3rd international software language engineering conference (SLE) : pre-proceedings, October 12-13, 2010, Eindhoven, the Netherlands

We are pleased to present the proceedings of the Third International Conference on Software Language Engineering (SLE 2010). The conference will be held in Eindhoven, the Netherlands during October 12-13, 2010 and will be co-located with The Ninth International Conference on Generative Programming and Component Engineering (GPCE'10), and The Workshop on Feature-Oriented Software Development (FOSD). An important goal of SLE is to integrate the different sub-communities of the software-language-engineering community to foster cross-fertilization and strengthen research overall. The Doctoral Symposium at SLE 2010 contributes towards these goals by providing a forum for both early and late-stage PhD students to present their research and get detailed feedback and advice from other researchers. The SLE conference series is devoted to a wide range of topics related to artificial languages in software engineering. SLE is an international research forum that brings together researchers and practitioners from both industry and academia to expand the frontiers of software language engineering. SLE's foremost mission is to encourage and organize communication between communities that have traditionally looked at software languages from different, more specialized, and yet complementary perspectives. SLE emphasizes the fundamental notion of languages as opposed to any realization in specific technical spaces. In this context, the term "software language" comprises all sorts of artificial languages used in software development including general-purpose programming languages, domain-specific languages, modeling and meta-modeling languages, data models, and ontologies. Software language engineering is the application of a systematic, disciplined, quantifiable approach to the development, use, and maintenance of these languages. The SLE conference is concerned with all phases of the lifecycle of software languages; these include the design, implementation, documentation, testing, deployment, evolution, recovery, and retirement of languages. Of special interest are tools, techniques, methods, and formalisms that support these activities. In particular, tools are often based on, or automatically generated from, a formal description of the language. Hence, the treatment of language descriptions as software artifacts, akin to programs, is of particular interest - while noting the special status of language descriptions, and the tailored engineering principles and methods for modularization, refactoring, refinement, composition, versioning, co-evolution, and analysis that can be applied to them. The response to the call for papers for SLE 2010 was very enthusiastic. We received 79 full submissions from 108 initial abstract submissions. From these submissions, the Program Committee (PC) selected 25 papers: 17 full papers, five short papers, and two tool demonstration papers, resulting in an acceptance rate of 32%. To ensure the quality of the accepted papers, each submitted paper was reviewed by at least three PC members. Each paper was discussed in detail during the electronic PC meeting. A summary of this discussion was prepared by members of the PC and provided to the authors along with the reviews

Context-Free Path Querying with Structural Representation of Result

Graph data model and graph databases are very popular in various areas such as bioinformatics, semantic web, and social networks. One specific problem in the area is a path querying with constraints formulated in terms of formal grammars. The query in this approach is written as grammar, and paths querying is graph parsing with respect to given grammar. There are several solutions to it, but how to provide structural representation of query result which is practical for answer processing and debugging is still an open problem. In this paper we propose a graph parsing technique which allows one to build such representation with respect to given grammar in polynomial time and space for arbitrary context-free grammar and graph. Proposed algorithm is based on generalized LL parsing algorithm, while previous solutions are based mostly on CYK or Earley algorithms, which reduces time complexity in some cases.Comment: Evaluation extende

Purely functional GLL parsing

Generalised parsing has become increasingly important in the context of software language design and several compiler generators and language workbenches have adopted generalised parsing algorithms such as GLR and GLL. The original GLL parsing algorithms are described in low-level pseudo-code as the output of a parser generator. This paper explains GLL parsing differently, defining the FUN-GLL algorithm as a collection of pure, mathematical functions and focussing on the logic of the algorithm by omitting implementation details. In particular, the data structures are modelled by abstract sets and relations rather than specialised implementations. The description is further simplified by omitting lookahead and adopting the binary subtree representation of derivations to avoid the clerical overhead of graph construction. Conventional parser combinators inherit the drawbacks from the recursive descent algorithms they implement. Based on FUN-GLL, this paper defines generalised parser combinators that overcome these problems. Th

A Reference GLL Implementation

The Generalised-LL (GLL) context-free parsing algorithmwas introduced at the 2009 LDTA workshop, and since then aseries of variant algorithms and implementations have beendescribed. There is a wide variety of optimisations that maybe applied to GLL, some of which were already present inthe originally published form.This paper presents a reference GLL implementation shornof all optimisations as a common baseline for the real-worldcomparison of performance across GLL variants. This baselineversion has particular value for non-specialists, sinceits simple form may be straightforwardly encoded in theimplementer’s preferred programming language.We also describe our approach to low level memory managementof GLL internal data structures. Our evaluation onlarge inputs shows a factor 3–4 speedup over a naïve implementationusing the standard Java APIs and a factor 4–5reduction in heap requirements. We conclude with noteson some algorithm-level optimisations that may be appliedindependently of the internal data representation

On the Relation between Context-Free Grammars and Parsing Expression Grammars

Context-Free Grammars (CFGs) and Parsing Expression Grammars (PEGs) have several similarities and a few differences in both their syntax and semantics, but they are usually presented through formalisms that hinder a proper comparison. In this paper we present a new formalism for CFGs that highlights the similarities and differences between them. The new formalism borrows from PEGs the use of parsing expressions and the recognition-based semantics. We show how one way of removing non-determinism from this formalism yields a formalism with the semantics of PEGs. We also prove, based on these new formalisms, how LL(1) grammars define the same language whether interpreted as CFGs or as PEGs, and also show how strong-LL(k), right-linear, and LL-regular grammars have simple language-preserving translations from CFGs to PEGs

Left Recursion in Parsing Expression Grammars

Parsing Expression Grammars (PEGs) are a formalism that can describe all deterministic context-free languages through a set of rules that specify a top-down parser for some language. PEGs are easy to use, and there are efficient implementations of PEG libraries in several programming languages. A frequently missed feature of PEGs is left recursion, which is commonly used in Context-Free Grammars (CFGs) to encode left-associative operations. We present a simple conservative extension to the semantics of PEGs that gives useful meaning to direct and indirect left-recursive rules, and show that our extensions make it easy to express left-recursive idioms from CFGs in PEGs, with similar results. We prove the conservativeness of these extensions, and also prove that they work with any left-recursive PEG. PEGs can also be compiled to programs in a low-level parsing machine. We present an extension to the semantics of the operations of this parsing machine that let it interpret left-recursive PEGs, and prove that this extension is correct with regards to our semantics for left-recursive PEGs.Comment: Extended version of the paper "Left Recursion in Parsing Expression Grammars", that was published on 2012 Brazilian Symposium on Programming Language

One Parser to Rule Them All

Despite the long history of research in parsing, constructing parsers for real programming languages remains a difficult and painful task. In the last decades, different parser generators emerged to allow the construction of parsers from a BNF-like specification. However, still today, many parsers are handwritten, or are only partly generated, and include various hacks to deal with different peculiarities in programming languages. The main problem is that current declarative syntax definition techniques are based on pure context-free grammars, while many constructs found in programming languages require context information. In this paper we propose a parsing framework that embraces context information in its core. Our framework is based on data-dependent grammars, which extend context-free grammars with arbitrary computation, variable binding and constraints. We present an implementation of our framework on top of the Generalized LL (GLL) parsing algorithm, and show how common idioms in syntax of programming languages such as (1) lexical disambiguation filters, (2) operator precedence, (3) indentation-sensitive rules, and (4) conditional preprocessor directives can be mapped to data-dependent grammars. We demonstrate the initial experience with our framework, by parsing more than 20000 Java, C#, Haskell, and OCaml source files