Estimate the Precision of Defects Based on Reports Duplication in Crowdsourced Testing

Abstract

When analyzing the defects of crowdsourced testing, the testing reports need to be preprocessed, including removing duplicate and false positives. At present, most crowdsourced testing research focuses on duplication of the reports, which has achieved high accuracy. However, studies on reducing false positives of defects have rarely been conducted. Starting from the duplication of defects in the reports, this paper discusses the relationship between the duplication and the accuracy of defects and proposes an estimation approach based on the defect distribution in historical crowdsourced testing projects. Experiments have shown that our approach can provide a priori knowledge of defects and exhibits good stability. We applied this approach to the defect population estimation of crowdsourced testing. With better experimental results, our improved model is more accurate than the original model. We attempt to apply it to the estimation of the defect population of crowdsourced testing, which is more accurate than the original model.INDEX TERMS Precision of defect duplication; crowdsourced testing; a priori distribution of defect precision.

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“…Then, a quantitative quality score is assigned to the software-specific version, and the evaluation process is repeated after each considerable change in the current software version. Another area of research [49] claims that almost all previous techniques study the duplicated defects without false defects. Hence, this paper contributes by using duplicated defects to build a model which can provide a high estimation accuracy for valid defects.…”