55 citations
- University of LimerickIE12 papers
- Science Foundation IrelandIE5 papers
- University of LuxembourgLU3 papers
- University of OttawaCA3 papers
- The Open UniversityGB2 papers
- University of East LondonGB2 papers
- University of SheffieldGB2 papers
- Aalborg UniversityDK1 paper
- Concordia UniversityCA1 paper
- Huawei Technologies (China)CN1 paper
- IBM (Ireland)IE1 paper
- IBM Research - IrelandIE1 paper
15 papers
From Online User Feedback to Requirements: Evaluating Large Language Models for Classification and Specification Tasks
Manjeshwar Aniruddh Mallya, Alessio Ferrari, Mohammad Amin Zadenoori +1
[Context and Motivation] Online user feedback provides valuable information to support requirements engineering (RE). However, analyzing online user feedback is challenging due to…
Hallucination to Consensus: Multi-Agent LLMs for End-to-End JUnit Test Generation
Qinghua Xu, Guancheng Wang, Lionel Briand +1
Unit testing plays a critical role in ensuring software correctness. However, writing unit tests manually is labor-intensive, especially for strongly typed languages like Java, mot…
LLM meets ML: Data-efficient Anomaly Detection on Unstable Logs
Fatemeh Hadadi, Qinghua Xu, Domenico Bianculli +1
Most log-based anomaly detectors assume logs are stable, though logs are often unstable due to software or environmental changes. Anomaly detection on unstable logs (ULAD) is there…
Impact of Log Parsing on Deep Learning-Based Anomaly Detection
Zanis Ali Khan, Donghwan Shin, Domenico Bianculli +1
Software systems log massive amounts of data, recording important runtime information. Such logs are used, for example, for log-based anomaly detection, which aims to automatically…
Systematic Evaluation of Deep Learning Models for Log-based Failure Prediction
Fatemeh Hadadi, Joshua H. Dawes, Donghwan Shin +2
With the increasing complexity and scope of software systems, their dependability is crucial. The analysis of log data recorded during system execution can enable engineers to auto…
Motivation and Autonomy in Global Software Development: An Empirical Study
John Noll, Mohammad Abdur Razzak, Sarah Beecham
Distributed development involving globally distributed teams in different countries and timezones adds additional complexity into an already complex undertaking. This paper focuses…