Research on Defect Priority Classification of Crowdsourcing Testing for Mobile Applications

Abstract

Crowdsourcing testing technology has developed in recent years with the development of software testing, which can speed up releasing cycle and improve the quality of testing. It is of great practical value to study the priority classification and cause analysis of defect reports by using the potential information of crowdsourcing test defect reports. This paper combines the research of mobile application crowdsourcing test defect report with machine learning data analysis technology, studies the priority classification of mobile application crowdsourcing test defect report, and then carries out defect cause analysis on the basis of defect priority classification. Defect classification is an intuitive reflection of defect research. This paper takes defect priority classification as the breakthrough point of defect report research, uses σ – AdaBoostSVM classification algorithm to classify defect reports, and then carries out cause analysis after defect report classification, which is conducive to the faster location and repair of defects. The experimental verification results demonstrate the effectiveness of the proposed method.