Detection of Requirement Errors and Faults via a Human Error Taxonomy

A Feasibility Study

Wenhua Hu, Jeffrey C. Carver, Vaibhav Anu, Gursimran S. Walia, Gary Bradshaw

Research output: Chapter in Book/Report/Conference proceedingConference contributionResearchpeer-review

7 Citations (Scopus)

Abstract

Background: Developing correct software requirements is important for overall software quality. Most existing quality improvement approaches focus on detection and removal of faults (i.e. problems recorded in a document) as opposed identifying the underlying errors that produced those faults. Accordingly, developers are likely to make the same errors in the future and fail to recognize other existing faults with the same origins. Therefore, we have created a Human Error Taxonomy (HET) to help software engineers improve their software requirement specification (SRS) documents. Aims: The goal of this paper is to analyze whether the HET is useful for classifying errors and for guiding developers to find additional faults. Methods: We conducted a empirical study in a classroom setting to evaluate the usefulness and feasibility of the HET. Results: First, software developers were able to employ error categories in the HET to identify and classify the underlying sources of faults identified during the inspection of SRS documents. Second, developers were able to use that information to detect additional faults that had gone unnoticed during the initial inspection. Finally, the participants had a positive impression about the usefulness of the HET. Conclusions: The HET is effective for identifying and classifying requirements errors and faults, thereby helping to improve the overall quality of the SRS and the software.

Original languageEnglish
Title of host publication10th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement, ESEM 2016
PublisherIEEE Computer Society
ISBN (Electronic)9781450344272
DOIs
StatePublished - 8 Sep 2016
Event10th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement, ESEM 2016 - Ciudad Real, Spain
Duration: 8 Sep 20169 Sep 2016

Publication series

NameInternational Symposium on Empirical Software Engineering and Measurement
Volume08-09-September-2016
ISSN (Print)1949-3770
ISSN (Electronic)1949-3789

Conference

Conference10th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement, ESEM 2016
CountrySpain
CityCiudad Real
Period8/09/169/09/16

Fingerprint

Taxonomies
Specifications
Inspection
Information use
Engineers

Keywords

  • Human Errors
  • Software Quality Improvement
  • Software Requirements

Cite this

Hu, W., Carver, J. C., Anu, V., Walia, G. S., & Bradshaw, G. (2016). Detection of Requirement Errors and Faults via a Human Error Taxonomy: A Feasibility Study. In 10th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement, ESEM 2016 [a30] (International Symposium on Empirical Software Engineering and Measurement; Vol. 08-09-September-2016). IEEE Computer Society. https://doi.org/10.1145/2961111.2962596
Hu, Wenhua ; Carver, Jeffrey C. ; Anu, Vaibhav ; Walia, Gursimran S. ; Bradshaw, Gary. / Detection of Requirement Errors and Faults via a Human Error Taxonomy : A Feasibility Study. 10th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement, ESEM 2016. IEEE Computer Society, 2016. (International Symposium on Empirical Software Engineering and Measurement).
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Hu, W, Carver, JC, Anu, V, Walia, GS & Bradshaw, G 2016, Detection of Requirement Errors and Faults via a Human Error Taxonomy: A Feasibility Study. in 10th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement, ESEM 2016., a30, International Symposium on Empirical Software Engineering and Measurement, vol. 08-09-September-2016, IEEE Computer Society, 10th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement, ESEM 2016, Ciudad Real, Spain, 8/09/16. https://doi.org/10.1145/2961111.2962596

Detection of Requirement Errors and Faults via a Human Error Taxonomy : A Feasibility Study. / Hu, Wenhua; Carver, Jeffrey C.; Anu, Vaibhav; Walia, Gursimran S.; Bradshaw, Gary.

10th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement, ESEM 2016. IEEE Computer Society, 2016. a30 (International Symposium on Empirical Software Engineering and Measurement; Vol. 08-09-September-2016).

Research output: Chapter in Book/Report/Conference proceedingConference contributionResearchpeer-review

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PB - IEEE Computer Society

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Hu W, Carver JC, Anu V, Walia GS, Bradshaw G. Detection of Requirement Errors and Faults via a Human Error Taxonomy: A Feasibility Study. In 10th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement, ESEM 2016. IEEE Computer Society. 2016. a30. (International Symposium on Empirical Software Engineering and Measurement). https://doi.org/10.1145/2961111.2962596