Related papers: Sampling in Software Engineering Research: A Criti…
In the last 15 years, software architecture has emerged as an important software engineering field for managing the development and maintenance of large, software- intensive systems. Software architecture community has developed numerous…
Much of software engineering research focuses on tools, algorithms, and optimization of software. Recently, we, as a community, have come to acknowledge that there is a gap in meta-research and addressing the human-factors in software…
This note highlights the importance of investigating diversity aspects in combination in empirical research. It draws on the psychological discourse and suggests why and how software engineering scholars can use the aspect of diversity in…
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…
The heterogeneity in the organization of software engineering (SE) research historically exists, i.e., funded research model and hands-on model, which makes software engineering become a thriving interdisciplinary field in the last 50…
Software engineering (SE) research should be relevant to industrial practice. There have been regular discussions in the SE community on this issue since the 1980's, led by pioneers such as Robert Glass. As we recently passed the milestone…
Software Engineering and the implementation of software has become a challenging task as many tools, frameworks and languages must be orchestrated into one functioning piece. This complexity increases the need for testing and analysis…
We have been thinking about other aspects of software engineering for many years; the missing link in engineering software is the soft skills set, essential in the software development process. Although soft skills are among the most…
Context: Software engineering has a problem in that when we empirically evaluate competing prediction systems we obtain conflicting results. Objective: To reduce the inconsistency amongst validation study results and provide a more formal…
Context: Start-up companies have become an important supplier of innovation and software-intensive products. The flexibility and reactiveness of start-ups enables fast development and launch of innovative products. However, a majority of…
In empirical software engineering, benchmarks can be used for comparing different methods, techniques and tools. However, the recent ACM SIGSOFT Empirical Standards for Software Engineering Research do not include an explicit checklist for…
Software engineering (SE) is full of abstract concepts that are crucial for both researchers and practitioners, such as programming experience, team productivity, code comprehension, and system security. Secondary studies aimed at…
Background: Research software is software developed by and/or used by researchers, across a wide variety of domains, to perform their research. Because of the complexity of research software, developers cannot conduct exhaustive testing. As…
Background: The development of scientific software applications is far from trivial, due to the constant increase in the necessary complexity of these applications, their increasing size, and their need for intensive maintenance and reuse.…
Reliable empirical models such as those used in software effort estimation or defect prediction are inherently dependent on the data from which they are built. As demands for process and product improvement continue to grow, the quality of…
In recent years, quantum, quantum-inspired, and hybrid algorithms are increasingly showing promise for solving software engineering optimization problems. However, best-intended practices for conducting empirical studies have not yet well…
This paper reviews existing work in software engineering that applies statistical causal inference methods. These methods aim at estimating causal effects from observational data. The review covers 32 papers published between 2010 and 2022.…
Software engineers are responsible for developing, maintaining, and innovating software. To hire software engineers, organizations employ a tech hiring pipeline. This process typically consists of a series of steps to evaluate the extent to…
While experimental reproduction remains a pillar of the scientific method, we observe that the software best practices supporting the reproduction of machine learning ( ML ) research are often undervalued or overlooked, leading both to poor…
Statistics comes in two main flavors: frequentist and Bayesian. For historical and technical reasons, frequentist statistics have traditionally dominated empirical data analysis, and certainly remain prevalent in empirical software…