Environmental modeling for automated cloud application testing

Linghao Zhang, Xiaoxing Ma, Jian Lu, Tao Xie, Nikolai Tillmann, Peli De Halleux

Research output: Contribution to journalArticlepeer-review


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.

Original languageEnglish (US)
Article number6095493
Pages (from-to)30-35
Number of pages6
JournalIEEE Software
Issue number2
StatePublished - Mar 2012
Externally publishedYes


  • cloud computing
  • cloud environment model
  • dynamic symbolic execution
  • software engineering
  • software testing

ASJC Scopus subject areas

  • Software


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