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08/10/2023
A Preliminary Evaluation of LLM-Based Fault Localization
Large Language Models (LLMs) have shown a surprising level of performanc...
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06/08/2023
Towards Autonomous Testing Agents via Conversational Large Language Models
Software testing is an important part of the development cycle, yet it r...
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06/04/2023
Learning Test-Mutant Relationship for Accurate Fault Localisation
Context: Automated fault localisation aims to assist developers in the t...
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04/19/2023
Towards Objective-Tailored Genetic Improvement Through Large Language Models
While Genetic Improvement (GI) is a useful paradigm to improve functiona...
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04/05/2023
Explainable Automated Debugging via Large Language Model-driven Scientific Debugging
Automated debugging techniques have the potential to reduce developer ef...
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03/01/2023
The Inversive Relationship Between Bugs and Patches: An Empirical Study
Software bugs pose an ever-present concern for developers, and patching ...
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01/27/2023
Repairing DNN Architecture: Are We There Yet?
As Deep Neural Networks (DNNs) are rapidly being adopted within large so...
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12/28/2022
A Bayesian Framework for Automated Debugging
Debugging takes up a significant portion of developer time. As a result,...
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12/13/2022
Fonte: Finding Bug Inducing Commits from Failures
A Bug Inducing Commit (BIC) is a commit that introduces a software bug i...
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09/23/2022
Large Language Models are Few-shot Testers: Exploring LLM-based General Bug Reproduction
Many automated test generation techniques have been developed to aid dev...
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04/14/2022
GLAD: Neural Predicate Synthesis to Repair Omission Faults
Existing template and learning-based APR tools have successfully found p...
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08/10/2021
Searching for Multi-Fault Programs in Defects4J
Defects4J has enabled numerous software testing and debugging research w...
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04/22/2021
Effectively Sampling Higher Order Mutants Using Causal Effect
Higher Order Mutation (HOM) has been proposed to avoid equivalent mutant...
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04/22/2021
Predictive Mutation Analysis via Natural Language Channel in Source Code
Mutation analysis can provide valuable insights into both System Under T...
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04/21/2021
Improving Test Distance for Failure Clustering with Hypergraph Modelling
Automated debugging techniques, such as Fault Localisation (FL) or Autom...
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04/19/2021
Causal Program Dependence Analysis
We introduce Causal Program Dependence Analysis (CPDA), a dynamic depend...
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04/14/2021
Human-in-the-Loop Fault Localisation Using Efficient Test Prioritisation of Generated Tests
Many existing fault localisation techniques become less effective or eve...
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05/29/2020
Reducing DNN Labelling Cost using Surprise Adequacy: An Industrial Case Study for Autonomous Driving
Deep Neural Networks (DNNs) are rapidly being adopted by the automotive ...
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05/19/2020
SINVAD: Search-based Image Space Navigation for DNN Image Classifier Test Input Generation
The testing of Deep Neural Networks (DNNs) has become increasingly impor...
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05/03/2020
Pandemic Programming: How COVID-19 affects software developers and how their organizations can help
Context. As a novel coronavirus swept the world in early 2020, thousands...
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12/28/2019
Search Based Repair of Deep Neural Networks
Deep Neural Networks (DNNs) are being adopted in various domains, includ...
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02/26/2019
Amortising the Cost of Mutation Based Fault Localisation using Statistical Inference
Mutation analysis can effectively capture the dependency between source ...
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08/25/2018
Guiding Deep Learning System Testing using Surprise Adequacy
Deep Learning (DL) systems are rapidly being adopted in safety and secur...
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12/08/2017
Mining Fix Patterns for FindBugs Violations
In this paper, we first collect and track large-scale fixed and unfixed ...
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09/14/2017
