Publication Type

Conference Proceeding Article

Version

publishedVersion

Publication Date

10-2026

Abstract

Graphical user interface (GUI) tests are widely used in regression testing of mobile applications (apps) tovalidate app behavior from the user’s perspective. However, frequent app evolution, such as UI redesignsand feature updates, often renders existing GUI tests obsolete, even when underlying functionality remainsunchanged. Automatically repairing such tests is critical for maintaining test suites and reducing substantialmanual effort. Despite the practical importance, there is still a lack of a systematic understanding of thecharacteristics of obsolete GUI tests and a publicly available benchmark to support their study. To fill thisgap, we construct a benchmark comprising 736 obsolete GUI tests collected from 36 real-world mobileapps across 668 historical versions. We then conduct a large-scale empirical study that reveals two majorchallenges in repairing obsolete GUI tests: First, identifying the intended target widget is difficult becausewidget attributes are frequently missing or unstable, and visually similar widgets may correspond to differentfunctionalities. Second, the target widget is often no longer directly reachable from the failure state, as it maybe hidden behind additional UI interactions or relocated to another page. To address these challenges, wefurther propose GUIRevive, an automated GUI test repair approach that addresses semantic ambiguity inwidget identification and target unreachability under UI evolution by integrating semantic-aware reasoning,functionality-preserving validation, and goal-guided UI exploration. Our evaluation shows that GUIRevivesuccessfully repairs 86.4% of obsolete GUI tests and significantly outperforms state-of-the-art repair techniquesby up to 220%. Moreover, GUIRevive has been deployed in industrial settings, achieving a 93% repair successrate on industrial mobile apps.

Keywords

GUI test repair, Android applications, UI evolution, large language models

Discipline

Graphics and Human Computer Interfaces | Software Engineering

Research Areas

Software and Cyber-Physical Systems

Publication

Proceedings of the ACM on Software Engineering: ISSTA 2026, October 4-9, Oakland, CA

First Page

4789

Last Page

4810

Identifier

10.1145/3832300

Publisher

ACM

City or Country

New York

Comments

Awarded ACM SIGSOFT Distinguished Paper Award in 2026

Additional URL

https://doi.org/10.1145/3832300

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