AIware 2024
Mon 15 - Tue 16 July 2024 Porto de Galinhas, Brazil, Brazil
co-located with FSE 2024
Dates
Tracks

This program is tentative and subject to change.

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Mon 15 Jul

Displayed time zone: Brasilia, Distrito Federal, Brazil change

09:00 - 10:30
Opening + Keynote1 + AIware VisionMain Track at Baobá 1
09:00
45m
Talk
Automatic Programming vs. Artificial Intelligence
Main Track
James Noble Independent. Wellington, NZ
DOI
09:45
45m
Talk
Towards AI for Software Systems
Main Track
Nafise Eskandani ABB Corporate Research Center, Guido Salvaneschi University of St. Gallen
DOI
11:00 - 12:30
Industry Talk1 + SE for AIwareMain Track at Baobá 1
11:00
45m
Talk
Function+Data Flow: A Framework to Specify Machine Learning Pipelines for Digital Twinning
Main Track
Eduardo de Conto Nanyang Technological University; CNRS@CREATE, Blaise Genest IPAL - CNRS - CNRS@CREATE, Arvind Easwaran Nanyang Technological University
DOI
11:45
45m
Talk
Green AI in Action: Strategic Model Selection for Ensembles in Production
Main Track
Nienke Nijkamp Delft University of Technology, June Sallou Delft University of Technology, Niels van der Heijden University of Amsterdam, Luís Cruz Delft University of Technology
DOI
14:00 - 15:30
Industry Talk2 + Human AI ConversationMain Track at Baobá 1
14:00
22m
Talk
Unveiling Assumptions: Exploring the Decisions of AI Chatbots and Human Testers
Main Track
Francisco Gomes de Oliveira Neto Chalmers | University of Gothenburg
DOI
14:22
22m
Talk
RUBICON: Rubric-Based Evaluation of Domain-Specific Human AI Conversations
Main Track
Param Biyani Microsoft, Yasharth Bajpai Microsoft, Arjun Radhakrishna Microsoft, Gustavo Soares Microsoft, Sumit Gulwani Microsoft
DOI
14:45
22m
Talk
From Human-to-Human to Human-to-Bot Conversations in Software Engineering
Main Track
Ranim Khojah Chalmers | University of Gothenburg, Francisco Gomes de Oliveira Neto Chalmers | University of Gothenburg, Philipp Leitner Chalmers | University of Gothenburg
DOI
15:07
22m
Talk
Unveiling the Potential of a Conversational Agent in Developer Support: Insights from Mozilla’s PDF.js Project
Main Track
João Correia PUC-Rio, Morgan C. Nicholson University of São Paulo, Daniel Coutinho Pontifical Catholic University of Rio de Janeiro (PUC-Rio), Caio Barbosa Pontifical Catholic University of Rio de Janeiro (PUC-Rio), Marco Castelluccio Mozilla, Marco Gerosa Northern Arizona University, Alessandro Garcia Pontifical Catholic University of Rio de Janeiro (PUC-Rio), Igor Steinmacher Northern Arizona University
DOI Pre-print
16:00 - 18:00
Security and Safety + Round Table + Day1 ClosingMain Track at Baobá 1
16:00
40m
Talk
A Case Study of LLM for Automated Vulnerability Repair: Assessing Impact of Reasoning and Patch Validation Feedback
Main Track
Ummay Kulsum North Carolina State University, Haotian Zhu Singapore Management University, Bowen Xu North Carolina State University, Marcelo d'Amorim North Carolina State University
DOI
16:40
40m
Talk
An AI System Evaluation Framework for Advancing AI Safety: Terminology, Taxonomy, Lifecycle Mapping
Main Track
Boming Xia CSIRO's Data61 & University of New South Wales, Qinghua Lu Data61, CSIRO, Liming Zhu CSIRO’s Data61, Zhenchang Xing CSIRO's Data61
DOI
17:20
40m
Talk
Measuring Impacts of Poisoning on Model Parameters and Embeddings for Large Language Models of Code
Main Track
Aftab Hussain University of Houston, Md Rafiqul Islam Rabin University of Houston, Amin Alipour University of Houston
DOI

Tue 16 Jul

Displayed time zone: Brasilia, Distrito Federal, Brazil change

09:00 - 10:30
Opening Day2 + Keynote2 + AIware for Domain-specific ApplicationsMain Track at Baobá 1
09:00
30m
Talk
Neuro-Symbolic Approach to Certified Scientific Software Synthesis
Main Track
Hamid Bagheri University of Nebraska-Lincoln, Mehdi Mirakhorli Rochester Institute of Technology, Mohamad Fazelnia University of Hawaii at Manoa, Ibrahim Mujhid University of Hawaii at Manoa, Md Rashedul Hasan University of Nebraska-Lincoln
DOI
09:30
30m
Talk
SolMover: Smart Contract Code Translation Based on Concepts
Main Track
Rabimba Karanjai University of Houston, Lei Xu Kent State University, Weidong Shi University of Houston
DOI
10:00
30m
Talk
The Art of Programming: Challenges in Generating Code for Creative Applications
Main Track
Michael Cook King’s College London
DOI
11:00 - 12:30
Industry Talk3 + AIware for CodeMain Track at Baobá 1
11:00
22m
Talk
A Transformer-Based Approach for Smart Invocation of Automatic Code Completion
Main Track
Aral de Moor Delft University of Technology, Arie van Deursen Delft University of Technology, Maliheh Izadi Delft University of Technology
DOI
11:22
22m
Talk
Chain of Targeted Verification Questions to Improve the Reliability of Code Generated by LLMs
Main Track
Sylvain Kouemo Ngassom Polytechnique Montréal, Arghavan Moradi Dakhel Polytechnique Montreal, Florian Tambon Polytechnique Montréal, Foutse Khomh Polytechnique Montréal
DOI
11:45
22m
Talk
Identifying the Factors That Influence Trust in AI Code Completion
Main Track
Adam Brown Google, Sarah D'Angelo Google, Ambar Murillo Google, Ciera Jaspan Google, Collin Green Google
DOI
12:07
22m
Talk
Leveraging Machine Learning for Optimal Object-Relational Database Mapping in Software Systems
Main Track
Sasan Azizian University of Nebraska-Lincoln, Elham Rastegari Creighton University, Hamid Bagheri University of Nebraska-Lincoln
DOI
14:00 - 15:30
Industry Talk4 + AIware for Software Lifecycle ActivitiesMain Track at Baobá 1
14:00
22m
Talk
A Comparative Analysis of Large Language Models for Code Documentation Generation
Main Track
Shubhang Shekhar Dvivedi IIIT Delhi, Vyshnav Vijay IIIT Delhi, Sai Leela Rahul Pujari IIIT Delhi, Shoumik Lodh IIIT Delhi, Dhruv Kumar Indraprastha Institute of Information Technology, Delhi
DOI
14:22
22m
Talk
AI-Assisted Assessment of Coding Practices in Modern Code Review
Main Track
Manushree Vijayvergiya Google, Malgorzata Salawa Google, Ivan Budiselic Google, Dan Zheng Google DeepMind, Pascal Lamblin Google, Marko Ivanković Google; Universität Passau, Juanjo Carin Google, Mateusz Lewko Google Inc, Jovan Andonov Google, Goran Petrović Google Inc, Danny Tarlow Google, Petros Maniatis Google DeepMind, René Just University of Washington
DOI
14:45
22m
Talk
Effectiveness of ChatGPT for Static Analysis: How Far Are We?
Main Track
Mohammad Mahdi Mohajer York University, Reem Aleithan York University, Canada, Nima Shiri Harzevili York University, Moshi Wei York University, Alvine Boaye Belle York University, Hung Viet Pham York University, Song Wang York University
DOI
15:07
22m
Talk
The Role of Generative AI in Software Development Productivity: A Pilot Case Study
Main Track
Mariana Coutinho CESAR School, Lorena Marques CESAR School, Anderson Santos CESAR School, Marcio Dahia CESAR School, Cesar França CESAR School, Ronnie de Souza Santos University of Calgary
DOI
16:00 - 18:00
Industry Talk5 + AIware challenge + Day2 ClosingChallenge Track at Baobá 1
16:00
40m
Talk
Automated Scheduling for Thematic Coherence in Conferences
Challenge Track
Mahzabeen Emu Queen’s University, Tasnim Ahmed Queen’s University, Salimur Choudhury Queen’s University
DOI
16:40
40m
Talk
Conference Program Scheduling using Genetic Algorithms
Challenge Track
Rucha Deshpande Purdue University, USA, Aishwarya Devi Akila Pandian Purdue University, Vigneshwaran Dharmalingam Purdue University
DOI
17:20
40m
Talk
Investigating the Potential of Using Large Language Models for Scheduling
Challenge Track
Deddy Jobson Mercari, Li Yilin Mercari
DOI

Call for Challenge Papers

Overview

The 1st ACM International Conference on AI-powered Software will host an AI-augmented software (AIware) challenge. The AIware Challenge brings together researchers and practitioners who are interested in applying, comparing, and challenging their AI-based tools and approaches to a particular community-focused problem. For 2024, the challenge will centre around the creation of an AIware to create the program (aka schedule) of a conference.

Program creation is the process of taking all the accepted papers to a conference and allocating a presentation slot for each paper with parallel sessions. The PC chairs of a conference typically do this manually. Sample programs from the MSR conference can be seen below. Some of the constraints that make the creation of a program challenging are as follows:

Constraints:

  1. Total time for all presentations in a session cannot be longer than the length of the session.
  2. Total number of sessions has to be equal to the number of sessions provided by the PC chairs.
  3. If there are parallel tracks, then no two papers with common authors can be scheduled in parallel at the same time

When these constraints are met, the PC chairs optimize for the papers in a session to be on a similar topic and work to avoid the parallel scheduling of sessions with related topics. The input data sources for the challenge comprise the number of conference sessions, the length of each session, the number of parallel tracks, and the accepted papers in a particular conference along with all the corresponding data: title, topics, abstract, paper, authors and allocated time for the presentation of each paper. Authors of the AIware challenge can collect any other data related to the papers or the authors of those papers that they deem as suitable.

Data

The authors of the AIware challenge can get this data from past MSR’s here:

MSR 2023 program
MSR 2022 Program

Participation

Participating in the challenge is straightforward:

  1. Extract the data from 2023 and 2022 MSR conferences for testing. Use any data that you may want for training.
  2. Build your AIware that solves the program creation problem.
  3. Gather the results - discuss the differences with the human-generated program. Are they better or worse and why do you think so?
  4. Write up and submit your 2-page challenge report

Since the data from MSR is common, authors are encouraged to collaborate by sharing the extracted data. To facilitate and encourage the sharing of extracted data and early results, a dedicated Slack channel has been created for this:

Paper Details

The challenge report describes the results of your work. The reports should cover the following aspects:

  • What data was used as input?
  • Which AI model was used?
  • How did you finetune or train the model?
  • What is the architecture of your AIware solution?
  • What prompts were used to query if any?
  • What data did you use for training?
  • What was your result - discuss the differences with the human-generated program of MSR 2023 and 2022.
  • Were any hard constraints broken?
  • Lessons learned and challenges in building such AIware?

Submission guidelines

Reports should be at most 2 pages long and in ACM 2-column format. See main track for more details.

Review and evaluation process

See main track for more details.

Awards

Attendees at AIware will select the winner of the best challenge submission.

Furthermore, we encourage all challenge participants to make their tools available for program chairs of future SE conferences to use.

Report submission is at:

https://aiware24challenge.hotcrp.com/

Important Dates

  • All dates are 23:59:59 AoE (UTC-12h).
  • Paper submission: Apr 10th, 2024
  • Paper notification: May 10th, 2024
  • Paper camera-ready: May 17th, 2024
  • Conference dates: July 15th-16th, 2024

For more details send email to: mei.nagappan@uwaterloo.ca, tianyi@purdue.edu