Defect prevention in requirements using human error information: An empirical study

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

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

5 Scopus citations

Abstract

Context and Motivation: The correctness of software requirements is of critical importance to the success of a software project. Problems that occur during requirements collection and specification, if not fixed early, are costly to fix later. Therefore, it is important to develop approaches that help requirement engineers not only detect, but also prevent requirements problems. Because requirements engineering is a human-centric activity, we can build upon developments from the field of human cognition. Question/Problem: Human Errors are the failings of human cognition during the process of solving, planning, or executing a task. We have employed research about Human Errors to describe the types of problems that occur during requirements engineering. The goal of this paper is to determine whether knowledge of Human Errors can serve as a fault prevention mechanism during requirements engineering. Principal ideas/results: The results of our study show that a better understanding of human errors does lead developers to insert fewer problems into their own requirements documents. Our results also indicate that different types of Human Error information have different impacts on fault prevention. Contribution: In this paper, we show that the use of Human Error information from Cognitive Psychology is useful for fault prevention during requirements engineering.

Original languageEnglish
Title of host publicationRequirements Engineering
Subtitle of host publicationFoundation for Software Quality - 23rd International Working Conference, REFSQ 2017, Proceedings
EditorsAnna Perini, Paul Grünbacher
PublisherSpringer Verlag
Pages61-76
Number of pages16
ISBN (Print)9783319540443
DOIs
StatePublished - 2017
Event23rd International Working Conference on Requirements Engineering – Foundation for Software Quality, REFSQ 2017 - Essen, Germany
Duration: 27 Feb 20172 Mar 2017

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10153 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference23rd International Working Conference on Requirements Engineering – Foundation for Software Quality, REFSQ 2017
Country/TerritoryGermany
City Essen
Period27/02/172/03/17

Keywords

  • Empirical study
  • Fault prevention
  • Human errors
  • Human factors
  • Software requirements

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