Cognition in Software Engineering: A Taxonomy and Survey of a Half-Century of Research

Abstract

Cognition plays a fundamental role in most software engineering activities. This article provides a taxonomy of cognitive concepts and a survey of the literature since the beginning of the Software Engineering discipline. The taxonomy comprises the top-level concepts of perception, attention, memory, cognitive load, reasoning, cognitive biases, knowledge, social cognition, cognitive control, and errors, and procedures to assess them both qualitatively and quantitatively. The taxonomy provides a useful tool to filter existing studies, classify new studies, and support researchers in getting familiar with a (sub) area. In the literature survey, we systematically collected and analysed 311 scientific papers spanning five decades and classified them using the cognitive concepts from the taxonomy. Our analysis shows that the most developed areas of research correspond to the four life-cycle stages, software requirements, design, construction, and maintenance. Most research is quantitative and focuses on knowledge, cognitive load, memory, and reasoning. Overall, the state of the art appears fragmented when viewed from the perspective of cognition. There is a lack of use of cognitive concepts that would represent a coherent picture of the cognitive processes active in specific tasks. Accordingly, we discuss the research gap in each cognitive concept and provide recommendations for future research.

Supplemental Material for Recognizing the known unknowns; the interaction between reflective thinking and optimism for uncertainty among software developer’s security perceptions.

“…Additionally, a systematic review (Mohanani et al, 2020) within software engineering points toward the breadth of biases affecting software (Fagerholm et al, 2022;Ralph, 2011). Our quantitative, datadriven study extends the understanding of heuristics and biases for secure software.…”

Recognizing the known unknowns; the interaction between reflective thinking and optimism for uncertainty among software developer’s security perceptions.

“…Additionally, a systematic review (Mohanani et al, 2020) within software engineering points toward the breadth of biases affecting software (Fagerholm et al, 2022;Ralph, 2011). Our quantitative, datadriven study extends the understanding of heuristics and biases for secure software.…”