TutorialsASE 2024

Here are the ASE ’24 tutorials:

Title: Evaluating Fault Detection, Test Generation and Program Repair Techniques using BugSwarm

Authors: Hao-Nan Zhu (University of California, Davis), Robert M. Furth (University of California, Davis), Cindy Rubio-González (University of California, Davis)

Room: Gardenia

Date: November 1, 2024 (Friday)

Time: 8:30 AM - 12:00 PM (with coffee break)

ABSTRACT: Software defect datasets serve as benchmarks when evaluating software engineering techniques, including approaches for fault detection, test generation, and automated program repair. It is crucial for researchers to be aware of available benchmarks to make the best selection for their case scenario. The goal of this tutorial is to provide participants with a general overview of existing software defect datasets, and to showcase BugSwarm, a large-scale dataset of thousands of reproducible software defect artifacts. The tutorial will have a 60-minute lecture and 120-minute hands-on activities. The lecture will cover the main aspects of software defect datasets and discuss the design of BugSwarm. The hands-on activities will teach participants how to set up and use the BugSwarm API and client, and will provide examples on how to evaluate a sample of fault detection, test generation, and automated program repair tools using BugSwarm.

Title: Tutorial on Software Engineering for FMware

Authors Gopi Krishnan Rajbahadur (Centre for Software Excellence, Huawei, Canada), Filipe Roseiro Cogo (Centre for Software Excellence, Huawei), Dayi Lin (Centre for Software Excellence, Huawei Canada), Ahmed E. Hassan (Queen’s University)

Room: Magnolia

Date: October 28, 2024 (Monday)

Time: 1:30 PM - 4:30 PM

ABSTRACT: Foundation Models (FMs) like GPT-4 have spurred the development of FMware, a new class of software crafted with novel roles, assets, and paradigms. FMware finds extensive use in software engineering (SE) research for tasks such as test generation and in commercial products like GitHub Copilot, despite the inherent unpredictability of FMs. Our tutorial will explore cutting-edge research and practical approaches in crafting FMware. We emphasize a software engineering perspective over artificial intelligence (AI) to focus on SE challenges and opportunities, avoiding in-depth discussions of AI and mathematics unless they are essential.

Title: EZR: How to build understandable models\from data, simpler, smarter, faster

Author Tim Menzies (North Carolina State University)

Room: Camellia

Date: October 28, 2024 (Monday)

Time: 1:30 PM - 4:30 PM

ABSTRACT: Here, we use a "less is more" approach to create EZR, a simple, fast toolkit that can model complex problems with just a few data points (using incremental sampling). The approach supports classification, regression, optimization, fairness, explanation, data synthesis, privacy, compression, planning, monitoring, and runtime certification (but not generative tasks). For all these tasks, our minimal data usage simplifies model construction and verification. The lesson from all this work is not everything can be simplified, but many things can. When simplicity works, we should embrace it. Who can argue against that?

We illustrate EZR with 41 examples from the SE domain ranging from (a)~the control of software processes to (b)~controlling the models learned by AI tools to (c)~the configuration of video encoders. With EZR, certain tasks that were previously intimidating complex (e.g. hyperparameter optimization) are now practical, easy, and fast. All the materials used here are available on-line under and open-source license (BSD2). This content would be suitable for a one semester advanced SE graduate class on ``how to refactor AI to make modeling simpler''.

About

Call for Proposals

Tutorials address a wide range of mature topics from theoretical foundations to practical techniques and tools for automated software engineering. The general chair and organizers will decide the exact dates after all proposals have been reviewed and accepted. Tutorials are intended to provide scientific background on themes relevant to ASE’s research audience.

Instructors are invited to submit proposals for 1.5h, half-day (3h) and full-day (6h) tutorials and, upon selection, are required to provide tutorial notes on the topic of presentation in PDF. Tutorial proposals are limited to 2 pages.

Submission

Proposal submissions should include the following information: * Name and affiliation of the proposer/organizer (including e-mail address) * Name and affiliation of each additional instructor * Instructors’ experience in the area, including other tutorials, courses, etc. * Title, objective, abstract, and duration * Outline with approximate timings * Target audience, including the indication of level (novice, intermediate, expert) * Assumed background of attendees * Brief biography of each instructor (for later inclusion in publicity materials) * History of the tutorial (if it has been already presented; provide location, approximate attendance, etc.) * Audio-visual and technical requirements * Preferences for tutorial date, duration (1.5h, half-day or full-day), and any other scheduling constraints, with justification for full day (if a full day is proposed)

Proposals should be submitted at https://ase2024tutorials.hotcrp.com/.

All submissions must be in PDF format and conform, at time of submission, to the to the ACM Proceedings Template: https://www.acm.org/publications/proceedings-template. LaTeX users must use the \documentclass[sigconf,review,anonymous]{acmart} option.

Tutorial proposals will be reviewed by the ASE 2024 tutorial committee. Acceptance of the proposal will be based on the timeliness and expected interest in the topic and the potential for attracting a sufficient number of participants. Note that tutorials with too few registered attendees may be cancelled.

Accepted Proposals

The authors of the accepted proposals are expected to produce the advertisement materials by the deadline. The materials include the website, the program, the date and time, the basic required knowledge of the attendants of the tutorials, and any other advertisement materials.

Important dates:

• Deadline: June 7
• Proposal Notification: June 21
• Advertisement Material: July 7
• Final Notification: July 15
• Camera-ready: August 22