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Creators/Authors contains: "Mansur, S_M_Hasan"

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  1. ; ; ; ; ; ; (, Proceedings of 12th International Conference on Mobile Software Engineering and Systems)
    Android User Interface (UI) testing has emerged as an important and prevalent research topic due to the ubiquity of apps and the unique challenges faced by developers in this software domain. One popular topic of research that aims to facilitate both manual and automated UI testing and debugging processes is record and replay (R&R) tools. These tools allow for the recording of UI actions to facilitate the execution of test scenarios and the replay of various types of bugs. R&R tools typically support three main settings: (i) UI regression testing via R&R of feature-based execution scenarios, (ii) R&R of non- crashing functional bugs (e.g., in crowdsourced settings), and (iii) R&R of crashing bugs. Despite the progress made in research related to R&R tools, prior work examined only the effectiveness of these tools in disparate or fragmented settings. As such, the research community currently lacks a comprehensive examination of the effectiveness of existing tools across their common use cases and the potential key limitations that emerge. We address this current gap in knowledge by conducting a thorough empirical study on using R&R tools to manually record and replay feature-based user scenarios, non-crashing failures, and crashing bugs. Additionally, we explore the possibility of using R&R tools in conjunction with automated input genera- tion (AIG) tools to automatically record and replay crashing bugs. Our study context includes one industrial and three academic R&R tools, 34 user scenarios from 17 apps, 90 non-crashing failures from 42 Android apps, and 31 crashing bugs from 17 Android apps. Our results illustrate that 17% of user scenarios, 38% of non-crashing failures, and 44% of crashing bugs are not able to be reliably recorded and replayed, with the most prevalent reasons for non-replayability being action interval resolution, incompatibility related to APIs, and limitations in Android tooling. Our findings reveal important research directions for R&R tools to facilitate their practical application and adoption. 
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    Free, publicly-accessible full text available April 4, 2026