ManagemOnt: A Semantic Approach to Software Engineering Management Process

Software engineering processes, today, tend to have a gap between the assets because of non-manageable experiences in the domain which causes the organizations to fail in process improvement activities and software engineering practices in terms of time and cost. The data maintained in current software engineering process models, such as project and resource plans, documents, metrics, etc. is syntactic and out of interpretation. The lack of interpretation results in redundant data for an asset of software engineering process. It is well-known for years that each asset in software engineering domain generates an output which is an input for another asset in the domain in a logically related manner. This approach to software engineering process assets reveals knowledge-based software engineering process modeling via inference and reuse of domain experiences. It is proposed to model semantic software engineering processes and their assets by means of ontologies to achieve the inference and reuse of domain knowledge in a way different from syntactic approach. In order to trigger semantic software engineering processes, project planning activity is prototyped from software engineering management process since this activity almost comprises the mentioned process data because of its position in software engineering processes and practices.

[1]  Banu Diri,et al.  Software Process Ontology , 2007, IMECS.

[2]  Robert Meersman,et al.  On Using Conceptual Data Modeling for Ontology Engineering , 2004, J. Data Semant..

[3]  Martin K. Purvis,et al.  UML as an Ontology Modelling Language , 1999, Intelligent Information Integration.

[4]  Nigel Shadbolt,et al.  Resource Description Framework (RDF) , 2009 .

[5]  Roy T. Fielding,et al.  Uniform Resource Identifiers (URI): Generic Syntax , 1998, RFC.

[6]  Roger S. Pressman,et al.  Software Engineering: A Practitioner's Approach , 1982 .

[7]  Robert Meersman,et al.  Data modelling versus ontology engineering , 2002, SGMD.

[8]  Stephen P Gardner,et al.  Ontologies and semantic data integration. , 2005, Drug discovery today.

[9]  Isabel F. Cruz,et al.  The role of ontologies in data integration , 2005 .

[10]  Raghu Ramakrishnan,et al.  Database Management Systems , 1976 .

[11]  Stefano Spaccapietra,et al.  Journal on Data Semantics I , 2003, Lecture Notes in Computer Science.

[12]  Mario Piattini,et al.  Ontologies for Software Engineering and Software Technology , 2010 .

[13]  Brian McBride,et al.  Jena: A Semantic Web Toolkit , 2002, IEEE Internet Comput..

[14]  R. Watson,et al.  Data Management , 1980, Bone Marrow Transplantation.

[15]  Nick Roussopoulos,et al.  Metadata Management , 1986, Computer.

[16]  Ali Behforooz,et al.  Software engineering fundamentals , 1996 .

[17]  Ian Horrocks,et al.  Position paper: a comparison of two modelling paradigms in the Semantic Web , 2006, WWW '06.

[18]  N. F. Noy,et al.  Ontology Development 101: A Guide to Creating Your First Ontology , 2001 .

[19]  Shelley Powers,et al.  Practical RDF , 2003 .

[20]  Hector Garcia-Molina,et al.  Distributed Databases , 1995, Encyclopedia of GIS.

[21]  Jeff Z. Pan,et al.  Resource Description Framework , 2020, Definitions.