3,458 papers · page 42 of 173
On open source software (OSS) platforms such as GitHub, forking and accepting pull-requests is an important approach for OSS projects to receive contributions, especially from external contributors who cannot directly commit into the source repositories. Having a large number of …
Automated code vulnerability detection has gained increasing attention in recent years. The deep learning (DL)-based methods, which implicitly learn vulnerable code patterns, have proven effective in vulnerability detection. The performance of DL-based methods usually relies on t…
Highly configurable systems enable customers to flexibly configure the systems in diverse deployment environments. The flexibility of configurations also poses challenges for performance testing. On one hand, there exist a massive number of possible configurations; while on the o…
Automated Program Repair (APR) aspires to automatically generate patches for an input buggy program. Traditional APR tools typically focus on specific bug types and fixes through the use of templates, heuristics, and formal specifications. However, these techniques are limited in…
Many open source projects provide good first issues (GFIs) to attract and retain newcomers. Although several automated GFI recommenders have been proposed, existing recommenders are limited to recommending generic GFIs without considering differences between individual newcomers.…
A physical simulation engine (PSE) is a software system that simulates physical environments and objects. Modern PSEs feature both forward and backward simulations, where the forward phase predicts the behavior of a simulated system, and the backward phase provides gradients (gui…
The widespread adoption of DNNs in NLP software has highlighted the need for robustness. Researchers proposed various automatic testing techniques for adversarial test cases. However, existing methods suffer from two limitations: weak error-discovering capabilities, with success …
Automated program repair (APR) approaches suffer from long patch validation time, which limits their practical application and receives relatively low attention. The patch validation process repeatedly executes tests to filter patches, and has been recognized as the dual of mutat…
Decompilation is a widely used process for reverse engineers to significantly enhance code readability by lifting assembly code to a higher-level C-like language, pseudo-code. Nevertheless, the process of compilation and stripping irreversibly discards high-level semantic informa…
The reuse and distribution of open-source software must be in compliance with its accompanying open-source license. In modern packaging ecosystems, maintaining such compliance is challenging because a package may have a complex multi-layered dependency graph with many packages, a…
AIoT (Artificial Intelligence of Things) which integrates AI and IoT has received rapidly growing interest from the software engineering community in recent years. It is crucial to design scalable, efficient, and reliable software solutions for large-scale AIoT systems in edge co…
Stack Overflow, the world's largest software Q&A (SQA) website, is facing a significant traffic drop due to the emergence of generative AI techniques. ChatGPT is banned by Stack Overflow after only 6 days from its release. The main reason provided by the official Stack Overflow i…
Modern software systems heavily rely on external libraries developed by third-parties to ensure efficient development. However, frequent library upgrades can lead to compatibility issues between the libraries and their client systems. In this paper, we introduce Compsuite, a data…
Automated program repair is to reduce the manual work for bug fixing by human developers. In recent 15 years, the research community of program repair has created many novel techniques. However, these techniques share several assumptions that cannot always be satisfied in daily s…
Static analysis tools have gained popularity among developers for finding potential bugs, but their widespread adoption is hindered by the accomnpanying high false alarm rates (up to 90%). To address this challenge, previous studies proposed the concept of actionable warnings, an…
Deep reinforcement learning (DRL) is increasingly applied in large-scale productions like Netflix and Facebook. As with most data-driven systems, DRL systems can exhibit undesirable behaviors due to environmental drifts, which often occur in constantly-changing production setting…
Code generation aims to generate source code implementing human requirements illustrated with natural language specifications. With the rapid development of intelligent software engineering, automated code generation has become a hot research topic in both artificial intelligence…
The template-based approach to invariant generation is a parametric and relatively complete methodology for inferring loop invariants. The relative completeness ensures the generated invariants' accuracy up to the template's form and the inductive condition. However, there has be…
Bug datasets are vital for enabling deep learning techniques to address software maintenance tasks related to bugs. However, existing bug datasets suffer from precise and scale limitations: they are either small-scale but precise with manual validation or large-scale but imprecis…
The recent fast development of quantum computers breaks several computation limitations that are difficult for conventional computers. Up to the present, although many approaches and tools have been proposed to test quantum programs, the fundamental features of quantum programs, …