Development of a human error taxonomy for software requirements: A systematic literature review

Background: Human-centric software engineering activities, such as requirements engineering, are prone to error. These human errors manifest as faults. To improve software quality, developers need methods to prevent and detect faults and their sources. Aims: Human error research from the field of cognitive psychology focuses on understanding and categorizing the fallibilities of human cognition. In this paper, we applied concepts from human error research to the problem of software quality. Method: We performed a systematic literature review of the software engineering and psychology literature to identify and classify human errors that occur during requirements engineering. Results: We developed the Human Error Taxonomy (HET) by adding detailed error classes to Reason's well-known human error taxonomy of Slips, Lapses, and Mistakes. Conclusion: The process of identifying and classifying human error identification provides a structured way to understand and prevent the human errors (and resulting faults) that occur during human-centric software engineering activities like requirements engineering. Software engineering can benefit from closer collaboration with cognitive psychology researchers.