Search-Based Test Generation Targeting Non-Functional Quality Attributes of Android Apps
Paper i proceeding, 2023
We propose a flexible multi-objective search-based test generation framework for interface testing of Android apps---STGFA-SMOG. This framework allows testers to target a variety of fitness functions, corresponding to different software quality attributes, code coverage, and other test case properties. We find that STGFA-SMOG outperforms random test generation in exposing potential quality issues and triggering crashes. Our study also offers insights on how different combinations of fitness functions can affect test generation for Android apps.
Software Quality
Search-Based Software Engineering
Automated Test Generation
Search-Based Test Generation
Quality Attributes
Författare
Teklit Berihu Gereziher
Student vid Chalmers
Selam Welu Gebrekrstos
Student vid Chalmers
Gregory Gay
Göteborgs universitet
GECCO '23: Proceedings of the Genetic and Evolutionary Computation Conference
9798400701191 (ISBN)
Porto, Portugal,
Context-Infused Automated Software Test Generation
Vetenskapsrådet (VR) (2019-05275), 2020-01-01 -- 2023-12-31.
Ämneskategorier
Programvaruteknik
Systemvetenskap
Datavetenskap (datalogi)
DOI
10.1145/3583131.3590449
ISBN
9798400701191