Frameworks for performing on cloud automated software testing using swarm intelligence algorithm: Brief survey

Mohammad Hossain, Sameer O Abufardeh, Sumeet Kumar

    Research output: Contribution to journalArticlepeer-review

    Abstract

    This paper surveys on Cloud Based Automated Testing Software that is able to perform Black-box testing, White-box testing, as well as Unit and Integration Testing as a whole. In this paper, we discuss few of the available automated software testing frameworks on the cloud. These frameworks are found to be more efficient and cost effective because they execute test suites over a distributed cloud infrastructure. One of the framework effectiveness was attributed to having a module that accepts manual test cases from users and it prioritize them accordingly. Software testing, in general, accounts for as much as 50% of the total efforts of the software development project. To lessen the efforts, one the frameworks discussed in this paper used swarm intelligence algorithms. It uses the Ant Colony Algorithm for complete path coverage to minimize time and the Bee Colony Optimization (BCO) for regression testing to ensure backward compatibility.

    Original languageEnglish (US)
    Pages (from-to)252-256
    Number of pages5
    JournalAdvances in Science, Technology and Engineering Systems
    Volume3
    Issue number2
    DOIs
    StatePublished - 2018

    Bibliographical note

    Funding Information:
    Authors would like to thank the reviewers of this work for their help. This work was accomplished by the support of University of Minnesota Crookston.

    Keywords

    • Ant colony algorithm
    • Bee colony optimization
    • Cloud based testing
    • Swarm intelligence
    • Test case prioritization

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