ICST 2024
Mon 27 - Fri 31 May 2024 Canada

The main theme of this workshop will be to foster an open dialogue between the community (i.e., academic and industrial researchers) related to how to best build a community infrastructure to support research on Android testing and analysis.

Just as mobile app developers face domain specific challenges, so do researchers working in this domain, including challenges such as

(1) the rapid evolution of mobile platforms and apps,

(2) the scale of data collection needed, particularly for supporting increasingly popular machine learning techniques, and

(3) the issues related to the reliability and usability of static and dynamic analysis tools.

The research community is in need of a shared infrastructure that can help support and accelerate research related to data collection and automated analysis for mobile apps. As such, the goal of this workshop will be to put together a comprehensive report that outlines the community needs around infrastructure and datasets for supporting research on mobile app testing and analysis.

Topics of the workshop will include, but are not limited to the following:

• Data that researchers need for testing-related and program analysis research for mobile apps.

• Automated tooling and infrastructure for conducting testing-related and program analysis research for mobile apps.

• Best practices for large-scale data collection efforts, and the practices required to maintain these datasets and keep them up to date.

• Infrastructure and tooling for static, dynamic, and security analysis of mobile apps.

• Best practices from practitioners for conducting research related to mobile app testing and analysis.

• Design requirements for the construction of a shared community infrastructure that supports research related to mobile app testing and analysis

Plenary
You're viewing the program in a time zone which is different from your device's time zone change time zone

Tue 28 May

Displayed time zone: Eastern Time (US & Canada) change

08:00 - 09:00
BreakfastSocial
08:00
60m
Other
Breakfast & Registration
Social

09:00 - 10:30
Opening & Academic KeynoteMODAL at Room 2
Chair(s): Wing Lam George Mason University
09:30
15m
Day opening
Welcome ceremony
MODAL

09:45
45m
Keynote
Keynote: Julia Rubin
MODAL
K: Julia Rubin University of British Columbia, S: Wing Lam George Mason University
11:00 - 12:30
Lightning Talks & Program Analysis PanelMODAL at Room 2
Chair(s): Kevin Moran University of Central Florida
11:00
45m
Talk
Lightning (5-10 min.) Talks - All Participants
MODAL

11:45
45m
Panel
Panel: Program Analysis for Mobile Apps
MODAL
Julia Rubin University of British Columbia, Safwat Hassan University of Toronto, Canada, Weiyi Shang University of Waterloo, Yousra Aafer Purdue University
14:00 - 15:30
Industry Keynote & Mobile Testing PanelMODAL at Room 2
Chair(s): Kevin Moran University of Central Florida
14:00
45m
Keynote
Keynote: Jiangfan Shi - Difficulties and Challenges of Mobile Testing in Industry
MODAL
Jiangfan Shi , S: Kevin Moran University of Central Florida
14:45
45m
Panel
Panel: Mobile Testing
MODAL
Jiangfan Shi , Mattia Fazzini University of Minnesota, Wenyu Wang University of Illinois Urbana-Champaign, Wing Lam George Mason University
16:00 - 17:30
Community Infrastructure Panel & ClosingMODAL at Room 2
Chair(s): Wing Lam George Mason University
16:00
45m
Panel
Panel: Community Dataset and Infrastructure
MODAL
August Shi The University of Texas at Austin, Kevin Moran University of Central Florida, Mei Nagappan University of Waterloo, Shin Yoo Korea Advanced Institute of Science and Technology
16:45
15m
Day closing
Closing discussions
MODAL

Call for Papers

Much of the research related to improving the quality of mobile apps, or automating mobile app development practices makes use of two major categories of artifacts:

(i) mobile application data (both static and dynamic) and

(ii) mobile application analysis techniques & tools.

For instance, a project related to automating mobile testing may aim to mine dynamic interaction traces for mobile apps to train a machine learning model for testing app UIs; conversely, security researchers may aim to use security-focused, static analysis tools that can analyze the complex event-driven nature of Android app code if the researchers wish to study the effectiveness of such tools. Unfortunately, past research on mobile app analysis, testing, and quality has used datasets and tools that have largely been created in an ad-hoc manner, leading to issues related to reproducibility and replicability, therefore hampering potential follow-up work on these topics.

Given the fragmentation around the development of datasets and research tooling related to mobile apps, this workshop aims to bring together researchers and practitioners to elicit design requirements related to building a shared infrastructure, and to provide a forum for sharing best practices for building complete, maintainable and open datasets and tools to support Android testing and analysis research.

We solicit short biographies (one to two paragraphs) and up to three representative papers (as PDF attachments or links) from researchers who would like to participate. The review and evaluation process will focus on whether the participant have the following experience:

(1) experience with mobile-related software engineering and testing,

(2) experience building research tools and datasets related to mobile apps, and

(3) experience publishing mobile testing and analysis research.

Submission biographies and representative papers will not be published in the proceedings and need not address all stated criteria, but they must address at least one of the aforementioned criteria.

Travel stipend of $500 USD to attend the workshop may be provided to those that make a submission.

All submissions should be sent to MODAL-Workshop-L@listserv.gmu.edu by March 27th, 2024 AOE April 29th, 2024 AOE.