Using Supervised Learning to Guide the Selection of Software Inspectors in Industry

Maninder Singh, Gursimran Singh Walia, Anurag Goswami

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations

Abstract

Software development is a multi-phase process that starts with requirement engineering. Requirements elicited from different stakeholders are documented in natural language (NL) software requirement specification (SRS) document. Due to the inherent ambiguity of NL, SRS is prone to faults (e.g., ambiguity, incorrectness, inconsistency). To find and fix faults early (where they are cheapest to find), companies routinely employ inspections, where skilled inspectors are selected to review the SRS and log faults. While other researchers have attempted to understand the factors (experience and learning styles) that can guide the selection of effective inspectors but could not report improved results. This study analyzes the reading patterns (RPs) of inspectors recorded by eye-tracking equipment and evaluates their abilities to find various fault-types. The inspectors' characteristics are selected by employing ML algorithms to find the most common RPs w.r.t each fault-types. Our results show that our approach could guide the inspector selection with an accuracy ranging between 79.3% and 94% for various fault-types.

Original languageEnglish (US)
Title of host publicationProceedings - 29th IEEE International Symposium on Software Reliability Engineering Workshops, ISSREW 2018
EditorsRoberto Natella, Sudipto Ghosh, Nuno Laranjeiro, Robin Poston, Bojan Cukic
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages12-17
Number of pages6
ISBN (Electronic)9781538694435
DOIs
StatePublished - Nov 16 2018
Externally publishedYes
Event29th IEEE International Symposium on Software Reliability Engineering Workshops, ISSREW 2018 - Memphis, United States
Duration: Oct 15 2018Oct 18 2018

Publication series

NameProceedings - 29th IEEE International Symposium on Software Reliability Engineering Workshops, ISSREW 2018

Conference

Conference29th IEEE International Symposium on Software Reliability Engineering Workshops, ISSREW 2018
Country/TerritoryUnited States
CityMemphis
Period10/15/1810/18/18

Keywords

  • classifiers
  • eye tracking
  • Fault types
  • inspector selection
  • machine learning
  • reading patterns

ASJC Scopus subject areas

  • Software
  • Safety, Risk, Reliability and Quality

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