4,951 papers · page 11 of 248
Commit messages concisely describe code changes in natural language and are important for software maintenance. Several approaches have been proposed to automatically generate commit messages, but they still suffer from critical limitations, such as time-consuming training and po…
Many assisting exploration strategies have been proposed to assist grey-box fuzzers in exploring program states guarded by tight and complex branch conditions such as equality constraints. Although they have shown promising results in their original papers, their evaluations seld…
Pre-trained large deep learning models are now serving as the dominant component for downstream middleware users and have revolutionized the learning paradigm, replacing the traditional approach of training from scratch locally. To reduce development costs, developers often integ…
Large language models (LLMs) have achieved decent results on automated program repair (APR). However, the next token prediction training objective of decoder-only LLMs (e.g., GPT-4) is misaligned with the masked span prediction objective of current infilling-style methods, which …
Recent advances in Large Language Models (LLMs) have revolutionized code generation, leading to widespread adoption of AI coding tools by developers. However, LLMs can generate license-protected code without providing the necessary license information, leading to potential intell…
Several tasks in program analysis, verification, and testing are modeled as constraint solving problems, utilizing SMT solvers as the reasoning engine. In this work, we aim to investigate the reasoning capabilities of large language models (LLMs) toward reducing the size of an in…
Numerous machine learning (ML) models have been developed, including those for software engineering (SE) tasks, under the assumption that training and testing data come from the same distribution. However, training and testing distributions often differ, as training datasets rare…
The problem of software quality has motivated the development of a variety of techniques for Automatic Program Repair (APR). Meanwhile, recent advances in AI and Large Language Models (LLMs) have produced orders of magnitude performance improvements over previous code generation …
The rapid advancement of blockchain platforms has significantly accelerated the growth of decentralized applications (DApps). Similar to traditional applications, DApps integrate front-end descriptions that showcase their features to attract users, and back-end smart contracts fo…
Modern configurable systems provide tremendous opportunities for engineering future intelligent software systems. A key difficulty thereof is how to effectively self-adapt the configuration of a running system such that its performance (e.g., runtime and throughput) can be optimi…
Software defects heavily affect software's function-alities and may cause huge losses. Recently, many AI-based approaches have been proposed to detect defects, which can be divided into two categories: software defect prediction and automatic unit test generation. While these app…
The use of deep learning to achieve automated software vulnerability detection has been a longstanding interest within the software security community. These deep vulnerability detectors are mostly trained in a supervised manner, which heavily relies on large-scale, high-quality …
Deep Learning (DL) systems have been widely adopted across various industrial domains such as autonomous driving and intelligent healthcare. As with traditional software, DL systems also need to constantly evolve to meet ever-changing user requirements. However, ensuring the qual…
Over the past decade, the application of deep learning in code clone detection has produced remarkable results. However, the current approaches have two limitations: (a) code representation approaches with low information utilization, such as vanilla Abstract Syntax Tree (AST), l…
The rise of Large Language Models (LLMs) has streamlined frontend interface creation through tools like Vercel's v0, yet surfaced challenges in design quality (e.g., accessibility, and usability). Current solutions, often limited by their focus, generalisability, or data dependen…
Existing malicious code detection techniques demand the integration of multiple tools to detect different malware patterns, often suffering from high misclassification rates. Therefore, malicious code detection techniques could be enhanced by adopting advanced, more automated app…
Recent advances in quantum computing have sparked excitement that this new computing paradigm could solve previously intractable problems. However, due to the faulty nature of current quantum hardware and quantum-intrinsic noise, the full potential of quantum computing is still y…
Modern distributed software development relies on commits to control system versions. Commit classification plays a vital role in both industry and academia. The widely-used commit classification framework was proposed in 1976 by Swanson and includes three base classes: perfectiv…
Code snippet adaptation is a fundamental activity in the software development process. Unlike code generation, code snippet adaptation is not a “free creation”, which requires developers to tailor a given code snippet in order to fit specific requirements and the code context. Re…
Mobile accessibility is increasingly important nowadays as it enables people with disabilities to use mobile applications to perform daily tasks. Ensuring mobile accessibility not only benefits those with disabilities but also enhances the user experience for all users, making ap…