Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/162613
Title: Automatically distilling storyboard with rich features for Android apps
Authors: Chen, Sen
Fan, Lingling
Chen, Chunyang
Liu, Yang
Keywords: Engineering::Computer science and engineering
Issue Date: 2022
Source: Chen, S., Fan, L., Chen, C. & Liu, Y. (2022). Automatically distilling storyboard with rich features for Android apps. IEEE Transactions On Software Engineering, 1-17. https://dx.doi.org/10.1109/TSE.2022.3159548
Journal: IEEE Transactions on Software Engineering
Abstract: Before developing a new mobile app, the development team usually endeavors painstaking efforts to review many existing apps with similar purposes. The review process is crucial in the sense that it reduces market risks and provides inspirations for app development. However, manual exploration of hundreds of existing apps by different roles (e.g., product manager, UI/UX designer, developer, and tester) can be ineffective. For example, it is difficult to completely explore all the functionalities of the app from different aspects including design, implementation, and testing in a short period of time. However, existing reverse engineering tools only provide basic features such as AndroidManifest.xml and Java source files for users. Following the conception of storyboard in movie production, we propose a system, named StoryDistiller, to automatically generate the storyboards for Android apps with rich features through reverse engineering, and assist different roles to review and analyze apps effectively and efficiently. Specifically, we (1) propose a hybrid method to extract a relatively complete Activity transition graph (ATG), that is, it first extracts the ATG of Android apps through static analysis method first, and further leverages dynamic component exploration to augment ATG; (2) extract the required inter-component communication (ICC) data of each target Activity by leveraging static data-flow analysis and renders UI pages dynamically by using app instrumentation together with the extracted required ICC data; (3) obtain rich features including comprehensive ATG with rendered UI pages, semantic activity names, corresponding logic and layout code, etc. (4) implement the storyboard visualization as a web service with the rendered UI pages and the corresponding rich features. Our experiments unveil that StoryDistiller is effective and indeed useful to assist app exploration and review. We also conduct a comprehensive comparison study to demonstrate better performance over IC3, Gator, Stoat, and StoryDroid.
URI: https://hdl.handle.net/10356/162613
ISSN: 0098-5589
DOI: 10.1109/TSE.2022.3159548
Rights: © 2021 IEEE. All rights reserved.
Fulltext Permission: none
Fulltext Availability: No Fulltext
Appears in Collections:SCSE Journal Articles

Page view(s)

7
Updated on Nov 26, 2022

Google ScholarTM

Check

Altmetric


Plumx

Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.