Using Human Error Abstraction Method for Detecting and Classifying Requirements Errors: A Live Study

1 Introduction Inspections, a proven quality improvement approach [3, 7], are a process where a team of skilled individuals review a software artifact (e.g., requirements specification document) to identify faults. Traditional fault-based software inspections (like Fault Checklist inspection) focus inspectors' attention on different type of faults (e.g., incorrect or incomplete or ambiguous requirements) [7]. Even a faithful application of validated fault-based techniques does not help inspectors in finding all faults. As a result, a larger part of (40%-50%) the development effort is spent fixing issues that should have been fixed in an earlier phase [3]. Hence, there is a real need to improve early fault detection and to help developers avoid the unnecessary rework. We hypothesize that inspections focused on identifying human errors (i.e., the underlying cause of faults) are better at identifying requirements problems when compared to inspections focused on faults (i.e., manifestation of human error). On those lines, our recent work [1, 5] uses a Cognitive Psychology perspective on human errors to improve the practice of requirements inspections. Human errors are understood as purely mental events, failings of human cognition in the process of problem solving, planning, and acting. Errors, in turn, will produce faults, a physical manifestation of the error. It is important that a clear distinction is made between human errors (mental events) vs program errors (related to coding or programmatic failures). To help inspectors in identifying human errors, the authors over the past two years, have worked on developing a Human Error Taxonomy (HET) that classifies human errors that commonly during requirements engineering [2]. Additionally, we have also developed a human error analysis framework called the Human Error Abstraction (HEA) method that can guide inspectors in analyzing and abstracting (i.e., extracting) human error information from requirements faults, a process referred to as Error Abstraction (EA) by Psychologists. Description of HET and HEA appears in Section 2. We recently carried out a series of empirical studies to validate the effectiveness of human error based inspections supported by HET against FC based inspection at two different sites [1, 5]. While the results were promising, the subjects did not have a supporting framework to assist them while abstracting errors from the faults. Analogous to human error investigation frameworks in Psychology, this paper discusses the design and evaluation of the HEA method during the live study.