An empirical validation of the suite of metrics for object-relational data modelling. (27th December 2010)

• Record Type: Journal Article
• Authors: Justus, S.; Iyakutti, K.
• Is Part Of: International journal of intelligent information and database systems. Volume 5:Number 1(2011)
• Page Start: 49
• Page End: 80
• Publication Date: 2010-12-27
• Subjects: product metrics -- object-relational data modelling -- empirical validation -- knowledge systems -- product attributes -- knowledge management -- music expert systems -- knowledge modelling -- software metrics; Database management -- Computer programs -- Periodicals; Information retrieval -- Computer programs -- Periodicals; Information storage and retrieval systems -- Computer programs -- Periodicals; Artificial intelligence -- Periodicals; Expert systems (Computer science) -- Periodicals; Intelligent agents (Computer software) -- Periodicals; 006.33
• Languages: English
• ISSNs: 1751-5858

Abstract

The important constituent of improvement is the ability to measure, quantify, and authenticate the attributes by measuring several known and unknown, dependent and independent attributes of a product. Designing a software system is an engineering activity, which is not without measurement, and here is where product metrics are applied. In this work, a suite of object-relational metrics is defined, evaluated and formalised. The empirical validation of the metrics is carried with two case studies: knowledge management tool (KMT) and music expert system (MES). Four main, three allied and two derived metrics are empirically validated with KMT and two storage metrics are applied to the MES, which showed better results for the efficient storage and retrieval of such knowledge units. This complete suite of metrics for knowledge modelling will serve as footage for future research and practice, and will contribute to the knowledge of the software metric community.