Testing android applications using multi-objective evolutionary algorithms with a stopping criteria

Anshuman Rohella, Shingo Takada

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

The ever increasing usage of Android devices and apps has created a demand for faster and reliable testing techniques. While the quality of test cases can be summed up based on the amount of code they cover, fault detection in applications is one of the main objectives for testing. We introduce an Android app testing approach which uses multiobjective genetic algorithm with elitism which finds optimal test cases by minimizing their length, maximizes the code coverage and fault detection capability, and minimizes the whole test suite for re-usability. In addition to that, we also incorporate a progress indicator which checks for improvements in test suite quality after subsequent generations and use it as a stopping criterion. The effectiveness of our approach is shown in our evaluation where it is able to perform better than the existing state-of-The-Art tools.

Original languageEnglish
Title of host publicationProceedings - SEKE 2018
Subtitle of host publication30th International Conference on Software Engineering and Knowledge Engineering
PublisherKnowledge Systems Institute Graduate School
Pages308-313
Number of pages6
Volume2018-July
ISBN (Electronic)1891706446
Publication statusPublished - 2018 Jan 1
Event30th International Conference on Software Engineering and Knowledge Engineering, SEKE 2018 - Redwood City, United States
Duration: 2018 Jul 12018 Jul 3

Other

Other30th International Conference on Software Engineering and Knowledge Engineering, SEKE 2018
CountryUnited States
CityRedwood City
Period18/7/118/7/3

Keywords

  • Android Testing
  • Evolutionary Testing
  • Multi-Objective Testing

ASJC Scopus subject areas

  • Software

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  • Cite this

    Rohella, A., & Takada, S. (2018). Testing android applications using multi-objective evolutionary algorithms with a stopping criteria. In Proceedings - SEKE 2018: 30th International Conference on Software Engineering and Knowledge Engineering (Vol. 2018-July, pp. 308-313). Knowledge Systems Institute Graduate School.