Optimization of Web Service Testing Task Assignment in Crowdtesting Environment

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 o...

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Bibliographic Details
Published in:Journal of computer science and technology 2023-04, Vol.38 (2), p.455-470
Main Authors: Tang, Wen-Jun, Chen, Rong, Zhang, Jia-Li, Huang, Lin, Zheng, Sheng-Jie, Guo, Shi-Kai
Format: Article
Language:English
Subjects:
Algorithms
Artificial Intelligence
Computer Science
Crowdsourcing
Data Structures and Information Theory
Evolutionary algorithms
Evolutionary computation
Information Systems Applications (incl.Internet)
Optimization
Regular Paper
Social networks
Software Engineering
Synthetic data
Theory of Computation
Usability testing
Web services
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Summary: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.
ISSN:1000-9000
1860-4749
DOI:10.1007/s11390-022-0824-7