Translating Video Recordings of Mobile App Usages into Replayable Scenarios

TL;DR

This paper presents V2S, an automated computer vision-based system that translates mobile app screen recordings into replayable scenarios, aiding developers in analyzing user interactions and reproducing bugs efficiently.

Contribution

V2S is a novel lightweight approach that converts Android app screen recordings into executable test scenarios using computer vision techniques, addressing challenges of analyzing graphical software artifacts.

Findings

V2S accurately replays approximately 89% of test scenarios from videos.

V2S can process 175 videos with 3,534 GUI actions effectively.

Case studies show potential usefulness for mobile developers.

Abstract

Screen recordings of mobile applications are easy to obtain and capture a wealth of information pertinent to software developers (e.g., bugs or feature requests), making them a popular mechanism for crowdsourced app feedback. Thus, these videos are becoming a common artifact that developers must manage. In light of unique mobile development constraints, including swift release cycles and rapidly evolving platforms, automated techniques for analyzing all types of rich software artifacts provide benefit to mobile developers. Unfortunately, automatically analyzing screen recordings presents serious challenges, due to their graphical nature, compared to other types of (textual) artifacts. To address these challenges, this paper introduces V2S, a lightweight, automated approach for translating video recordings of Android app usages into replayable scenarios. V2S is based primarily on computer vision techniques and adapts recent solutions for object detection and image classification to detect and classify user actions captured in a video, and convert these into a replayable test scenario. We performed an extensive evaluation of V2S involving 175 videos depicting 3,534 GUI-based actions collected from users exercising features and reproducing bugs from over 80 popular Android apps. Our results illustrate that V2S can accurately replay scenarios from screen recordings, and is capable of reproducing $\approx$ 89% of our collected videos with minimal overhead. A case study with three industrial partners illustrates the potential usefulness of V2S from the viewpoint of developers.