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07/24/2023
Refining ChatGPT-Generated Code: Characterizing and Mitigating Code Quality Issues
In this paper, we systematically study the quality of 4,066 ChatGPT-gene...
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07/14/2023
Ethics in the Age of AI: An Analysis of AI Practitioners' Awareness and Challenges
Ethics in AI has become a debated topic of public and expert discourse i...
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05/26/2023
AIBugHunter: A Practical Tool for Predicting, Classifying and Repairing Software Vulnerabilities
Many ML-based approaches have been proposed to automatically detect, loc...
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05/26/2023
Learning to Quantize Vulnerability Patterns and Match to Locate Statement-Level Vulnerabilities
Deep learning (DL) models have become increasingly popular in identifyin...
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02/20/2023
A3Test: Assertion-Augmented Automated Test Case Generation
Test case generation is an important activity, yet a time-consuming and ...
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02/19/2023
On the Reliability and Explainability of Automated Code Generation Approaches
Automatic code generation, the task of generating new code snippets from...
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02/13/2023
A Systematic Literature Review of Explainable AI for Software Engineering
Context: In recent years, leveraging machine learning (ML) techniques ha...
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11/23/2022
Explainable AI for Pre-Trained Code Models: What Do They Learn? When They Do Not Work?
In recent years, there has been a wide interest in designing deep neural...
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11/09/2022
Syntax-Aware On-the-Fly Code Completion
Code completion aims to help improve developers' productivity by suggest...
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09/20/2022
An Information-Theoretic and Contrastive Learning-based Approach for Identifying Code Statements Causing Software Vulnerability
Software vulnerabilities existing in a program or function of computer s...
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09/19/2022
Cross Project Software Vulnerability Detection via Domain Adaptation and Max-Margin Principle
Software vulnerabilities (SVs) have become a common, serious and crucial...
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09/15/2022
AutoUpdate: Automatically Recommend Code Updates for Android Apps
Android developers frequently update source code to improve the performa...
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09/02/2022
Explainable AI for Android Malware Detection: Towards Understanding Why the Models Perform So Well?
Machine learning (ML)-based Android malware detection has been one of th...
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06/20/2022
Ethics in AI through the Developer's Prism: A Socio-Technical Grounded Theory Literature Review and Guidelines
The term 'ethics' is widely used, explored, and debated in the context o...
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06/11/2022
Software Engineering in Australasia
Six months ago an important call was made for researchers globally to pr...
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03/12/2021
JITLine: A Simpler, Better, Faster, Finer-grained Just-In-Time Defect Prediction
A Just-In-Time (JIT) defect prediction model is a classifier to predict ...
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03/09/2021
Deep Learning for Android Malware Defenses: a Systematic Literature Review
Malicious applications (especially in the Android platform) are a seriou...
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02/24/2021
Practitioners' Perceptions of the Goals and Visual Explanations of Defect Prediction Models
Software defect prediction models are classifiers that are constructed f...
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02/19/2021
SQAPlanner: Generating Data-Informed Software Quality Improvement Plans
Software Quality Assurance (SQA) planning aims to define proactive plans...
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01/13/2021
Assessing the Students' Understanding and their Mistakes in Code Review Checklists – An Experience Report of 1,791 Code Review Checklist Questions from 394 Students
Code review is a widely-used practice in software development companies ...
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12/03/2020
Explainable AI for Software Engineering
Artificial Intelligence/Machine Learning techniques have been widely use...
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09/08/2020
Predicting Defective Lines Using a Model-Agnostic Technique
Defect prediction models are proposed to help a team prioritize source c...
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06/26/2018
AutoSpearman: Automatically Mitigating Correlated Metrics for Interpreting Defect Models
The interpretation of defect models heavily relies on software metrics t...
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06/20/2018
The Impact of IR-based Classifier Configuration on the Performance and the Effort of Method-Level Bug Localization
Context: IR-based bug localization is a classifier that assists develope...
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01/31/2018
The Impact of Correlated Metrics on Defect Models
Defect models are analytical models that are used to build empirical the...
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01/31/2018
The Impact of Automated Parameter Optimization on Defect Prediction Models
Defect prediction models---classifiers that identify defect-prone softwa...
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01/31/2018