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Publication . Fonseca, João Manuel Sousa; Pereira, Maria João; Henriques, Pedro Rangel

This paper presents a project whose main objective is to explore the Ontological-based development of Domain Specific Languages (DSL), more precisely, of their underlying Grammar. After reviewing the basic concepts characterizing Ontologies and Domain-Specific Languages, we introduce a tool, Onto2Gra, that takes profit of the knowledge described by the ontology and automatically generates a grammar for a DSL that allows to discourse about the domain described by that ontology. This approach represents a rigorous method to create, in a secure and effective way, a grammar for a new specialized language restricted to a concrete domain. The usual process of creating a grammar from the scratch is, as every creative action, difficult, slow and error prone; so this proposal is, from a Grammar Engineering point of view, of uttermost importance. After the grammar generation phase, the Grammar Engineer can manipulate it to add syntactic sugar to improve the final language quality or even to add semantic actions. The Onto2Gra project is composed of three engines. The main one is OWL2DSL, the component that converts an OWL ontology into an attribute grammar. The two additional modules are Onto2OWL, converts ontologies written in OntoDL (a light-weight DSL to describe ontologies) into standard OWL, and DDesc2OWL, converts domain instances written in the DSL generated by OWL2DSL into the initial OWL ontology.

2014Conference paper

Open access

From source code identifiers to natural language terms

Publication . Carvalho, Nuno Ramos; Almeida, José João; Henriques, Pedro Rangel; Pereira, Maria João

Program comprehension techniques often explore program identifiers, to infer knowledge about programs. The relevance of source code identifiers as one relevant source of information about programs is already established in the literature, as well as their direct impact on future comprehension tasks. Most programming languages enforce some constrains on identifiers strings (e.g., white spaces or commas are not allowed). Also, programmers often use word combinations and abbreviations, to devise strings that represent single, or multiple, domain concepts in order to increase programming linguistic efficiency (convey more semantics writing less). These strings do not always use explicit marks to distinguish the terms used (e.g., CamelCase or underscores), so techniques often referred as hard splitting are not enough. This paper introduces Lingua::IdSplitter a dictionary based algorithm for splitting and expanding strings that compose multi-term identifiers. It explores the use of general programming and abbreviations dictionaries, but also a custom dictionary automatically generated from software natural language content, prone to include application domain terms and specific abbreviations. This approach was applied to two software packages, written in C, achieving a f-measure of around 90% for correctly splitting and expanding identifiers. A comparison with current state-of-the-art approaches is also presented.

2015Journal article

Open access