Software quality in artificial intelligence system

Abstract

The main objective of the study is to define the metrics to measure the quality of software in the architecture for an artificial intelligence system. The proposed architecture for measurement consists of four components; Task specification layer, problem solver layer, domain layer and an adapter layer. These four components are hierarchically organized in a layered fashion. In this architecture, the overall structure is decomposed into sub components, in a layered way such that a new layer can be added to the existing layer that can change the behavior of the system. The quality of components in the architecture are measured with metrics such as source code, depth of inheritance, number of paths, complexity level etc., These metrics are related to software quality characteristics suggested by ISO. This study is organized in the following way; Firstly, the study addresses the significance of software architecture in a software intensive AI system, the importance of quality of the software in the architecture and a layered architecture for artificial intelligence system. The secondly, the study addresses the relation ship between the quality characteristics and the metrics used for measuring the quality. The performance of the system with respect to functional requirement and nonfunctional requirements are measured and discussed. © 2007 Asian Network for Scientific Information.