a b s t r a c tStratego/XT is a language and toolset for program transformation. The Stratego language provides rewrite rules for expressing basic transformations, programmable rewriting strategies for controlling the application of rules, concrete syntax for expressing the patterns of rules in the syntax of the object language, and dynamic rewrite rules for expressing context-sensitive transformations, thus supporting the development of transformation components at a high level of abstraction. The XT toolset offers a collection of flexible, reusable transformation components, and tools for generating such components from declarative specifications. Complete program transformation systems are composed from these components. This paper gives an overview of Stratego/XT 0.17, including a description of the Stratego language and XT transformation tools; a discussion of the implementation techniques and software engineering process; and a description of applications built with Stratego/XT.

We present the D framework for points-to analysis of Java programs. D builds on the idea of specifying pointer analysis algorithms declaratively, using Datalog: a logicbased language for defining (recursive) relations. We carry the declarative approach further than past work by describing the full end-to-end analysis in Datalog and optimizing aggressively using a novel technique specifically targeting highly recursive Datalog programs.As a result, D achieves several benefits, including full order-of-magnitude improvements in runtime. We compare D with Lhoták and Hendren's P, which defines the state of the art for context-sensitive analyses. For the exact same logical points-to definitions (and, consequently, identical precision) D is more than 15x faster than P for a 1-call-site sensitive analysis of the DaCapo benchmarks, with lower but still substantial speedups for other important analyses. Additionally, D scales to very precise analyses that are impossible with P and Whaley et al.'s bddbddb, directly addressing open problems in past literature. Finally, our implementation is modular and can be easily configured to analyses with a wide range of characteristics, largely due to its declarativeness.

We present the D framework for points-to analysis of Java programs. D builds on the idea of specifying pointer analysis algorithms declaratively, using Datalog: a logicbased language for defining (recursive) relations. We carry the declarative approach further than past work by describing the full end-to-end analysis in Datalog and optimizing aggressively using a novel technique specifically targeting highly recursive Datalog programs.As a result, D achieves several benefits, including full order-of-magnitude improvements in runtime. We compare D with Lhoták and Hendren's P, which defines the state of the art for context-sensitive analyses. For the exact same logical points-to definitions (and, consequently, identical precision) D is more than 15x faster than P for a 1-call-site sensitive analysis of the DaCapo benchmarks, with lower but still substantial speedups for other important analyses. Additionally, D scales to very precise analyses that are impossible with P and Whaley et al.'s bddbddb, directly addressing open problems in past literature. Finally, our implementation is modular and can be easily configured to analyses with a wide range of characteristics, largely due to its declarativeness.

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Abstract. In meta programming with concrete object syntax, object-level programs are composed from fragments written in concrete syntax. The use of small program fragments in such quotations and the use of meta-level expressions within these fragments (anti-quotation) often leads to ambiguities. This problem is usually solved through explicit disambiguation, resulting in considerable syntactic overhead. A few systems manage to reduce this overhead by using type information during parsing. Since this is hard to achieve with traditional parsing technology, these systems provide specific combinations of meta and object languages, and their implementations are difficult to reuse. In this paper, we generalize these approaches and present a language independent method for introducing concrete object syntax without explicit disambiguation. The method uses scannerless generalized-LR parsing to parse meta programs with embedded objectlevel fragments, which produces a forest of all possible parses. This forest is reduced to a tree by a disambiguating type checker for the meta language. To validate our method we have developed embeddings of several object languages in Java, including AspectJ and Java itself.