TY - GEN
T1 - Extensible and automated model-evaluations with INProVE
AU - Kemmann, Sören
AU - Kuhn, Thomas
AU - Trapp, Mario
PY - 2011
Y1 - 2011
N2 - Model-based development is gaining more and more importance for the creation of software-intensive embedded systems. One important aspect of software models is model quality. This does not imply functional correctness, but non-functional properties, such as maintainability, scalability, extensibility. Lots of effort was put into development of metrics for control flow models. In the embedded systems domain however, domain specific- and data flow languages are commonly applied for model creation. For these languages, existing metrics are not applicable. Domain and project specific quality metrics therefore are informally defined; tracking conformance to these metrics is a manual and effort consuming task. To resolve this situation, we developed INProVE. INProVE is a model-based framework that supports definition of quality metrics in an intuitive, yet formal notion. It provides automated evaluation of design models through its indicators. Applied in different industry projects to complex models, INProVE has proven its applicability for quality assessment of data flow-oriented design models not only in research, but also in practice.
AB - Model-based development is gaining more and more importance for the creation of software-intensive embedded systems. One important aspect of software models is model quality. This does not imply functional correctness, but non-functional properties, such as maintainability, scalability, extensibility. Lots of effort was put into development of metrics for control flow models. In the embedded systems domain however, domain specific- and data flow languages are commonly applied for model creation. For these languages, existing metrics are not applicable. Domain and project specific quality metrics therefore are informally defined; tracking conformance to these metrics is a manual and effort consuming task. To resolve this situation, we developed INProVE. INProVE is a model-based framework that supports definition of quality metrics in an intuitive, yet formal notion. It provides automated evaluation of design models through its indicators. Applied in different industry projects to complex models, INProVE has proven its applicability for quality assessment of data flow-oriented design models not only in research, but also in practice.
KW - Automated Quality Evaluation
KW - Model Quality
KW - Quality Assurance
KW - Quality Evolution
KW - Quality Modeling
KW - Simulink
UR - http://www.scopus.com/inward/record.url?scp=79959944870&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-21652-7_12
DO - 10.1007/978-3-642-21652-7_12
M3 - Conference contribution
AN - SCOPUS:79959944870
SN - 9783642216510
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 193
EP - 208
BT - System Analysis and Modeling
T2 - 6th International Workshop on System Analysis and Modeling, SAM 2010, Co-located with the 13th ACM/IEEE International Conference on Model-Driven Engineering Languages and Systems, MODELS
Y2 - 4 October 2010 through 5 October 2010
ER -