What kinds of development problems can be solved by searching the web?: a field study
Proceedings of the 3rd International Workshop on Search-Driven Development: Users, Infrastructure, Tools, and Evaluation
Analyzing and mining a code search engine usage log
Empirical Software Engineering
Enriching Documents with Examples: A Corpus Mining Approach
ACM Transactions on Information Systems (TOIS)
Portfolio: Searching for relevant functions and their usages in millions of lines of code
ACM Transactions on Software Engineering and Methodology (TOSEM) - Testing, debugging, and error handling, formal methods, lifecycle concerns, evolution and maintenance
Improving software modularization via automated analysis of latent topics and dependencies
ACM Transactions on Software Engineering and Methodology (TOSEM)
Hi-index | 0.01 |
We present a topic modeling analysis of a year long usage log of Koders, one of the major commercial code search engines. This analysis contributes to the understanding of what users of code search engines are looking for. Observations on the prevalence of these topics among the users, and on how search and download activities vary across topics, leads to the conclusion that users who find code search engines usable are those who already know to a high level of specificity what to look for. This paper presents a general categorization of these topics that provides insights on the different ways code search engine users express their queries. The findings support the conclusion that existing code search engines provide only a subset of the various information needs of the users when compared to the categories of queries they look at.