The Community for Technology Leaders
RSS Icon
Issue No.02 - March-April (2012 vol.29)
pp: 30-35
Xiaoxing Ma , Nanjing University
Jian Lu , Nanjing University
Tao Xie , North Carolina State University
Nikolai Tillmann , Microsoft Research
Peli de Halleux , Microsoft Research
Platforms such as Windows Azure let applications conduct data-intensive cloud computing. Unit testing can help ensure high-quality development of such applications, but the results depend on test inputs and the cloud environment's state. Manually providing various test inputs and cloud states is laborious and time-consuming. However, automated test generation must simulate various cloud states to achieve effective testing. To address this challenge, a proposed approach models the cloud environment and applies dynamic symbolic execution to generate test inputs and cloud states. Applying this approach to open-source Azure cloud applications shows that it can achieve high structural coverage.
cloud computing, software testing, dynamic symbolic execution, cloud environment model, software engineering
Xiaoxing Ma, Jian Lu, Tao Xie, Nikolai Tillmann, Peli de Halleux, "Environmental Modeling for Automated Cloud Application Testing", IEEE Software, vol.29, no. 2, pp. 30-35, March-April 2012, doi:10.1109/MS.2011.158
1. P. Godefroid, N. Klarlund, and K. Sen, "DART: Directed Automated Random Testing," Proc. 2005 ACM SIGPLAN Conf. Programming Language Design and Implementation (PLID 05), ACM, 2005, pp. 213–223.
40 ms
(Ver 2.0)

Marketing Automation Platform Marketing Automation Tool