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Currently, while software engineers write code for various modules, quite often, various types of errors - coding, logic, semantic, and others (most of which are not caught by compilation and other tools) get introduced. Some of these bugs…
This paper presents a comprehensive empirical analysis of security vulnerabilities in AI-generated code across public GitHub repositories. We collected and analyzed 7,703 files explicitly attributed to four major AI tools: ChatGPT…
Multimodal AI has the potential to significantly enhance document-understanding tasks, such as processing receipts, understanding workflows, extracting data from documents, and summarizing reports. Code generation tasks that require…
Microservice architectures provide an intuitive promise of high maintainability and evolvability due to loose coupling. However, these quality attributes are notably vulnerable to technical debt (TD). Few studies address TD in microservice…
Technical Debt occurs when development teams favour short-term operability over long-term stability. Since this places software maintainability at risk, technical debt requires early attention to avoid paying for accumulated interest. Most…
Modern software is developed under considerable time pressure, which implies that developers more often than not have to resort to compromises when it comes to code that is well written and code that just does the job. This has led over the…
Self-Admitted Technical Debt (SATD) refers to technical compromises explicitly admitted by developers in natural language artifacts such as code comments, commit messages, and issue trackers. Among its types, Architecture Technical Debt…
Open-source software serves as a foundation for the internet and the cyber supply chain, but its exploitation is becoming increasingly prevalent. While advances in vulnerability detection for OSS have been significant, prior research has…
Appropriate comments of code snippets provide insight for code functionality, which are helpful for program comprehension. However, due to the great cost of authoring with the comments, many code projects do not contain adequate comments.…
In software development, technical debt (TD) refers to suboptimal implementation choices made by the developers to meet urgent deadlines and limited resources, posing challenges for future maintenance. Self-Admitted Technical Debt (SATD) is…
Over the past years, deep learning methods allowed for new state-of-the-art results in ad-hoc information retrieval. However such methods usually require large amounts of annotated data to be effective. Since most standard ad-hoc…
Early identification of security issues in software development is vital to minimize their unanticipated impacts. Code review is a widely used manual analysis method that aims to uncover security issues along with other coding issues in…
The increasing complexity and volume of software systems have heightened the importance of identifying and mitigating security vulnerabilities. The existing software vulnerability datasets frequently fall short in providing comprehensive,…
Automated detection of vulnerability-fixing commits (VFCs) is critical for timely security patch deployment, as advisory databases lag patch releases by a median of 25 days and many fixes never receive advisories. We present a comprehensive…
[Background] In large open-source software projects, development knowledge is often fragmented across multiple artefacts and contributors such that individual stakeholders are generally unaware of the full breadth of the product features.…
Self-Admitted Technical Debt (SATD) is a metaphorical concept to describe the self-documented addition of technical debt to a software project in the form of source code comments. SATD can linger in projects and degrade source-code quality,…
This report focuses on enhancing a binary code comment quality classification model by integrating generated code and comment pairs, to improve model accuracy. The dataset comprises 9048 pairs of code and comments written in the C…
A central function of code review is to increase understanding; helping reviewers understand a code change aids in knowledge transfer and finding bugs. Comments in code largely serve a similar purpose, helping future readers understand the…
Static analysis tools are widely used to detect software bugs and vulnerabilities but often struggle with scalability and efficiency in complex codebases. Traditional approaches rely on manually crafted annotations -- labeling functions as…
Effective data management and sharing are critical success factors in industry-academia collaboration. This paper explores the motivations and lessons learned from publishing open data sets in such collaborations. Through a survey of…