基于行为分析的移动应用众包测试人员画像方法研究
A Mobile Application Crowdsourced Testers Portrait Method Based on Behavior Analysis

由于移动应用众包测试的非契约和匿名性，使得移动应用测试发包方难以选择适合的众包测试人员。为此，试图依据历史测试数据，分析其测试经验、偏好、能力行为特征，构建众包测试人员的精确画像模型，帮助发包方选择适合的众包测试人员，保证测试质量。仿真实验结果验证了画像模型的正确性和有效性。
The mobile application crowdsourced test is non-contractua and anonymous. Therefore it is hard for its requester to select a suitable crowdsourced tester. To solve the problem, this paper uese histroical test data to analyze test experience,test perference and test ablity. Then it establishes a precise portrait model of the crowdsourced tester to help the requester to select the suitable crowdsourced tester and predict the test quality. The simulation results preliminarily verify the correctness and effectiveness of the portrait model