An Evolutionary Approach to Adapt Tests Across Mobile Apps

TL;DR

This paper introduces ADAPTDROID, an evolutionary testing technique that automatically adapts GUI tests across similar Android apps to generate semantically meaningful test cases, addressing limitations of existing test generators.

Contribution

It presents a novel evolutionary approach to test adaptation across mobile apps, improving the relevance of generated GUI tests compared to prior methods.

Findings

Successfully adapted tests in 11 out of 20 scenarios

Demonstrated effectiveness across 32 popular Android apps

Addresses semantic relevance in GUI test generation

Abstract

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.