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Enhancing Software Development Process Quality based on Metrics Correlation and Suggestion

Topics: Application Software; Data-driven Software Engineering; Project Management; Quality Management; Requirements Engineering; Software and Systems Modeling; Software Development Lifecycle; Software Engineering Tools; Software Project Planning and Tracking

Authors: Sarah Dahab 1 ; Erika Silva 1 ; Stephane Maag 1 ; Ana Rosa Cavalli 2 and Wissam Mallouli 3

Affiliations: 1 SAMOVAR, Telecom SudParis, Université Paris-Saclay and France ; 2 SAMOVAR, Telecom SudParis, Université Paris-Saclay, France, Montimage R&D, Paris and France ; 3 Montimage R&D, Paris and France

Keyword(s): Software Engineering, Metrics Combination, Reuse, Suggestion, Correlation.

Related Ontology Subjects/Areas/Topics: Applications ; Artificial Intelligence ; Enterprise Information Systems ; Information Systems Analysis and Specification ; Knowledge Management and Information Sharing ; Knowledge-Based Systems ; Operational Research ; Project Management ; Requirements Engineering ; Symbolic Systems

Abstract: To improve software quality, it is necessary to introduce new metrics with the required detail and increased expressive power, in order to provide valuable information to the different actors of software development. In this paper we present two approaches based on metrics that contribute to improve software quality development. Both approaches are complementary and are focused on the combination, reuse and correlation of metrics. They suggest to the user indications of how to reuse metrics and provide recommendations after the application of metrics correlation. They have been applied to selected metrics on software maintainability, safety, security etc. The approaches have been implemented in two tools, Metrics Suggester and MINT. Both approaches and tools are part of the ITEA3 MEASURE project and they have been integrated into the project platform. To illustrate its application we have created different scenarios on which both approaches are applied. Results show that both approac hes are complementary and can be used to improve the software process. (More)

CC BY-NC-ND 4.0

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Paper citation in several formats:
Dahab, S.; Silva, E.; Maag, S.; Cavalli, A. and Mallouli, W. (2018). Enhancing Software Development Process Quality based on Metrics Correlation and Suggestion. In Proceedings of the 13th International Conference on Software Technologies - ICSOFT; ISBN 978-989-758-320-9; ISSN 2184-2833, SciTePress, pages 120-131. DOI: 10.5220/0006856501540165

@conference{icsoft18,
author={Sarah Dahab. and Erika Silva. and Stephane Maag. and Ana Rosa Cavalli. and Wissam Mallouli.},
title={Enhancing Software Development Process Quality based on Metrics Correlation and Suggestion},
booktitle={Proceedings of the 13th International Conference on Software Technologies - ICSOFT},
year={2018},
pages={120-131},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006856501540165},
isbn={978-989-758-320-9},
issn={2184-2833},
}

TY - CONF

JO - Proceedings of the 13th International Conference on Software Technologies - ICSOFT
TI - Enhancing Software Development Process Quality based on Metrics Correlation and Suggestion
SN - 978-989-758-320-9
IS - 2184-2833
AU - Dahab, S.
AU - Silva, E.
AU - Maag, S.
AU - Cavalli, A.
AU - Mallouli, W.
PY - 2018
SP - 120
EP - 131
DO - 10.5220/0006856501540165
PB - SciTePress