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Background: Open source software has an increasing importance in modern software development. However, there is also a growing concern on the sustainability of such projects, which are usually managed by a small number of developers,…
GitHub Actions is a widely used platform to automate the build and deployment of software projects through configurable workflows. As the platform's popularity grows, it also becomes a target of choice for software supply chain attacks.…
The Software Engineering (SE) community has been embracing the open science policy and encouraging researchers to disclose artifacts in their publications. However, the status and trends of artifact practice and quality remain unclear,…
Reconstructing a method's change history efficiently and accurately is critical for many software engineering tasks, including maintenance, refactoring, and comprehension. Despite the availability of method history generation tools such as…
This article presents a free and open source toolkit that supports the semi-automated checking of research outputs (SACRO) for privacy disclosure within secure data environments. SACRO is a framework that applies best-practice…
Software debloating tools seek to improve program security and performance by removing unnecessary code, called bloat. While many techniques have been proposed, several barriers to their adoption have emerged. Namely, debloating tools are…
Several official statistics agencies release synthetic data as public use microdata files. In practice, synthetic data do not admit accurate results for every analysis. Thus, it is beneficial for agencies to provide users with feedback on…
Software clones have been an active area of research for the past two decades. However, although numerous clone detection tools are now available, only a small fraction of the literature has focused on tool evaluation, and this is in fact…
Attacks like Spectre abuse speculative execution, one of the key performance optimizations of modern CPUs. Recently, several testing tools have emerged to automatically detect speculative leaks in commercial (black-box) CPUs. However, the…
Large language models increasingly use external tools such as web search and document retrieval to solve information-intensive tasks. However, multi-hop tool use in complex tasks introduces substantial latency, since the model must…
In software development there is a constant pressure to produce code faster and faster without compromising on quality. New tools supporting developers are created in response to this demand. Currently a new generation of such solutions is…
Background. Developers use Automated Static Analysis Tools (ASATs) to control for potential quality issues in source code, including defects and technical debt. Tool vendors have devised quite a number of tools, which makes it harder for…
Measuring and evaluating source code similarity is a fundamental software engineering activity that embraces a broad range of applications, including but not limited to code recommendation, duplicate code, plagiarism, malware, and smell…
Release notes (RNs) summarize main changes between two consecutive software versions and serve as a central source of information when users upgrade software. While producing high quality RNs can be hard and poses a variety of challenges to…
Chaos engineering aims to improve the resilience of software systems by intentionally injecting faults to identify and address system weaknesses that cause outages in production environments. Although many tools for chaos engineering exist,…
The surge of research on fake news and misinformation in the aftermath of the 2016 election has led to a significant increase in publicly available source code repositories. Our study aims to systematically analyze and evaluate the most…
Software developed on public platform is a source of data that can be used to make predictions about those projects. While the individual developing activity may be random and hard to predict, the developing behavior on project level can be…
Spreadsheets are known to be error-prone. Over the last decade, research has been done to determine the causes of the high rate of errors in spreadsheets. This paper examines the added value of a spreadsheet tool (PerfectXL) that visualizes…
This report presents a comparative analysis of open-source vulnerability scanners for conversational large language models (LLMs). As LLMs become integral to various applications, they also present potential attack surfaces, exposed to…
Machine learning models are increasingly used for software security tasks. These models are commonly trained and evaluated on large Internet-derived datasets, which often contain duplicated or highly similar samples. When such samples are…