Method and system for software testing management

Abstract

The invention discloses a software testing management method. The method includes the following steps: S1, dividing software testing data into a plurality of dimensions; S2, recording software testing data of any dimension, and classifying the records; S3, storing the software testing data in accordance with the classification of the records; and S4, conducting inquiries on the stored software testing data in accordance with the classification of the records. Correspondingly, the invention also discloses a software testing management system. The method and system of the invention record long-time accumulated testing work, classify and sort the testing work, provide inquires, and testing data can serve as data evidence for weekly statement, monthly statement, yearly statement, or graph derived from the inquiries can be directly used to analyze working content, work amount, and quality of testing versions of testing personnel.

Description

technical field [0001] The invention relates to the management field of software testing, in particular to a software testing management method and system. Background technique [0002] At present, mainstream software testing tools at home and abroad have many shortcomings in performance. In addition to high prices, their technical features cannot be used in mainstream enterprise-level testing environments, and the efficiency of traditional testing work is often unsatisfactory. The following scenarios often occur: 1) The submitted bugs only have bug scenarios, and it is difficult to trace the code, and the workload of locating the problem appears to be heavy; 2) The test data submitted by the testers to the test supervisor, project manager and other upper management is often artificial The test result table has no real data dependence. If there are fake elements, the product will often go online with problems; 3) It is difficult for traditional functional testers to share da...

AI Technical Summary

Problems solved by technology

[0002] At present, mainstream software testing tools at home and abroad have many shortcomings in performance. In addition to high prices, their technical features cannot be used in mainstream enterprise-level testing environments, and the efficiency of traditional testing work is often unsatisfactory. The following scenarios often occur: 1) The submitted bugs only have bug scenarios, and it is difficult to trace the code, and the workload of locating the problem appears to be heavy; 2) The test data submitted by the testers to the test supervisor, project manager and other upper management is often artificial The test result table has no real data dependence. If there are fake elements, the product will often go online with problems; 3) It is difficult for traditional functional testers to share data during the test process, and there is no real-time data of the overall test progress of the project. The work efficiency is very low; 4) When the project version is iterated, a large number of test cases of the previous version will be repeated, resulting in a large test cost; if the test cost is compromised, it is often artificially judged that the version iteration needs to add tests The focus of use cases and tests, such version iteration mode is prone to test blind spots; 5) If the enterprise outsources the test work of the project to other enterprises or test teams, it is difficult to control the test progress and test completeness, and then test Quality without a digital control

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