Investigation of error notifications through categorization

  • Authors:
  • Michael Bazik

  • Affiliations:
  • North Carolina State University, USA

  • Venue:
  • Proceedings of the 2013 companion publication for conference on Systems, programming, & applications: software for humanity
  • Year:
  • 2013

Quantified Score

Hi-index 0.00

Visualization

Abstract

Program analysis tools often output error notifications that novice and industry programmers both have trouble understanding. The lack of expressive, scalable error notifications makes programming difficult to novice developers and hinders the progress of industry developers. Here, I propose a taxonomy of error notifications containing categories each with a model syntax for error notifications of similar type. By categorizing error notifications into 39 categories, and developing a questionnaire to aid in the categorization process, error notification creators can edit and refine existing error notifications as well as use the categories to create expressive, scalable error notifications that offer developers a better opportunity to resolve errors.