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The readability of source code is key for understanding and maintaining software systems and tests. Several studies investigate the readability of source code, but there is limited research on the readability of test code and related…
In spite of the growing importance of software security and the industry demand for more cyber security expertise in the workforce, the effect of security education and experience on the ability to assess complex software security problems…
To legitimize itself as a scientific discipline, the software engineering academic community must let go of its non-empirical dogmas. A dogma is belief held regardless of evidence. This paper analyzes the nature and detrimental effects of…
Hypothesis tests under order restrictions arise in a wide range of scientific applications. By exploiting inequality constraints, such tests can achieve substantial gains in power and interpretability. However, these gains come at a cost:…
Context: The Evidence-Based Software Engineering (EBSE) paradigm and the planning phase of a systematic literature review. Objective: A protocol to do a systematic literature review with detailed information about the processes suggested by…
Provenance-based Intrusion Detection Systems (PIDSes) have been widely used to detect Advanced Persistent Threats (APTs). Although many studies achieve high performance in the evaluations of their original papers, their performance in…
The Causal Roadmap outlines a systematic approach to asking and answering questions of cause-and-effect: define the quantity of interest, evaluate needed assumptions, conduct statistical estimation, and carefully interpret results. To…
Context: Conducting experiments is central to research machine learning research to benchmark, evaluate and compare learning algorithms. Consequently it is important we conduct reliable, trustworthy experiments. Objective: We investigate…
Software built on poor structural patterns often shows higher exposure to security defects. When code differs from established best practices, verification and maintenance become increasingly difficult, thereby raising the risk of…
In empirical software engineering (SE) research, researchers have considerable freedom to decide how to process data, what operationalizations to use, and which statistical model to fit. Gelman and Loken refer to this freedom as leading to…
The growing complexity of safety-relevant systems causes an increasing effort for safety assurance. The reduction of development costs and time-to-market, while guaranteeing safe operation, is therefore a major challenge. In order to enable…
Context: Software testing plays an essential role in product quality improvement. For this reason, several software testing models have been developed to support organizations. However, adoption of testing process models inside…
In this paper, a novel approach, Inforence, is proposed to isolate the suspicious codes that likely contain faults. Inforence employs a feature selection method, based on mutual information, to identify those bug-related statements that may…
Single-prompt accuracy is the dominant way to benchmark language models, but it can miss reliability failures that matter. We evaluate a 15-model open-weight corpus, with the main reliability analyses focused on 10 instruct models across…
Large language models (LLMs) are being increasingly adopted in the software engineering domain, yet the robustness of their grasp on core software design concepts remains unclear. We conduct an empirical study to systematically evaluate…
Program synthesis--the automated generation of executable code from high-level specifications--has been a central goal of computer science for over fifty years. This thesis provides a comparative literature review of the main paradigms that…
The identification of vulnerabilities is an important element in the software development life cycle to ensure the security of software. While vulnerability identification based on the source code is a well studied field, the identification…
Recent trends in the software engineering (i.e., Agile, DevOps) have shortened the development life-cycle limiting resources spent on security analysis of software designs. In this context, architecture models are (often manually) analyzed…
Testing is the most widely employed method to find vulnerabilities in real-world software programs. Compositional analysis, based on symbolic execution, is an automated testing method to find vulnerabilities in medium- to large-scale…
Code generation models are widely used in software development, yet their sensitivity to prompt phrasing remains under-examined. Identical requirements expressed with different emotions or communication styles can yield divergent outputs,…