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.
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