|
|
论文:2017,Vol:35,Issue(6):1083-1088 |
|
|
引用本文： |
|
|
安刚, 张涛, 成静. 基于行为分析的移动应用众包测试人员画像方法研究[J]. 西北工业大学学报 |
|
|
An Gang, Zhang Tao, Chen Jing. A Mobile Application Crowdsourced Testers Portrait Method Based on Behavior Analysis[J]. Northwestern polytechnical university |
|
|
|
|
|
|
|
| 基于行为分析的移动应用众包测试人员画像方法研究 |
|
| 安刚1, 张涛2, 成静3 |
|
1. 西安交通大学, 陕西 西安 710049;
2. 西北工业大学, 陕西 西安 710072;
3. 西安工业大学, 陕西 西安 710021 |
| 摘要: |
| 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。 |
| 关键词:
移动应用测试
众包测试
人员画像
行为分析
|
|
| A Mobile Application Crowdsourced Testers Portrait Method Based on Behavior Analysis |
|
| An Gang1, Zhang Tao2, Chen Jing3 |
|
1. Xi'an Jiaotong University, Xi'an 710049, China;
2. Xi'an Northwes Tern PolytechnIcal University, Xi'an 710072, China;
3. Xi'an Technological University, Xi'an 710021, China |
| Abstract: |
| 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. |
| Key words:
computer simulation
design of experiments
economic analysis
mathematical models
historical tetst data
behavior analysis
crowdsourced tester
matching of requester and tester
mobile application test
non-contractual anonymity
portrait model of tester
|
|
| 收稿日期: 2017-02-03
修回日期:
|
| DOI: |
| 基金项目: 陕西省科技攻关计划（2016GY-100）、航天科技支撑计划（2014HTXGD）、西安市科技计划、上海航天科技创新基金与航天支撑技术基金资助 |
| 通讯作者:
Email： |
| 作者简介: 安刚(1974-),西安交通大学博士研究生,主要从事移动计算、可信软件研究。
|
|
| 相关功能 |
|
|
|
|
| 作者相关文章 |
|
| 安刚 在本刊中的所有文章 |
| 张涛 在本刊中的所有文章 |
| 成静 在本刊中的所有文章 |
|
|
|
|
|
|
|
|
参考文献: |
|
|
[1] Tao C, Gao J. Modeling Mobile Application Test Platform and Environment:Testing Criteria and Complexity Analysis[C]//The Workshop on Joining Academia & Industry Contributions to Test Automation & Model-Based Testing, 2014:28-33
[2] Gao J, Bai X, Tsai W T, et al. Mobile Application Testing:A Tutorial[J]. IEEE Computer, 2014,47(2):46-55
[3] Guaiani F, Muccini H. Crowd and Laboratory Testing. Can They Co-Exist? An Exploratory Study[C]//Proceedings of the 2015 IEEE/ACM 2nd International Workshop on Crowd Sourcing in Software Engineering, 2015:32-37
[4] Wang J, Cui Q, Wang Q, et al. Towards Effectively Test Report Classification to Assist Crowdsourced Testing[C]//ACM/IEEE International Symposium on Empirical Software Engineering and Measurement, 2016:6
[5] Zhang T, Gao J, Cheng J. Crowdsourced Testing Services for Mobile apps[C]//Proceedings of the 2017 IEEE International Symposium on Service-Oriented System Engineering, 2017:132-137 |
|
|
|
|
|
|
|
