Test Reuse Based on Adaptive Semantic Matching across Android Mobile Applications

TL;DR

This paper introduces TRASM, an adaptive semantic matching approach that enhances test reuse across Android apps by improving event matching accuracy and reducing test reuse failures and time.

Contribution

TRASM presents a novel adaptive strategy for semantic event matching, addressing limitations of previous methods and improving test reuse effectiveness across mobile applications.

Findings

Improves GUI event matching precision

Reduces test reuse failure rate

Decreases test reuse time

Abstract

Automatic test generation can help verify and develop the behavior of mobile applications. Test reuse based on semantic similarities between applications of the same category has been utilized to reduce the manual effort of Graphical User Interface (GUI) testing. However, most of the existing studies fail to solve the semantic problem of event matching, which leads to the failure of test reuse. To overcome this challenge, we propose TRASM (Test Reuse based on Adaptive Semantic Matching), a test reuse approach based on adaptive strategies to find a better event matching across android mobile applications. TRASM first performs GUI events deduplication on the initial test set obtained from test generation, and then employs an adaptive strategy to find better event matching, which enables reusing the existing test. Preliminary experiments with comparison to baseline methods on 15 applications demonstrate that TRASM can improve the precision of GUI event matching while reducing the failure of test reuse and the running time required for test reuse.