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Development of a human error taxonomy for software requirements: A systematic literature review
TLDR
The Human Error Taxonomy (HET) is developed by adding detailed error classes to Reason's well-known human error taxonomy of Slips, Lapses, and Mistakes by identifying and classifying human error identification. Expand
Effectiveness of Human Error Taxonomy during Requirements Inspection: An Empirical Investigation
TLDR
Results show that subjects using HET were not only more effective at detecting faults, but they found faults faster, and post-hoc analysis of HET revealed meaningful insights into the most commonly occurring human errors at different points during requirements development. Expand
Using a Cognitive Psychology Perspective on Errors to Improve Requirements Quality: An Empirical Investigation
TLDR
A newly developed Human Error Taxonomy (HET) and a formal Error-Abstraction and Inspection (EAI) process to improve fault detection performance of inspectors during the requirements inspection and provide useful insights into commonly occurring human errors that contributed to requirement faults are described. Expand
Defect Prevention in Requirements Using Human Error Information: An Empirical Study
TLDR
The results of this study show that a better understanding of human errors does lead developers to insert fewer problems into their own requirements documents, and indicate that different types of Human Error information have different impacts on fault prevention. Expand
Detection of Requirement Errors and Faults via a Human Error Taxonomy: A Feasibility Study
TLDR
The Human Error Taxonomy is effective for identifying and classifying requirements errors and faults, thereby helping to improve the overall quality of the SRS and the software. Expand
Using human error information for error prevention
TLDR
Evaluating whether understanding human errors contributes to the prevention of errors and concomitant faults during requirements engineering and identifying error prevention techniques used in industrial practice showed that the better a requirements engineer understands human errors, the fewer errors and Concomitant Fault makes when developing a new requirements document. Expand
Usefulness of a Human Error Identification Tool for Requirements Inspection: An Experience Report
TLDR
This empirical study investigates the effectiveness of a newly developed Human Error Abstraction Assist (HEAA) tool in helping inspectors identify human errors to guide the fault detection during the requirements inspection. Expand
Using Human Error Abstraction Method for Detecting and Classifying Requirements Errors: A Live Study
TLDR
It is hypothesize that inspections focused on identifying human errors are better at identifying requirements problems when compared to inspectionsfocused on faults, and the design and evaluation of the HEA method during the live study is discussed. Expand
Issues and Opportunities for Human Error-Based Requirements Inspections: An Exploratory Study
TLDR
The goal of the controlled study presented in this paper was to identify the specific tasks of EAI that inspectors find most difficult to perform and the strategies that successful inspectors use when performing the tasks. Expand
Error Abstraction Accuracy and Fixation during Error-Based Requirements Inspections
TLDR
The impact of an inspector's ability to accurately abstract human errors on their fault-detection effectiveness is investigated. Expand
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