Locating Software Errors à la WebSearchEngine

Large part of software development is fixing errors, to improve software quality and customer satisfaction. Developers spent 60-80% of their time on searching for relevant code files to fix.

In the context of doctoral research at the Open University in London, we invented a completely new search algorithm. It suggests the likely files to fix an error with enormous efficiency, leading to:

  • reduce time and cost to correct errors, by automatically adding the suggestions to the error report;
  • build confidence and improve productivity of new or outsourced staff not familiar with the codebase;

Our approach is fast, light-weight and simple and yet outperforms other approaches by listing at least one faulty file among the top 10 suggested.
Average hit rates:

  • 1 out 1: 44%
  • 1 out of 5: 69%
  • 1 out of 10: 76%

We are looking for industrial collaborations partners.

  • Our tool is ready for use with industrial code.
  • Extendable to other programming languages, besides Java.
  • Enabled for professional workflows and tools, e.g. bug tracking systems, continuous integration tools, IDEs.

Locating Bugs without Looking Back, MSR 2016. Paper: http://oro.open.ac.uk/45654.