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Human Error Analysis in Software Engineering

In: Theory and Application on Cognitive Factors and Risk Management - New Trends and Procedures

Author

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  • Fuqun Huang

Abstract

As the primary cause of software defects, human error is the key to understanding, detecting and preventing software defects. This chapter first reviews the state of art of an emerging area: software fault defense based on human error mechanisms. Then, an approach for human error analysis (HEA) is proposed. HEA consists of two important components: human error modes (HEM) and an undated version of causal mechanism graphs (CMGs). Human error modes are the general erroneous patterns that humans tend to behave in a variety of activities. Causal mechanism graph provides a way to extract the error-prone contexts in software development, and link the contexts to general human error modes. HEA can be used at various phases of software development, for both defect detection and prevention purposes. An application case is provided to demonstrate how to use HEA.

Suggested Citation

  • Fuqun Huang, 2017. "Human Error Analysis in Software Engineering," Chapters, in: Fabio De Felice & Antonella Petrillo (ed.), Theory and Application on Cognitive Factors and Risk Management - New Trends and Procedures, IntechOpen.
    • Handle: RePEc:ito:pchaps:112509
    DOI: 10.5772/intechopen.68392
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    File URL: https://www.intechopen.com/chapters/54996
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    Cited by:

    1. Selvik, Jon T. & Bellamy, Linda J., 2020. "Addressing human error when collecting failure cause information in the oil and gas industry: A review of ISO 14224:2016," Reliability Engineering and System Safety, Elsevier, vol. 194(C).

    More about this item

    Keywords

    human error analysis; software defect prevention; fault detection; causal mechanism graph; software quality assurance;
    All these keywords.

    JEL classification:

    • M11 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - Production Management

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