Related papers: An Empirically Evaluated Checklist for Surveys in …
Background: The need for empirical investigations in software engineering is growing. Many researchers nowadays, conduct and validate their solutions using empirical research. Survey is one empirical method which enables researchers to…
Context: Surveys constitute an valuable tool to capture a large-scale snapshot of the state of the practice. Apparently trivial to adopt, surveys hide, however, several pitfalls that might hinder rendering the result valid and, thus,…
Context: Systematic literature reviews (SLRs) have become standard practise as part of software engineering research, although their quality varies. To build on the reviews, both for future research and industry practice, they need to be of…
Background: Given the social aspects of Software Engineering (SE), in the last twenty years, researchers from the field started using research methods common in social sciences such as case study, ethnography, and grounded theory. More…
Context: Software testability is the degree to which a software system or a unit under test supports its own testing. To predict and improve software testability, a large number of techniques and metrics have been proposed by both…
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…
Background: Blog posts are frequently used by software practitioners to share information about their practice. Blog posts therefore provide a potential source of evidence for software engineering (SE) research. The use of blog posts as…
Software engineering research is evolving and papers are increasingly based on empirical data from a multitude of sources, using statistical tests to determine if and to what degree empirical evidence supports their hypotheses. To…
Systematic literature studies have received much attention in empirical software engineering in recent years. They have become a powerful tool to collect and structure reported knowledge in a systematic and reproducible way. We distinguish…
In this chapter, we provide advice on how to effectively teach survey research based on lessons learned from several international teaching experiences on the topic and from conducting large-scale surveys published at various scientific…
Background: Despite a long history, numerous laws and regulations, ethics remains an unnatural topic for many software engineering researchers. Poor research ethics may lead to mistrust of research results, lost funding and retraction of…
The experimental evaluation of the methods and concepts covered in software engineering has been increasingly valued. This value indicates the constant search for new forms of assessment and validation of the results obtained in Software…
Context: Software Engineering research makes use of collections of software artifacts (corpora) to derive empirical evidence from. Goal: To improve quality and reproducibility of research, we need to understand the characteristics of used…
While being an important and often used research method, survey research has been less often discussed on a methodological level in empirical software engineering than other types of research. This chapter compiles a set of important and…
Context: Empirical Software Engineering (ESE) drives innovation in SE through qualitative and quantitative studies. However, concerns about the correct application of empirical methodologies have existed since the 2006 Dagstuhl seminar on…
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…
Empirical software engineering is concerned with the design and analysis of empirical studies that include software products, processes, and resources. Optimization is a form of data analytics in support of human decision-making.…
Empirical methods like experimentation have become a powerful means to drive the field of software engineering by creating scientific evidence on software development, operation, and maintenance, but also by supporting practitioners in…
Context: Empirical Software Engineering (ESE) faces increasing challenges due to data scale, methodological complexity, and reproducibility concerns. Large Language Models (LLMs) have emerged as promising tools to support empirical…
Background: Research software is crucial for enabling research discoveries and supporting data analysis, simulation, and interpretation across domains. However, evolving requirements, complex inputs, and legacy dependencies hinder the…