Qualitative software engineering research: Reflections and guidelines

Review article, 2024

Researchers are increasingly recognizing the importance of human aspects in software development. Because qualitative methods are used to explore human behavior in-depth, we believe that studies using such methods will become more common. Existing qualitative software engineering guidelines do not cover the full breadth of qualitative methods and the knowledge on how to use them like in social sciences. The purpose of this study was to extend the software engineering community's current body of knowledge regarding available qualitative methods and their quality assurance frameworks and to provide recommendations and guidelines for their use. With the support of an epistemological argument and a survey of the literature, we suggest that future research would benefit from (1) utilizing a broader set of research methods, (2) more strongly emphasizing reflexivity, and (3) employing qualitative guidelines and quality criteria. We present an overview of three qualitative methods commonly used in social sciences but rarely seen in software engineering research, namely interpretative phenomenological analysis, narrative analysis, and discourse analysis. Furthermore, we discuss the meaning of reflexivity in relation to the software engineering context and suggest means of fostering it. Our paper will help software engineering researchers better select and then guide the application of a broader set of qualitative research methods. The behavioral and social sciences have an established history and research tradition to study human behavior, cognition, motivation, and affect quantitatively. To a fair extent, this expertise extends to qualitative research. We argue that qualitative software engineering research would greatly benefit from a knowledge transfer from these disciplines. We introduce (a) qualitative methods that are novel to software engineering, (b) new practices that enrich qualitative research in software engineering, and (c) quality assurance frameworks.