the total demand variable is used as the total demand.

[0065] Step A2: Statistically analyze all acquired demand time information to obtain an iteration cycle.

[0066] Continuing with the previous example, the requirement submission date and closing date in all the requirement information obtained can be traversed to determine the earliest requirement submission date and the latest requirement closing date, and the time between the two can be calculated as the iteration cycle.

[0067] Step A3: Statistically analyze all acquired defect information to obtain the total number of defects.

[0068] Continuing with the previous example, after obtaining the bug information, the initial value of the total number of bugs variable is set to 0. When traversing all the bug information obtained, the value of the total number of bugs variable is increased by 1 for each requirement number traversed, until all the bug information is traversed and the value of the total number of bugs variable is used as the total number of bugs.

[0069] Step A4, statistically analyzing all acquired region information, all module information, all requirement identification information and all defect information, and obtaining the total number distribution of requirements and defects corresponding to regions and / or modules.

[0070] Continuing with the previous example, after the number of all bugs (ie, the total number of bugs) is counted in step A3, the requirement numbers of all bugs can be saved by region and module according to the region information and module information of each bug, so as to obtain and count relevant information in the next step.

[0071] Based on this, as an example, when performing step A4, a dictionary variable can be initialized, with the region and module as the key, the total number of requirements and the total number of bugs as the value, and the initial values ​​of the total number of requirements and the total number of bugs in the dictionary variable are both 0; then all the requirement information obtained is traversed, and the total number of requirements in the dictionary variable is increased by 1 each time the requirement of the corresponding region or the corresponding module is traversed, and the total number of bugs in the dictionary variable is increased by 1 each time the bug of the corresponding region or the corresponding module is traversed. According to this operation method, after traversing all the requirement information, all the key-value pairs of the dictionary variable can be extracted as the total number of requirements and the total number of bugs counted by region and module respectively. For example, the initialized dictionary variable is the statistical information {Ma'anshan: {total number of requirements: 0, number of bugs: 0}}. When traversing the demand information, if the current demand area traversed is Ma'anshan, the statistical information is updated to {Ma'anshan: {total number of requirements: 1, number of bugs: 0}}. If the current demand area traversed is Linfen, the statistical information is updated to {Ma'anshan: {total number of requirements: 0, number of bugs: 0}, Linfen: {total number of requirements: 1, number of bugs: 0}}. And so on. After traversing the demand information, the statistical information obtained includes the regional distribution of the total number of requirements and the number of bugs.

[0072] As another example, when performing step A4, another dictionary variable can be initialized. The dictionary variable uses "region-module" as the key, the number of bugs as the value, and the requirements as the array. Each requirement in the array stores its own requirement number, developer, tester and other information, and the initial value of the number of bugs in the dictionary variable is 0; then the array of the dictionary variable is traversed, and each time a bug of the corresponding module in the corresponding region is traversed, the number of bugs in the dictionary variable is increased by 1, and the requirement number of the requirement where the bug is located and its related required information are extracted. According to this operation method, after traversing the array, all key-value pairs of the dictionary variable can be extracted as the number of bugs counted by region and module, and the requirement number of the requirement where the bug is located and its related required information are obtained.

[0073] As a possible implementation, the above defect information may include defect priority information; the above multiple dimensions may also include defect priority; the above multiple preset fields may also include a preset fifth field representing the defect priority. Based on this, the operation method of the above step 3 may also include: based on the preset fifth field, obtaining defect priority information from the defect information. The above step S104 (i.e., analyzing and counting all the acquired demand information to obtain statistical information of multiple dimensions) may also include: performing statistical analysis on all the acquired regional information, all the module information and all the defect information to obtain the defect priority distribution of the total number of defects corresponding to the region and / or module.

[0074] Continuing with the previous example, after obtaining bug information through the TFS API, traverse all bug information to filter out bug information with the value of the field ['fields']['System.State'] being "closed" and / or "rejected", and then extract the value of the field ['fields']['Microsoft.VSTS.Common.Severity'] in the bug information retained after filtering as the bug priority and save it. When analyzing and counting all the required information obtained, you can first initialize a dictionary variable, which uses the region and module as the key and the number of bugs of each priority (i.e., severe, high, medium, low, and invalid) as the value, and the initial value of the number of bugs of each priority in the dictionary variable is 0; then traverse all the bug information obtained, and obtain the priority of each bug in the corresponding region or module traversed, and add 1 to the number of bugs of the priority. According to this operation method, after traversing all the bug information, all the key-value pairs of the dictionary variable can be extracted as the number of bugs of each priority counted by region and module. For example, the initialized dictionary variable is the statistical information {Region 1: {Severe: 0, High: 0, Medium: 0, Low: 0, Invalid: 0}, Region 2: {Severe: 0, High: 0, Medium: 0, Low: 0, Invalid: 0}, …}. If the region traversed to the current bug is Region 1 and the priority of the current bug is high, the statistical information is changed to {Region 1: {Severe: 0, High: 1, Medium: 0, Low: 0, Invalid: 0}, Region 2: {Severe: 0, High: 0, Medium: 0, Low: 0, Invalid: 0}, …}, and so on. The statistical information obtained after traversing the bug information includes the distribution of the number of bugs of each priority level counted by region.

[0075] As a possible implementation, the above step S106 (i.e., generating a data file containing a function list and a test summary based on preset configuration information, all acquired requirement information and statistical information of multiple dimensions) may include: filling all acquired requirement information and statistical information of multiple dimensions into a preset list template and a preset test summary template according to preset rules, and generating a function list and a test summary respectively; forming a data file of the function list and the test summary, and saving the data file to the above file saving path.

[0076] Continuing with the previous example, a function list template and a test summary template with a certain data structure (such as a table structure with rows and columns or other data structures) can be pre-established; after obtaining the demand information from TFS and obtaining the information analyzed and counted by this part of the demand information (referred to as analysis and statistics information), the various information required in the demand information and the analysis and statistics information can be filled into the function list template and the test summary template, and the filled function list template and the test summary template can be set up with relevant operations (such as information segmentation, adding titles, etc.), so as to obtain the function list and the test summary. For example Figure 2 , create an empty table page in advance, split "Release date, Requirement / BUG / Problem ID number, System, Proposed area, Module name, Upgrade content, Description, Developer, Tester, Submission date, Number of bugs (i.e. number of bugs), BUG level (i.e. priority of bugs)" into the title array of the function list by ',', set the header format, and thus obtain a function list template; after obtaining the above-mentioned requirement information and analysis and statistical information, the required various related information can be written into the table in turn for storage, thus obtaining a function list, the format of which can be referred to Figure 2 For example Figure 3 , create an empty table page in advance, and split "iteration number, total number of requirements, iteration cycle, whether it is released as planned, actual manpower / day invested in testing, number of requirement changes, number of delayed requirements & working hours, iteration responsible person" into an iteration summary array by ',' to set the title of the sub-table required for the iteration summary. Similarly, pre-set the titles of the sub-tables required for the bug summary, the module with a high bug ratio, and the region, and set the header format, so as to obtain a test summary template; after obtaining the above-mentioned requirement information and analysis and statistical information, the required various related information can be written into the table (i.e., multiple sub-tables) in sequence for storage, so as to obtain a test summary, the format of which can be referred to Figure 3 shown.

[0077] After obtaining the function list and the test summary, a data file having a data structure compatible with the function list and the test summary may be newly created, the function list and the test summary may be imported into the data file, and the data file may be saved to the above file saving path.

[0078] As a possible implementation, the preset configuration information may be pre-cached in a preset cache space. Based on this, before performing the above step S102 (i.e., obtaining the target demand information from the service platform based on the preset query statement and the preset configuration information), the above test data processing method may further include: obtaining the above preset configuration information from the preset cache space.

[0079] As a possible implementation method, before performing the above step S102 (i.e., obtaining the target demand information from the service platform based on the preset query statement and preset configuration information), the above test data processing method may also include: providing a configuration interface for the user to input the above configuration information; obtaining the above preset configuration information from the input information of the configuration interface.

[0080] For ease of understanding, the following is an illustrative description of the operation of automatically generating a function list and a test summary using a specific application as an example. Figure 4 As shown, the above automatic generation of function list and test summary can be performed as follows:

[0081] Step 01, check whether there is configuration information (such as TFS account and password, required query conditions, file save path, etc.) in the cache file; if it exists, read the configuration information directly from the cache and enter the configuration information into the interface (i.e., configuration interface); if it does not exist, open a new interface so that the user can enter the above configuration information through the interface, and store the configuration information entered through the interface into the cache file.

[0082] Step 02, set the address for connecting to TFS and the required path information in the configuration file.

[0083] In actual application, the above configuration file usually has a certain file format (such as ini file format, etc.). The above configuration information can be saved in the configuration file in the form of a string, and the configuration file is stored in a local file directory to facilitate automatic reading of the configuration information next time.

[0084] Step 03, obtain the requirement list from TFS through the set WIQL and configuration information.

[0085] Step 04, analyze and count all the information contained in the demand list to obtain the required analyzed and counted information.

[0086] The above statistical information may include: the total number of requirements, iteration cycle, total number of bugs, modules with a higher proportion of bugs, and the total number of requirements and number of bugs by region.

[0087] Step 05, save all the information contained in the requirements list and the analyzed and statistical information into an Excel table in a fixed format to generate a function list and test report.

[0088] To sum up the above, the above test data processing method can automatically generate a function list and test summary, reducing the pressure on testers to analyze, process and integrate scattered data in TFS query results, saving manpower costs, and ensuring the correctness of test data processing results. It avoids errors caused by manual analysis and processing of data, thereby meeting the needs of rapid iteration and release of software.

[0089] Based on the above test data processing method, the embodiment of the present invention also provides a test data processing device, see Figure 5 As shown, the device may include the following modules:

[0090] The acquisition module 502 is used to obtain the demand information of the target demand from the service platform based on the preset query statement and preset configuration information; wherein the preset configuration information includes the demand query condition and the file save path, and the demand information includes the demand identification information, the demand personnel information, the demand time information, the test task link information, the demand description information, the defect information, the region information and the module information.

[0091] The processing module 504 is used to analyze and count all the acquired demand information to obtain statistical information in multiple dimensions; wherein the multiple dimensions include demand quantity, demand time, defect quantity, region and module.

[0092] The generation module 506 is used to generate a data file including a function list and a test summary based on the preset configuration information, all the acquired requirement information and statistical information of multiple dimensions.

[0093] By using the above-mentioned test data processing device, the demand information obtained from the service platform can be automatically analyzed and counted, and then a data file containing a function list and a test summary can be automatically generated, thereby alleviating the problem of high labor cost and low reliability of the method of conducting test summaries and writing function lists in the prior art, and can meet the needs of rapid iteration and release of software.

[0094] The preset query statement may include multiple preset fields and multiple preset regular expressions. Based on this, the acquisition module 502 may also be used to: acquire the demand identification information of the target demand from the service platform based on the multiple preset fields and the demand query condition; acquire the first information corresponding to the demand identification information of the target demand from the service platform based on the demand identification information of the target demand; acquire the region information, module information, demand description information, demand personnel information, defect information and time information of the target demand from the first information based on the multiple preset fields and the multiple preset regular expressions.

[0095] The above-mentioned multiple preset fields may include a preset first field representing the test task type, a preset second field representing the requirement description, a preset third field representing the requirement personnel, and a fourth field representing the requirement time. Based on this, the above-mentioned acquisition module 502 can also be used to: obtain the region information and module information of the target requirement from the first information based on the preset first regular expression; obtain the requirement description information of the target requirement from the first information based on the preset second field and the preset second regular expression; obtain the requirement personnel information of the target requirement from the first information based on the preset third field and the preset third regular expression; obtain the defect information of the target requirement from the first information based on the preset first field; obtain the time information of the target requirement from the first information based on the preset fourth field.

[0096] The above-mentioned processing module 504 can also be used for: performing statistical analysis on all acquired requirement identification information to obtain the total number of requirements; performing statistical analysis on all acquired requirement time information to obtain the iteration cycle; performing statistical analysis on all acquired defect information to obtain the total number of defects; performing statistical analysis on all acquired region information, all module information, all requirement identification information and all defect information to obtain the total distribution of the total number of requirements and the total number of defects corresponding to the regions and / or modules.

[0097] The above-mentioned defect information may include defect priority information; the above-mentioned multiple dimensions may also include defect priority; the above-mentioned multiple preset fields may also include a preset fifth field representing the defect priority. Based on this, the above-mentioned acquisition module 502 may also be used to: obtain defect priority information from the defect information based on the preset fifth field. The above-mentioned processing module 504 may also be used to: perform statistical analysis on all the acquired regional information, all the module information and all the defect information to obtain the defect priority distribution of the total number of defects corresponding to the region and / or module.

[0098] The above-mentioned generation module 506 can also be used to: fill all the acquired demand information and statistical information of multiple dimensions into the preset list template and the preset test summary template according to preset rules, and generate a function list and a test summary respectively; form the function list and the test summary into the data file, and save the data file to the file save path.

[0099] The preset configuration information may be pre-cached in a preset cache space. Based on this, the acquisition module 502 may also be used to: acquire the preset configuration information from the preset cache space.

[0100] See also Figure 5 As shown, the device may also include:

[0101] The interface module 508 is used to provide a configuration interface for the user to input the configuration information.

[0102] The acquisition module 502 may also be used to: acquire the preset configuration information from input information of the configuration interface.

[0103] The test data processing device provided in the embodiment of the present invention has the same implementation principle and technical effects as those of the aforementioned test data processing method embodiment. For the sake of brief description, for matters not mentioned in the device embodiment, reference may be made to the corresponding contents in the aforementioned method embodiment.

[0104] The embodiment of the present invention further provides an electronic device, such as Figure 6 As shown, it is a schematic diagram of the structure of the electronic device, wherein the electronic device includes a processor 61 and a memory 60, the memory 60 stores computer executable instructions that can be executed by the processor 61, and the processor 61 executes the computer executable instructions to implement the above-mentioned test data processing method.

[0105] exist Figure 6 In the illustrated embodiment, the electronic device further includes a bus 62 and a communication interface 63 , wherein the processor 61 , the communication interface 63 and the memory 60 are connected via the bus 62 .

[0106] Among them, the memory 60 may include a high-speed random access memory (RAM), and may also include a non-volatile memory (non-volatile memory), such as at least one disk storage. The communication connection between the system network element and at least one other network element is realized through at least one communication interface 63 (which can be wired or wireless), and the Internet, wide area network, local area network, metropolitan area network, etc. can be used. The bus 62 can be an ISA (Industry Standard Architecture) bus, a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus, etc. The bus 62 can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 6 Only one bidirectional arrow is used in the diagram, but this does not mean that there is only one bus or only one type of bus.

[0107] The processor 61 may be an integrated circuit chip with signal processing capabilities. In the implementation process, each step of the above method can be completed by the hardware integrated logic circuit in the processor 61 or the instructions in the form of software. The above processor 61 can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it can also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor. The steps of the method disclosed in the embodiment of the present invention can be directly embodied as a hardware decoding processor to execute, or it can be executed by a combination of hardware and software modules in the decoding processor. The software module can be located in a mature storage medium in the field such as a random access memory, a flash memory, a read-only memory, a programmable read-only memory, or an electrically erasable programmable memory, a register, etc. The storage medium is located in the memory, and the processor 61 reads the information in the memory and completes the steps of the test data processing method of the above embodiment in combination with its hardware.

[0108] The computer program product of the test data processing method, device and electronic device provided in the embodiments of the present invention includes a computer-readable storage medium storing program code. The instructions included in the program code can be used to execute the test data processing method described in the previous method embodiment. The specific implementation can be found in the method embodiment and will not be repeated here.

[0109] Unless otherwise specifically stated, the relative steps, numerical expressions and values ​​of the components and steps set forth in these embodiments do not limit the scope of the present invention.

[0110] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a non-volatile computer-readable storage medium that is executable by a processor. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in each embodiment of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0111] In the description of the present invention, it should be noted that the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", etc., indicating the orientation or positional relationship, are based on the orientation or positional relationship shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, the terms "first", "second", and "third" are used for descriptive purposes only, and cannot be understood as indicating or implying relative importance.

[0112] Finally, it should be noted that the above-described embodiments are only specific implementations of the present invention, which are used to illustrate the technical solutions of the present invention, rather than to limit them. The protection scope of the present invention is not limited thereto. Although the present invention is described in detail with reference to the above-described embodiments, ordinary technicians in the field should understand that any technician familiar with the technical field can still modify the technical solutions recorded in the above-described embodiments within the technical scope disclosed by the present invention, or can easily think of changes, or make equivalent replacements for some of the technical features therein; and these modifications, changes or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.

Claims

1. A test data processing method, characterized in that: The method comprises: Based on the preset query statement and preset configuration information, the demand information of the target demand is obtained from the service platform; wherein the preset configuration information includes the demand query condition and the file saving path, and the demand information includes the demand identification information, the demand personnel information, the demand time information, the test task link information, the demand description information, the defect information, the region information and the module information; Analyze and count all acquired demand information to obtain statistical information in multiple dimensions; wherein the multiple dimensions include demand quantity, demand time, defect quantity, region and module; Based on the preset configuration information, all acquired requirement information and statistical information of multiple dimensions, a data file including a function list and a test summary is generated.

2. The method according to claim 1, characterized in that The preset query statement includes multiple preset fields and multiple preset regular expressions; Based on the preset query statement and preset configuration information, the target demand information is obtained from the service platform, including: Based on the multiple preset fields and the demand query condition, obtaining demand identification information of the target demand from the service platform; Based on the demand identification information of the target demand, obtaining first information corresponding to the demand identification information of the target demand from the service platform; Based on the multiple preset fields and the multiple preset regular expressions, the region information, module information, requirement description information, requirement personnel information, defect information and time information of the target requirement are obtained from the first information.

3. The method according to claim 2, characterized in that The plurality of preset fields include a preset first field representing a test task type, a preset second field representing a requirement description, a preset third field representing a requirement person, and a fourth field representing a requirement time; based on the plurality of preset fields and the plurality of preset regular expressions, obtaining region information, module information, requirement description information, requirement person information, defect information, and time information of a target requirement from the first information, including: Acquire target required region information and module information from the first information based on a preset first regular expression; Based on a preset second field and a preset second regular expression, acquiring requirement description information of the target requirement from the first information; Based on a preset third field and a preset third regular expression, obtaining the target demand's demand personnel information from the first information; Based on the preset first field, obtaining defect information of the target requirement from the first information; Based on the preset fourth field, time information of the target requirement is acquired from the first information.

4. The method according to claim 3, characterized in that Analyze and count all acquired demand information to obtain statistical information in multiple dimensions, including: Perform statistical analysis on all acquired demand identification information to obtain the total number of demands; Perform statistical analysis on all acquired demand time information to obtain the iteration cycle; Perform statistical analysis on all acquired defect information to obtain the total number of defects; Statistical analysis is performed on all acquired region information, all module information, all requirement identification information, and all defect information to obtain the total number distribution of the total number of requirements and the total number of defects corresponding to each region and / or module.

5. The method according to claim 4, characterized in that The defect information includes defect priority information; the multiple dimensions also include defect priority; the multiple preset fields also include a preset fifth field representing the defect priority; based on the multiple preset fields and the multiple preset regular expressions, the region information, module information, requirement description information, requirement personnel information, defect information and time information of the target requirement are obtained from the first information, and further includes: Based on the preset fifth field, obtaining defect priority information from the defect information; Analyze and count all acquired demand information to obtain statistical information in multiple dimensions, including: Statistical analysis is performed on all acquired region information, all module information, and all defect information to obtain defect priority distribution of the total number of defects corresponding to the region and / or module.

6. The method according to claim 1, characterized in that Based on the preset configuration information, all the acquired requirement information and the statistical information of multiple dimensions, a data file containing a function list and a test summary is generated, including: Fill all acquired demand information and statistical information of multiple dimensions into the preset checklist template and preset test summary template according to preset rules, and generate a function checklist and test summary respectively; The function list and the test summary are combined into the data file, and the data file is saved to the file saving path.

7. The method according to claim 1, characterized in that The preset configuration information is pre-cached in a preset cache space; Before obtaining the demand information of the target demand from the service platform based on the preset query statement and the preset configuration information, the method further includes: The preset configuration information is obtained from the preset cache space.

8. The method according to claim 1, characterized in that: Before obtaining the demand information of the target demand from the service platform based on the preset query statement and the preset configuration information, the method further includes: Providing a configuration interface for the user to input the configuration information; The preset configuration information is obtained from input information of the configuration interface.

9. A test data processing device, characterized in that: The device comprises: An acquisition module is used to acquire the demand information of the target demand from the service platform based on a preset query statement and preset configuration information; wherein the preset configuration information includes demand query conditions and file storage paths, and the demand information includes demand identification information, demand personnel information, demand time information, test task link information, demand description information, defect information, region information and module information; A processing module is used to analyze and count all acquired demand information to obtain statistical information in multiple dimensions; wherein the multiple dimensions include demand quantity, demand time, defect quantity, region and module; A generation module is used to generate a data file containing a function list and a test summary based on the preset configuration information, all the acquired requirement information and statistical information of multiple dimensions.

10. An electronic device, characterized in that: The invention comprises a processor and a memory, wherein the memory stores computer executable instructions that can be executed by the processor, and the processor executes the computer executable instructions to implement the method according to any one of claims 1 to 8.

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