Skip to main content

Usefulness of a Human Error Identification Tool for Requirements Inspection: An Experience Report

  • Conference paper
  • First Online:
Requirements Engineering: Foundation for Software Quality (REFSQ 2017)

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 10153))

Abstract

Context and Motivation: Our recent work leverages Cognitive Psychology research on human errors to improve the standard fault-based requirements inspections. Question: The empirical study presented in this paper 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. Results: The results showed that the HEAA tool, though effective, presented challenges during the error abstraction process. Contribution: In this experience report, we present major challenges during the study execution and lessons learned for future replications.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Subscribe and save

Springer+ Basic
EUR 32.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  1. Anu, V., Walia, G.S., Hu, W., Carver, J.C., Bradshaw, G.: Effectiveness of human error taxonomy during requirements inspection: an empirical investigation. In: Software Engineering and Knowledge Engineering, SEKE 2016 (2016)

    Google Scholar 

  2. Anu, V., Walia, G.S., Hu, W., Carver, J.C., Bradshaw, G.: The Human Error Abstraction Assist (HEAA) tool (2016). http://vaibhavanu.com/NDSU-CS-TP-2016-001.html

  3. Hsieh, H.F., Shannon, S.E.: Three approaches to qualitative content analysis. Qual. Health Res. 15(9), 1277–1288 (2005)

    Article  Google Scholar 

  4. Hu, W., Carver, J.C., Anu, V., Walia, G.S., 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 (2016)

    Google Scholar 

  5. Lanubile, F., Shull, F., Basili, V.R.: Experimenting with error abstraction in requirements documents. In: Proceedings of the 5th International Symposium on Software Metrics (1998)

    Google Scholar 

  6. Porter, A.A., Votta, L.G., Basili, V.R.: Comparing detection methods for software requirements inspections: a replicated experiment. IEEE Trans. Softw. Eng. 21(6), 563–575 (1995)

    Article  Google Scholar 

Download references

Acknowledgment

This work was supported by NSF Awards 1423279 and 1421006. The authors would like to thank the students of the Software Requirements course at North Dakota State University for participating in this study.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Vaibhav Anu .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2017 Springer International Publishing AG

About this paper

Cite this paper

Anu, V., Walia, G., Bradshaw, G., Hu, W., Carver, J.C. (2017). Usefulness of a Human Error Identification Tool for Requirements Inspection: An Experience Report. In: Grünbacher, P., Perini, A. (eds) Requirements Engineering: Foundation for Software Quality. REFSQ 2017. Lecture Notes in Computer Science(), vol 10153. Springer, Cham. https://doi.org/10.1007/978-3-319-54045-0_26

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-54045-0_26

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-54044-3

  • Online ISBN: 978-3-319-54045-0

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics