An Information Retrieval Approach to Concept Location in Source Code
WCRE '04 Proceedings of the 11th Working Conference on Reverse Engineering
Source Code Exploration with Google
ICSM '06 Proceedings of the 22nd IEEE International Conference on Software Maintenance
Using natural language program analysis to locate and understand action-oriented concerns
Proceedings of the 6th international conference on Aspect-oriented software development
Combining Formal Concept Analysis with Information Retrieval for Concept Location in Source Code
ICPC '07 Proceedings of the 15th IEEE International Conference on Program Comprehension
Introduction to Information Retrieval
Introduction to Information Retrieval
Automatically capturing source code context of NL-queries for software maintenance and reuse
ICSE '09 Proceedings of the 31st International Conference on Software Engineering
Integrating natural language and program structure information to improve software search and exploration
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As software continues to grow, locating code for maintenance tasks becomes increasingly difficult. Software search tools help developers find source code relevant to their maintenance tasks. One major challenge to successful search tools is locating relevant code when the user's query contains words with multiple meanings or words that occur frequently throughout the program. Traditional search techniques, which treat each word individually, are unable to distinguish relevant and irrelevant methods under these conditions. In this paper, we present a novel search technique that uses information such as the position of the query word and its semantic role to calculate relevance. Our evaluation shows that this approach is more consistently effective than three other state of the art search techniques.