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World Conference on Information Systems and Technologies

WorldCIST'18 2018: Trends and Advances in Information Systems and Technologies pp 122–131Cite as

An Approach for Knowledge Extraction from Source Code (KNESC) of Typed Programming Languages

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 745))

Abstract

Knowledge extraction is the discovery of knowledge from structured and/or unstructured sources. This knowledge can be used to build or enrich a domain ontology. Source code is rarely used. But implementation platforms evolve faster than business logic and these evolutions are usually integrated directly into source code without updating the conceptual model. In this paper, we present a generic approach for knowledge extraction from source code of typed programming languages using Hidden Markov Models. This approach consist of the definition of the HMM so that it can be used to extract any type of knowledge from the source code. The method is experimented on EPICAM and GeoServer developed in Java and on MapServer developed in C/C++. Structural evaluation shows that source code contains a structure that permit to build a domain ontology and functional evaluation shows that source code contains more knowledge than those contained in both databases and meta-models.

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Author information

Authors and Affiliations

  1. UMMISCO, Faculty of Science, University of Yaoundé I, Yaoundé, Cameroon

    Azanzi Jiomekong

  2. EIR-IMTICE, Université Alioune Diop de Bambey, Bambey, Senegal

    Gaoussou Camara

Authors
  1. Azanzi Jiomekong
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  2. Gaoussou Camara
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Corresponding author

Correspondence to Azanzi Jiomekong .

Editor information

Editors and Affiliations

  1. Departamento de Engenharia Informática, Universidade de Coimbra, Coimbra, Portugal

    Álvaro Rocha

  2. College of Engineering, The Ohio State University, Columbus, OH, USA

    Hojjat Adeli

  3. DSI/EEUM, Universidade do Minho, Guimarães, Portugal

    Luís Paulo Reis

  4. DIMES, Università della Calabria, Arcavacata di Rende, Italy

    Sandra Costanzo

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© 2018 Springer International Publishing AG, part of Springer Nature

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Jiomekong, A., Camara, G. (2018). An Approach for Knowledge Extraction from Source Code (KNESC) of Typed Programming Languages. In: Rocha, Á., Adeli, H., Reis, L.P., Costanzo, S. (eds) Trends and Advances in Information Systems and Technologies. WorldCIST'18 2018. Advances in Intelligent Systems and Computing, vol 745. Springer, Cham. https://doi.org/10.1007/978-3-319-77703-0_12

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  • DOI: https://doi.org/10.1007/978-3-319-77703-0_12

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-77702-3

  • Online ISBN: 978-3-319-77703-0

  • eBook Packages: EngineeringEngineering (R0)

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