Hybrid storage for enabling fully-featured text search and fine-grained structural search over source code

Authors:
Oleksandr Panchenko
Affiliations:
Hasso Plattner Institute for Software Systems Engineering, P.O. Box 900460, 14440 Potsdam, Germany
Venue:
SUITE '09 Proceedings of the 2009 ICSE Workshop on Search-Driven Development-Users, Infrastructure, Tools and Evaluation
Year:
2009

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Abstract

Searching is an important activity in software maintenance. Dedicated data structures have been used to support either textual or structural queries over source code. The goal of this ongoing research is to elaborate a hybrid data storage that enables simultaneous textual and structural search. The naive adjacency list method has been combined with the inverted index approach. The data model has been enhanced with the use of recent data compression approaches for column-oriented databases to allow no-loss albeit compact storage of fine-grained structural data. The graph indexing has enabled the proposed data model to expeditiously answer fine-grained structural queries. This paper describes the basics of the proposed approach and estimates its feasibility.