A personal retrospective on language workbenches

Model-driven software engineering and specifically domain-specific languages have contributed to improve the quality of software and the efficiency in the development of software. However, the design and implementation of domain-specific languages requires still an enormous investment. Language workbenches are the most important tools in the field of software language engineering. The introduction of language workbenches has alleviated partly the development effort, but there are still a few major challenges that need to be tackled. This paper presents a personal perspective on the development of tools for language engineering and language workbenches in particular and future challenges to be tackled.</p

Recursion Aware Modeling and Discovery For Hierarchical Software Event Log Analysis (Extended)

This extended paper presents 1) a novel hierarchy and recursion extension to the process tree model; and 2) the first, recursion aware process model discovery technique that leverages hierarchical information in event logs, typically available for software systems. This technique allows us to analyze the operational processes of software systems under real-life conditions at multiple levels of granularity. The work can be positioned in-between reverse engineering and process mining. An implementation of the proposed approach is available as a ProM plugin. Experimental results based on real-life (software) event logs demonstrate the feasibility and usefulness of the approach and show the huge potential to speed up discovery by exploiting the available hierarchy.Comment: Extended version (14 pages total) of the paper Recursion Aware Modeling and Discovery For Hierarchical Software Event Log Analysis. This Technical Report version includes the guarantee proofs for the proposed discovery algorithm

Extracting mathematical semantics from LaTeX documents

We report on a project to use SGLR parsing and term rewriting with ELAN4 to extract the semantics of mathematical formulas from a LaTeX document and representing them in MathML. The LaTeX document we used is part of the Digital Library of Mathematical Functions (DLMF) project of the US National Institute of Standards and Technology (NIST) and obeys project-specific conventions, which contains macros for mathematical constructions, among them 200 predefined macros for special functions, the subject matter of the project. The SGLR parser can parse general context-free languages, which suffices to extract the structure of mathematical formulas from calculus that are written in the usual mathematical style, with most parentheses and multiplication signs omitted. The parse tree is then rewritten into a more concise and uniform internal syntax that is used as the base for extracting MathML or other semantical information

Development of parsing tools for Casl using generic language technology

An environment for the Common Algebraic Specification Language CASL consists of independent tools. A number of CASL have been built using the algebraic formalism ASF+SDF and the+SDF Meta-Environment. CASL supports-defined syntax which is non-trivial to: ASF+SDF offers a powerful parsing(Generalized LR). Its interactive environment facilitates rapid complemented by early detection correction of errors. A number of core developed for the ASF+SDF-Environment can be reused in the context CASL. Furthermore, an instantiation of a format developed for the representation ASF+SDF specifications and terms provides a-specific exchange format

Extracting mathematical semantics from LaTeX documents

We report on a project to use SGLR parsing and term rewriting with ELAN4 to extract the semantics of mathematical formulas from a LaTeX document and representing them in MathML. The LaTeX document we used is part of the Digital Library of Mathematical Functions (DLMF) project of the US National Institute of Standards and Technology (NIST) and obeys project-specific conventions, which contains macros for mathematical constructions, among them 200 predefined macros for special functions, the subject matter of the project. The SGLR parser can parse general context-free languages, which suffices to extract the structure of mathematical formulas from calculus that are written in the usual mathematical style, with most parentheses and multiplication signs omitted. The parse tree is then rewritten into a more concise and uniform internal syntax that is used as the base for extracting MathML or other semantical information

Modular grammar specification

We establish a semantics for building grammars from a modularised specification in which modules are able to delete productions from imported nonterminals. Modules have import lists of nonterminals; some or all of an imported nonterminal's productions may be suppressed at import time. There are two basic import mechanisms which (a) reference or (b) clone an imported nonterminal's productions. One of our goals is to allow a precise answer to the question: ‘what character level language does this grammar generate’ in the face of difficult issues such as the mutual embedding of languages that have different whitespace and commenting conventions. Our technique is to automatically generate a character level grammar from grammars written at token level in the conventional way; the grammar is constructed from modules each of which may have its own whitespace convention. Keywords: Context free grammar; Modularity; Whitespace processin

SAMOS - A framework for model analytics and management

The increased popularity and adoption of model-* engineering paradigms, such as model-driven and model-based engineering, leads to an increase in the number of models, metamodels, model transformations and other related artifacts. This calls for automated techniques to analyze large collections of those artifacts to manage model-* ecosystems. SAMOS is a framework to address this challenge: it treats model-* artifacts as data, and applies various techniques—ranging from information retrieval to machine learning—to analyze those artifacts in a holistic, scalable and efficient way. Such analyses can help to understand and manage those ecosystems

HaliVer: Deductive Verification and Scheduling Languages Join Forces

The HALIVER tool integrates deductive verification into the popular scheduling language HALIDE, used for image processing pipelines and array computations. HALIVER uses VERCORS, a separation logic-based verifier, to verify the correctness of (1) the HALIDE algorithms and (2) the optimised parallel code produced by HALIDE when an optimisation schedule is applied to an algorithm. This allows proving complex, optimised code correct while reducing the effort to provide the required verification annotations. For both approaches, the same specification is used. We evaluated the tool on several optimised programs generated from characteristic HALIDE algorithms, using all but one of the essential scheduling directives available in HALIDE. Without annotation effort, HALIVER proves memory safety in almost all programs. With annotations HALIVER, additionally, proves functional correctness properties. We show that the approach is viable and reduces the manual annotation effort by an order of magnitude

HaliVer: Deductive Verification and Scheduling Languages Join Forces

The HaliVer tool integrates deductive verification into the popular scheduling language Halide, used for image processing pipelines and array computations. HaliVer uses Vercors, a separation logic-based verifier, to verify the correctness of (1) the Halide algorithms and (2) the optimised parallel code produced by \halide when an optimisation schedule is applied to the algorithm. This allows proving complex, optimised code correct while reducing the effort to provide the required verification annotations. For both approaches, the same specification is used. We evaluated the tool on several optimised programs generated from characteristic Halide algorithms, using all but one of the essential scheduling directives available in Halide. Without annotation effort, Haliver proves memory safety in almost all programs. With annotations Haliver, additionally, proves functional correctness properties. We show that the approach is viable and reduces the manual annotation effort by an order of magnitude

DRAFT-What you always wanted to know but could not find about block-based environments

Block-based environments are visual programming environments, which are becoming more and more popular because of their ease of use. The ease of use comes thanks to their intuitive graphical representation and structural metaphors (jigsaw-like puzzles) to display valid combinations of language constructs to the users. Part of the current popularity of block-based environments is thanks to Scratch. As a result they are often associated with tools for children or young learners. However, it is unclear how these types of programming environments are developed and used in general. So we conducted a systematic literature review on block-based environments by studying 152 papers published between 2014 and 2020, and a non-systematic tool review of 32 block-based environments. In particular, we provide a helpful inventory of block-based editors for end-users on different topics and domains. Likewise, we focused on identifying the main components of block-based environments, how they are engineered, and how they are used. This survey should be equally helpful for language engineering researchers and language engineers alike