Doutorado em Ciência da Computação

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Navegando Doutorado em Ciência da Computação por Autor "Amorim, Fernanda Araujo Baião"

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    Interoperabilidade semântica entre códigos fonte baseada em ontologia
    (Universidade Federal do Espírito Santo, 2021-11-24) Aguiar, Camila Zacché de; Souza, Vitor Estevão Silva; https://orcid.org/0000000318695704; http://lattes.cnpq.br/2762374760685577; https://orcid.org/0000-0001-7945-6489; http://lattes.cnpq.br/1194248632540081; Garcia, Rogerio Eduardo; https://orcid.org/0000-0003-1248-528X; http://lattes.cnpq.br/8031012573259361; Amorim, Fernanda Araujo Baião; https://orcid.org/0000-0001-7932-7134; http://lattes.cnpq.br/5068302552861597; Barcellos, Monalessa Perini; https://orcid.org/0000-0002-6225-9478; http://lattes.cnpq.br/8826584877205264; Guizzardi, Giancarlo; https://orcid.org/0000-0002-3452-553X; http://lattes.cnpq.br/5297252436860003
    The source code is a well-formed sequence of computer instructions expressed in a programming language, composed of a set of symbols organized with their respective syntax and semantics. The different representations of source code in programming languages create a heterogeneous context, as does the use of multiple programming languages in a single source code. This scenario prevents the direct exchange of information between source codes of different programming languages, requiring specialized knowledge of their languages and diversity of tools and practices. In this sense, as a way to mitigate heterogeneity between programming languages, we apply semantic interoperability to ensure that shared information have their meanings understood and operationalized by code written in different source programming languages. To do this, we adopt ontologies to ensure uniform interpretations that share a consistent common commitment about the source code domain. In addition to acting as an interlanguage between different source codes, ontologies are widely accepted in the literature as tools to provide semantics and interoperability between entities with different natures. To apply ontologies to source code interoperability, this research presents a source code ontology network called SCON — Source Code Ontology Network and a method for source code interoperability based on ontology called OSCIN — Ontology-Based Source Code Interoperability. While SCON semantically represents common and consensual concepts about the domain of source code, regardless of the programming language, OSCIN aims to apply this representation for different purposes in a unified way. The method is based on the source code subdomain that will be represented, the programming language that it is capable of handling, and the application purpose that will be applied. In order to provide a set of solutions to support the application of the OSCIN method in different source code subdomains, programming languages and application purposes, this research presents the OSCINF framework — Ontology-based Source Code Interoperability Framework, which generates the artifacts expected by the OSCIN method and defines the SABiOS method — Systematic Approach for Building Ontologies with Scrum for the construction of well-founded ontologies. Finally, this research evaluates source code interoperability by applying the OSCIN method to detect smells, software metrics and code migration in source codes from different programming languages.
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    Transforming ontology-based conceptual models into relational schemas
    (Universidade Federal do Espírito Santo, 2023-03-29) Guidoni, Gustavo Ludovico; Almeida, Joao Paulo Andrade; https://orcid.org/0000-0002-9819-3781; http://lattes.cnpq.br/4332944687727598; https://orcid.org/0009-0009-0932-4769; http://lattes.cnpq.br/6446725385317269; Souza, Vitor Estevao Silva; https://orcid.org/0000000318695704; http://lattes.cnpq.br/2762374760685577; Campos, Maria Luiza Machado; Amorim, Fernanda Araujo Baião; https://orcid.org/0000-0001-7932-7134; http://lattes.cnpq.br/5068302552861597; Barcellos, Monalessa Perini; http://lattes.cnpq.br/8826584877205264
    Despite the relevant contributions of ontology-based conceptual modeling and the widespread use of relational schemas, the combination of these two technologies has not yet received due attention. Among the conceptual modeling technologies, OntoUML stands out as a language to describe a domain of interest, having as its main niche the formulation and propagation of knowledge. Conceptual models produced with OntoUML can be seen as a “starting point” for other artifacts, such as relational schemas in a database realization. To produce a relational schema from the conceptual model in an automated way, it is necessary to bridge the gap between a series of constructs. The current literature provides some object-relational transformation approaches that could, in principle, be applied to ontology-driven conceptual models, such as those produced in OntoUML. However, there are important constructs that are not covered by such approaches that must be addressed. Most of the existing object-relational transformation approaches fail to support conceptual models that: (i) include overlapping or incomplete generalizations; (ii) support dynamic classication; (iii) have multiple inheritance; and (iv) have orthogonal hierarchies. This is because many of the approaches discussed in the literature assume primitives underlying object-oriented programming languages (instead of conceptual modeling languages). To solve this gap, this work aims to understand the forces that govern classical strategies for transforming class hierarchies into relational schemas, while raising some ontological meta-properties that characterize the classes in these models (like sortality and rigidity). The information obtained is used to guide the transformation of the conceptual model into a relational schema in order to avoid some problems in existing approaches, leading to the novel one table per kind strategy. In addition to automating relational schema generation, we also propose an automated ontology-based data access mapping for the resulting relational schema, in order to provide access data in terms of the original conceptual model, and hence queries can be written at a high level of abstraction (in SPARQL), independently of the transformation strategy selected. Further, we forward engineer additional constraints along with the transformed schema (ultimately implemented as triggers) to guarantee that the semantics of the source model is respected. The proposed approach is contrasted with dominant transformation approaches in the literature from the perspectives of: (i) the supported conceptual modeling primitives; (ii) size of the resulting schema; (iii) query answering performance; and (iv) usability of the resulting schema, for which an empirical study is reported.