Programming errors in traversal programs over structured data

Traversal strategies \'a la Stratego (also \'a la Strafunski and 'Scrap Your Boilerplate') provide an exceptionally versatile and uniform means of querying and transforming deeply nested and heterogeneously structured data including terms in functional programming and rewriting, objects in OO programming, and XML documents in XML programming. However, the resulting traversal programs are prone to programming errors. We are specifically concerned with errors that go beyond conservative type errors; examples we examine include divergent traversals, prematurely terminated traversals, and traversals with dead code. Based on an inventory of possible programming errors we explore options of static typing and static analysis so that some categories of errors can be avoided. This exploration generates suggestions for improvements to strategy libraries as well as their underlying programming languages. Haskell is used for illustrations and specifications with sufficient explanations to make the presentation comprehensible to the non-specialist. The overall ideas are language-agnostic and they are summarized accordingly

Faithful (meta-)encodings of programmable strategies into term rewriting systems

Rewriting is a formalism widely used in computer science and mathematical logic. When using rewriting as a programming or modeling paradigm, the rewrite rules describe the transformations one wants to operate and rewriting strategies are used to con- trol their application. The operational semantics of these strategies are generally accepted and approaches for analyzing the termination of specific strategies have been studied. We propose in this paper a generic encoding of classic control and traversal strategies used in rewrite based languages such as Maude, Stratego and Tom into a plain term rewriting system. The encoding is proven sound and complete and, as a direct consequence, estab- lished termination methods used for term rewriting systems can be applied to analyze the termination of strategy controlled term rewriting systems. We show that the encoding of strategies into term rewriting systems can be easily adapted to handle many-sorted signa- tures and we use a meta-level representation of terms to reduce the size of the encodings. The corresponding implementation in Tom generates term rewriting systems compatible with the syntax of termination tools such as AProVE and TTT2, tools which turned out to be very effective in (dis)proving the termination of the generated term rewriting systems. The approach can also be seen as a generic strategy compiler which can be integrated into languages providing pattern matching primitives; experiments in Tom show that applying our encoding leads to performances comparable to the native Tom strategies

Programming errors in traversal programs over structured data

Traversal strategies provide an established means of describing automated queries, analyses, transformations, and other non-trivial computations on deeply structured data (including, most notably, data representations of software artifacts such as programs). The resulting traversal programs are prone to programming errors. We are specifically concerned with errors that go beyond classic type errors, in particular: (i) divergence of traversal, (ii) unintentional extent of traversal into data, (iii) trivial traversal results, (iv) inapplicability of the constituents of a traversal program along traversal. We deliver a taxonomy of programming errors, and start attacking some of them by refinements of traversal programming

Effective Strategic Programming for Java Developers

International audienceIn object programming languages, the Visitor design pattern allows separation of algorithms and data-structures. When applying this pattern to tree-like structures, programmers are always confronted with the difficulty of making their code evolve. One reason is that the code implementing the algorithm is interwound with the code implementing the traversal inside the Visitor. When implementing algorithms such as data analyses or transformations, encoding the traversal directly into the algorithm turns out to be cumbersome as this type of algorithm only focuses on a small part of the data-structure model (e.g., program optimization). Unfortunately, typed programming languages like Java do not offer simple solutions for expressing generic traversals. Rewrite-based languages like ELAN or Stratego have introduced the notion of strategies to express both generic traversal and rule application control in a declarative way. Starting from this approach, our goal was to make the notion of strategic programming available in a widely used language such as Java and thus to offer generic traversals in typed Java structures. In this paper, we present the strategy language SL that provides programming support for strategies in Java

A TYPE ANALYSIS OF REWRITE STRATEGIES

Rewrite strategies provide an algorithmic rewriting of terms using strategic compositions of rewrite rules. Due to the programmability of rewrites, errors are often made due to incorrect compositions of rewrites or incorrect application of rewrites to a term within a strategic rewriting program. In practical applications of strategic rewriting, testing and debugging becomes substantially time-intensive for large programs applied to large inputs derived from large term grammars. In essence, determining which rewrite in what position in a term did or did not re comes down to logging, tracing and/or di -like comparison of inputs to outputs. In this thesis, we explore type-enabled analysis of strategic rewriting programs to detect errors statically. In particular, we introduce high-precision types to closely approximate the dynamic behavior of rewriting. We also use union types to track sets of types due to presence of strategic compositions. In this framework of high-precision strategic typing, we develop and implement an expressive type system for a representative strategic rewriting language TL. The results of this research are sufficiently broad to be adapted to other strategic rewriting languages. In particular, the type-inferencing algorithm does not require explicit type annotations for minimal impact on an existing language. Based on our experience with the implementation, the type system significantly reduces the time and effort to program correct rewrite strategies while performing the analysis on the order of thousands of source lines of code per second