Journal of Computer Science and Technology ›› 2023, Vol. 38 ›› Issue (2): 455-470.doi: 10.1007/s11390-022-0824-7

Special Issue: Software Systems; Computer Networks and Distributed Computing

• Regular Paper • Previous Articles    

Optimization of Web Service Testing Task Assignment in Crowdtesting Environment

Wen-Jun Tang (唐文君), Rong Chen* (陈 荣), Member, CCF, ACM, IEEE, Jia-Li Zhang (张佳丽), Lin Huang (黄 琳), Sheng-Jie Zheng (郑圣杰), and Shi-Kai Guo (郭世凯), Member, CCF   

  1. Information Science and Technology College, Dalian Maritime University, Dalian 116026, China
  • Received:2020-07-22 Revised:2022-11-30 Accepted:2022-12-23 Online:2023-05-10 Published:2023-05-10
  • Contact: Rong Chen
  • About author:Rong Chen received his M.S. and Ph.D. degrees in computer software and theory from Jilin University, Changchun, in 1997 and 2000, respectively. He is currently a professor of the Information Science and Technology College at the Dalian Maritime University, Dalian, and has previously held position at Sun Yat-sen University, Guangzhou. His research interests include software diagnosis, collective intelligence, activity recognition, Internet and mobile computing. He is a member of CCF, ACM and IEEE.
  • Supported by:
    This work was supported by the National Natural Science Foundation of China under Grant Nos. 61672122, 61902050 and 61602077, the Fundamental Research Funds for the Central Universities of China under Grant No. 3132019355, and the CERNET Innovation Project under Grant No. NGII20190627.

Crowdtesting has emerged as an attractive and economical testing paradigm that features testers from different countries, with various backgrounds and working conditions. Recent developments in crowdsourcing testing suggest that it is feasible to manage test populations and processes, but they are often outside the scope of standard testing theory. This paper explores how to allocate service-testing tasks to proper testers in an ever-changing crowdsourcing environment. We formalize it as an optimization problem with the objective to ensure the testing quality of the crowds, while considering influencing factors such as knowledge capability, the rewards, the network connections, and the geography and the skills required. To solve the proposed problem, we design a task assignment algorithm based on the Differential Evolution (DE) algorithm. Extensive experiments are conducted to evaluate the efficiency and effectiveness of the proposed algorithm in real and synthetic data, and the results show better performance compared with other heuristic-based algorithms.

Key words: crowdtesting; task assignment; web service testing; heuristic algorithm; optimization; quality of web service;

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