Recommending Relevant Sections from a Webpage about Programming Errors and Exceptions

TL;DR

This paper introduces a context-aware, IDE-integrated method for recommending relevant webpage sections about programming errors, improving developers' efficiency by filtering out irrelevant content during troubleshooting.

Contribution

It presents a novel, context-sensitive approach for extracting relevant webpage sections related to programming exceptions within an IDE environment.

Findings

High precision, recall, and F1-measure in evaluations

Effective filtering of irrelevant webpage content

Outperforms existing techniques like VSM and LSA

Abstract

Programming errors or exceptions are inherent in software development and maintenance, and given today's Internet era, software developers often look at web for finding working solutions. They make use of a search engine for retrieving relevant pages, and then look for the appropriate solutions by manually going through the pages one by one. However, both the manual checking of a page's content against a given exception (and its context) and then working an appropriate solution out are non-trivial tasks. They are even more complex and time-consuming with the bulk of irrelevant (i.e., off-topic) and noisy (e.g., advertisements) content in the web page. In this paper, we propose an IDE-based and context-aware page content recommendation technique that locates and recommends relevant sections from a given web page by exploiting the technical details, in particular, the context of an encountered exception in the IDE. An evaluation with 250 web pages related to 80 programming exceptions, comparison with the only available closely related technique, and a case study involving comparison with VSM and LSA techniques show that the proposed technique is highly promising in terms of precision, recall and F1-measure.