Using argumentation theory to analyse software practitioners’ defeasible evidence, inference and belief

Research output: Contribution to journalArticlepeer-review

10 Citations (Scopus)

Abstract

Context Software practitioners are often the primary source of information for software engineering research. They naturally produce information about their experiences of software practice, and the beliefs they infer from their experiences. Researchers must evaluate the quality and quantity of this information for their research. Objective To examine how concepts and methods from argumentation research can be used to study practitioners’ evidence, inference and beliefs so as to better understand and improve software practice. Method We develop a preliminary framework and preliminary methodology, and use those to identify, extract and structure practitioners’ evidence, inference and beliefs. We illustrate the application of the framework and methodology with examples from a practitioner's blog post. Result The practitioner uses (factual) stories, analogies, examples and popular opinion as evidence, and uses that evidence in defeasible reasoning to justify his beliefs and to rebut the beliefs of other practitioners. Conclusion The framework, methodology and examples could provide a foundation for software engineering researchers to develop a more sophisticated understanding of, and appreciation for, practitioners’ defeasible evidence, inference and belief. Further work needs to automate (parts of) the methodology to support larger-scale application of the methodology.

Original languageEnglish
Pages (from-to)62-80
Number of pages19
JournalInformation and Software Technology
Volume87
Early online date02 Feb 2017
DOIs
Publication statusPublished - Jul 2017

Keywords

  • Analogy
  • Argumentation
  • Behavioural software engineering
  • Evidence
  • Evidence based software engineering
  • Experience
  • Explanation
  • Qualitative analysis
  • Software practice
  • Story

ASJC Scopus subject areas

  • Software
  • Information Systems
  • Computer Science Applications

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