Crowdsourcing test task completion degree evaluation method and system

Abstract

The invention discloses a crowdsourcing test task completion degree evaluation method and system. The method comprises the following steps: obtaining a test cost element data set according to test process conditions; performing correlation analysis on the test manpower cost data set and the test report cost data set; obtaining a defect data set of a test report result, and selecting a corresponding modeling equation from a pre-constructed segmented reliability model framework based on the correlation degree of a test manpower cost data set and a test report cost data set according to a correlation analysis result, estimating parameters of the modeling equation by utilizing a least square and maximum likelihood estimation method based on the defect data set to obtain the total number of potential defects of the software; according to the actual detection defect number of the defect data set and the total number of the potential defects of the software, the detection defect coverage rate is obtained through calculation, and the task completion degree is evaluated. The method has the advantages that the quality of test software is guaranteed, waste of a large amount of test time and test resources can be avoided, and the overall performance of a crowdsourcing test platform is improved.

Description

technical field [0001] The invention relates to a task completion evaluation method, in particular to a crowdsourcing test task completion evaluation method. Background technique [0002] Crowdsourcing testing is an emerging testing method, and its working mode is usually that the crowdsourcing testing platform releases tasks to different test workers to complete within a specified time, and integrates and evaluates the workers' test reports after the test is completed. The unique advantages of this method, such as personnel diversity and complementarity, can greatly improve the efficiency of defect discovery. However, compared with traditional testing methods, this distributed testing method lacks scientific and reasonable task division and task allocation, and its testing process is also invisible. Therefore, the crowdsourcing testing platform cannot effectively monitor and manage the testing process. Managers often can only plan the end of crowdsourced testing tasks base...

AI Technical Summary

Problems solved by technology

[0004] Although the existing TE-based SRGM can estimate the number of potential defects, its research is mainly focused on the traditional software testing mode, and crowdsourcing testing is different from traditional testing methods because of the random diversity of its participants and testing methods. The large number of reports makes software products more reasonably and adequately tested. This large amount of manpower and reporting costs may lead to low-efficiency testing.

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