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Authors: Sarah A. Dahab ; Juan Jose Hernandez Porras and Stephane Maag

Affiliation: Telecom SudParis, France

Keyword(s): Software Metrics, Formal Measurement, Software Measurement, Measurement Plan, Formal Software Measurement, SVM, Big Data.

Related Ontology Subjects/Areas/Topics: Cross-Feeding between Data and Software Engineering ; Model-Driven Engineering ; Software Engineering ; Software Engineering Methods and Techniques ; Software Metrics ; Software Project Management

Abstract: The software measurement is an integral part of the software engineering process. With the rise of the software system and their complexity distributed through diverse development phases, the software measurement process has to deal with more management and performance constraints. In fact, the current software measurement process is fixed and manually planned at the beginning of the project and has to manage a huge amount of data resulting from the complexity of the software. Thereby, measuring software becomes costly and heavy. In addition, the implementation of the measures is dependent on the developer and reduce the scalability, maintainability and the interoperability of the measurement process. It becomes expert-dependent and thus more costly. In order to tackle these difficulties, first, we propose in this paper a formal software measurement implementation model based on the standard measurement specification SMM. Then, a software measurement plan suggestion framework based o n a learning-based automated analysis. (More)

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Paper citation in several formats:
Dahab, S.; Porras, J. and Maag, S. (2018). A Novel Formal Approach to Automatically Suggest Metrics in Software Measurement Plans. In Proceedings of the 13th International Conference on Evaluation of Novel Approaches to Software Engineering - ENASE; ISBN 978-989-758-300-1; ISSN 2184-4895, SciTePress, pages 283-290. DOI: 10.5220/0006710902830290

@conference{enase18,
author={Sarah A. Dahab. and Juan Jose Hernandez Porras. and Stephane Maag.},
title={A Novel Formal Approach to Automatically Suggest Metrics in Software Measurement Plans},
booktitle={Proceedings of the 13th International Conference on Evaluation of Novel Approaches to Software Engineering - ENASE},
year={2018},
pages={283-290},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006710902830290},
isbn={978-989-758-300-1},
issn={2184-4895},
}

TY - CONF

JO - Proceedings of the 13th International Conference on Evaluation of Novel Approaches to Software Engineering - ENASE
TI - A Novel Formal Approach to Automatically Suggest Metrics in Software Measurement Plans
SN - 978-989-758-300-1
IS - 2184-4895
AU - Dahab, S.
AU - Porras, J.
AU - Maag, S.
PY - 2018
SP - 283
EP - 290
DO - 10.5220/0006710902830290
PB - SciTePress