An Evolutionary Approach to Adapt Tests Across Mobile Apps
This addresses the issue of generating meaningful tests for mobile app developers, but it is incremental as it builds on existing test adaptation methods.
The paper tackled the problem of automatic GUI test generators missing semantically relevant test cases by proposing ADAPTDROID, a technique that uses evolutionary testing to adapt GUI tests across similar Android apps, achieving successful adaptation in 11 out of 20 scenarios.
Automatic generators of GUI tests often fail to generate semantically relevant test cases, and thus miss important test scenarios. To address this issue, test adaptation techniques can be used to automatically generate semantically meaningful GUI tests from test cases of applications with similar functionalities. In this paper, we present ADAPTDROID, a technique that approaches the test adaptation problem as a search-problem, and uses evolutionary testing to adapt GUI tests (including oracles) across similar Android apps. In our evaluation with 32 popular Android apps, ADAPTDROID successfully adapted semantically relevant test cases in 11 out of 20 cross-app adaptation scenarios.