An IDE-Based Context-Aware Meta Search Engine

TL;DR

This paper introduces an IDE-integrated, context-aware web search tool for developers that improves search relevance by considering programming context, resulting in higher accuracy and user satisfaction compared to traditional keyword searches.

Contribution

It presents a novel IDE-based search engine that combines multiple web APIs and context analysis to enhance developer problem-solving efficiency.

Findings

96% recommendation accuracy in experiments

64.28% agreement in user study

Outperforms traditional keyword-based search methods

Abstract

Traditional web search forces the developers to leave their working environments and look for solutions in the web browsers. It often does not consider the context of their programming problems. The context-switching between the web browser and the working environment is time-consuming and distracting, and the keyword-based traditional search often does not help much in problem solving. In this paper, we propose an Eclipse IDE-based web search solution that collects the data from three web search APIs-- Google, Yahoo, Bing and a programming Q & A site-- Stack Overflow. It then provides search results within IDE taking not only the content of the selected error into account but also the problem context, popularity and search engine recommendation of the result links. Experiments with 25 run time errors and exceptions show that the proposed approach outperforms the keyword-based search approaches with a recommendation accuracy of 96%. We also validate the results with a user study involving five prospective participants where we get a result agreement of 64.28%. While the preliminary results are promising, the approach needs to be further validated with more errors and exceptions followed by a user study with more participants to establish itself as a complete IDE-based web search solution.