Source code querying tools allow programmers to explore relations between different parts of the code base. This paper describes such a tool, named CodeQuest. It combines two previous proposals, namely the use of logic programming and database systems. As the query language we use safe Datalog, which was originally introduced in the theory of databases. That provides just the right level of expressiveness; in particular recursion is indispensable for source code queries. Safe Datalog is like Prolog, but all queries are guaranteed to terminate, and there is no need for extra-logical annotations. Our implementation of Datalog maps queries to a relational database system. We are thus able to capitalise on the query optimiser provided by such a system. For recursive queries we implement our own optimisations in the translation from Datalog to SQL. Experiments confirm that this strategy yields an efficient, scalable code querying system.

Code Quest : Scalable Source Code Queries with Datalog

Source code querying tools allow programmers to explore relations between different parts of the code base. This paper describes such a tool, named codeQuest. It combines two previous proposals, namely the use of logic programming and database systems.

As the query language we use safe Datalog, which was originally introduced in the theory of databases. That provides just the right level of expressiveness; in particular recursion is indispensable for source code queries. Safe Datalog is like Prolog, but all queries are guaranteed to terminate, and there is no need for extra-logical annotations.

Our implementation of Datalog maps queries to a relational database system. We are thus able to capitalise on the query optimiser provided by such a system. For recursive queries we implement our own optimisations in the translation from Datalog to SQL. Experiments confirm that this strategy yields an efficient, scalable code querying system.

CodeQuest : scalable source code queries with datalog

Current research in software reengineering offers a great amount of tools specialized on certain reengineering tasks. The definition of a powerful common interchange format is a key issue to provide interoperability between these tools. This paper discusses aspects of data interchange formats for exchanging reengineering related data. It proposes a graph-based format to exchange both application specific concepts and data by XML documents.

/pdf/grax-an-interchange-format-for-reengineering-tools-47equrh0ym.pdf

GraX-an interchange format for reengineering tools

We present an overview of JTL (the Java Tools Language, pronounced "Gee-tel"), a novel language for querying JAVA [8] programs. JTL was designed to serve the development of source code software tools for JAVA, and as a small language which to aid programming language extensions to JAVA. Applications include definition of pointcuts for aspect-oriented programming, fixing type constraints for generic programming, specification of encapsulation policies, definition of micro-patterns, etc. We argue that the JTL expression of each of these is systematic, concise, intuitive and general.JTL relies on a simply-typed relational database for program representation, rather than an abstract syntax tree. The underlying semantics of the language is restricted to queries formulated in First Order Predicate Logic augmented with transitive closure (FOPL).Special effort was taken to ensure terse, yet readable expression of logical conditions. The JTL pattern public abstract class, for example, matches all abstract classes which are publicly accessible, while class (public clone();) matches all classes in which method clone is public. To this end, JTL relies on a DATALOG-like syntax and semantics, enriched with quantifiers and pattern matching which all but entirely eliminate the need for recursive calls.JTL's query analyzer gives special attention to the fragility of the "closed world assumption" in examining JAVA software, and determines whether a query relies on such an assumption.The performance of the JTL interpreter is comparable to that of JQuery after it generated its database cache, and at least an order of magnitude faster when the cache has to be rebuilt.

/pdf/jtl-the-java-tools-language-ofba6da571.pdf

JTL: the Java tools language

A powerful set of features can assist software developers in searching source code. Source code can be queried to find occurrences of source code elements mapped to domain concepts appearing in an ontology. Queries can specify a search for occurrences of particular operations performed on domain concepts within the source code. Query expansion can be used to locate related domain concepts as indicated in the ontology. Query keyword weighting can be used to emphasize one domain concept over another. Tools can be provided to create the ontology and associate the ontology with the elements appearing in the source code. Results can include user interface features assisting in navigation to a location within the source code associated with the query results.

Semantic-based query techniques for source code

Querying and analyzing source code interactively is a critical task in reverse engineering and program understanding. Current source code query systems lack sufficient formalism and offer limited query capabilities. We introduce the formal framework of Source Code Algebra (SCA), and outline a source code query system based on it. SCA provides a formal data model for source code, an algebraic expression-based query language, and opportunities for query optimization. An algebraic model of source code addresses the issues of conceptual integrity, expressive power, and performance of a source code query system within a unified framework. >

Querying source code using an algebraic query language

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Querying source code using an algebraic query language