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Effort estimation is a key factor for software project success, defined as delivering software of agreed quality and functionality within schedule and budget. Traditionally, effort estimation has been used for planning and tracking project…
Be it in debugging, testing, code review or, more recently, pair programming with AI assistance: in all these activities, software engineers need to understand source code. Accordingly, plenty of research is taking place in the field to…
Explainability is needed to establish confidence in machine learning results. Some explainable methods take a post hoc approach to explain the weights of machine learning models, others highlight areas of the input contributing to…
Measuring and evaluating software quality has become a fundamental task. Many models have been proposed to support stakeholders in dealing with software quality. However, in most cases, quality models do not fit perfectly for the target…
As software systems continue to grow in complexity, testing has become a fundamental part of ensuring the quality and reliability of software products. Yet, software testing is still often perceived, both in industry and academia, as a…
Software is among the most complex endeavors of the human mind; large scale systems can have tens of millions of lines of source code. However, seldom is complexity measured above the lowest level of code, and sometimes source code files or…
Scientific open-source software (Sci-OSS) projects are critical for advancing research, yet sustaining these projects long-term remains a major challenge. This paper explores the sustainability of Sci-OSS hosted on GitHub, focusing on two…
Machine learning (ML) models have been applied to a wide range of natural language processing (NLP) tasks in recent years. In addition to making accurate decisions, the necessity of understanding how models make their decisions has become…
Background: Research software plays an important role in solving real-life problems, empowering scientific innovations, and handling emergency situations. Therefore, the correctness and trustworthiness of research software are of absolute…
Software engineering activities in the Industry has come a long way with various improve- ments brought in various stages of the software development life cycle. The complexity of modern software, the commercial constraints and the…
Estimating the effort and quality of a system is a critical step at the beginning of every software project. It is necessary to have reliable ways of calculating these measures, and, it is even better when the calculation can be done as…
In this report we propose a solution to problem of the dependency on the experience of the software project quality assurance personnel by providing a transparent, objective and measurement based quality framework. The framework helps the…
Whenever an architect or a team of architects begins an architectural design, there are certain goals set to achieve. There are many factors involved in setting up goals for the architecture design such as type of the project, end user…
Context: Scientific open-source software (SciOSS) plays a foundational role in research and engineering, yet its long-term sustainability has often been overlooked and remains a significant concern. Objective: This study investigates the…
Software is now a vital scientific instrument, providing the tools for data collection and analysis across disciplines from bioinformatics and computational physics, to the humanities. The software used in research is often home-grown and…
A well-known approach for identifying defect-prone parts of software in order to focus testing is to use different kinds of product metrics such as size or complexity. Although this approach has been evaluated in many contexts, the question…
With the growing pervasiveness of artificial intelligence, the ability to explain the inferences made by machine learning models has become increasingly important. Numerous techniques for model explainability have been proposed, with…
Usability is an increasing concern in open source software (OSS). Given the recent changes in the OSS landscape, it is imperative to examine the OSS contributors' current valued factors, practices, and challenges concerning usability. We…
Accountability is an often called for property of technical systems. It is a requirement for algorithmic decision systems, autonomous cyber-physical systems, and for software systems in general. As a concept, accountability goes back to the…
Complex machine learning algorithms are used more and more often in critical tasks involving text data, leading to the development of interpretability methods. Among local methods, two families have emerged: those computing importance…