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

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.

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