Solving Semantic Searches for Source Code

Programmers search for code frequently utilizing syntactic queries. The effectiveness of this type of search depends on the ability of a programmer to specify a query that captures how the desired code may have been implemented, and the results often include many irrelevant matches that must be filtered manually. More semantic search approaches could address these limitations, yet the existing approaches either do not scale or require for the programmer to define complex queries. Instead, our approach to semantic search requires for the programmer to write lightweight, incomplete specifications, such as an example input and expected output of a desired function. Unlike existing approaches to semantic search, we use an SMT solver to identify programs in a repository, encoded as constraints, that match the programmer-provided specification. We instantiate the approach on subsets of the Java string library, Yahoo! Pipes mashup language, and SQL select statements, and begin to assess its effectiveness and efficiency through evaluations in each domain