This program is tentative and subject to change.
Wed 10 Sep 2025 11:10 - 11:20 at Room TBD2 - Session 2 - Quality Assurance 1
Dala is a novel capability-based programming model that ensures data-race freedom while also supporting efficient inter-thread communication. While Dala has been designed to inform the design of future programming languages, the question arises whether existing languages can be retrofitted with Dala capabilities. We report such a design called JDala. In JDala, Dala capabilities are added to Java using annotations and interpreted using bytecode instrumentation. With some examples we demonstrate that by adding three simple annotations to the language, we can avoid concurrency bugs like deadlocks and unexpected program behaviour resulting from shallow immutability of Java standard library APIs. JDala demo: https://youtu.be/QddK1q35h-U
This program is tentative and subject to change.
Wed 10 SepDisplayed time zone: Auckland, Wellington change
Wed 10 Sep
Displayed time zone: Auckland, Wellington change
10:30 - 12:00 | Session 2 - Quality Assurance 1Tool Demonstration Track / Research Papers Track / Industry Track / NIER Track / Journal First Track at Room TBD2 | ||
10:30 15m | A Jump-Table-Agnostic Switch Recovery on ASTs Research Papers Track | ||
10:45 15m | Quantization Is Not a Dealbreaker: Empirical Insights from Large Code Models Research Papers Track Saima Afrin William & Mary, Antonio Mastropaolo William and Mary, USA, Bowen Xu North Carolina State University | ||
11:00 10m | AI-Powered Commit Explorer (APCE) Tool Demonstration Track Yousab Grees Belmont University, Polina Iaremchuk Belmont University, Ramtin Ehsani Drexel University, Esteban Parra Belmont University, Preetha Chatterjee Drexel University, USA, Sonia Haiduc Florida State University | ||
11:10 10m | JDala - A Simple Capability System for Java Tool Demonstration Track Quinten Smit Victoria University of Wellington, Jens Dietrich Victoria University of Wellington, Michael Homer Victoria University of Wellington, Andrew Fawcet Victoria University of Wellington, James Noble Independent. Wellington, NZ | ||
11:20 10m | ExpertCache: GPU-Efficient MoE Inference through Reinforcement Learning-Guided Expert Selection NIER Track Xunzhu Tang University of Luxembourg, Tiezhu Sun University of Luxembourg, Yewei Song University of Luxembourg, SiYuanMa , Jacques Klein University of Luxembourg, Tegawendé F. Bissyandé University of Luxembourg | ||
11:30 15m | Efficient Detection of Intermittent Job Failures Using Few-Shot Learning Industry Track Henri Aïdasso École de technologie supérieure (ÉTS), Francis Bordeleau École de Technologie Supérieure (ETS), Ali Tizghadam TELUS | ||
11:45 15m | LogOW: A Semi-Supervised Log Anomaly Detection Model in Open-World Setting Journal First Track Jingwei Ye Nankai University, Chunbo Liu Civil Aviation University of China, Zhaojun Gu Civil Aviation University of China, Zhikai Zhang Civil Aviation University of China, Xuying Meng The Institute of Computing Technology, Chinese Academy of Sciences, Weiyao Zhang The Institute of Computing Technology, Chinese Academy of Sciences, Yujun Zhang The Institute of Computing Technology, Chinese Academy of Sciences | ||