Computational intelligence and visual computing: an emerging technology for software engineering

 The discipline of Software Engineering is abstract and complex with all its endeavors being cast in a knowledge-intensive environment. It is not surprising that there have been a number of important initiatives that have attempted to address a burning need for solid development tools and comprehensive environments supporting an in-depth analysis. The objective of this study is to discuss a role of Computational Intelligence (CI) and visual computing being viewed as a sound methodological and algorithmic environment for knowledge-oriented Software Engineering. The CI itself is regarded as a synergistic consortium of granular computing (including fuzzy sets) promoting abstraction, neurocomputing supporting various learning schemes and evolutionary computing providing important faculties of global optimization. By its very nature, CI embraces a diversity of design paradigms; in particular it promotes a top-down approach (when exploiting fuzzy sets first and afterwards working in the neural network environment) or bottom-up style (where these two technologies are used in a reverse order). Visual computing is inherently associated with CI: it is human-centric where fuzzy sets make visualization activities feasible. Fuzzy sets are treated as a graphic means of accepting information from users. They are regarded as a vehicle used to visualize results in a linguistic manner. Software Engineering and CI are highly compatible: they are knowledge-intensive, human-oriented, and have to deal with various manifestations of the abstract world of software constructs and thought processes. This multifaceted conceptual compatibility is a prerequisite for the development of vital synergistic links that bring the technology of CI into Software Engineering. The symbiosis accrues considerable benefits for both technologies by posing new categories of challenging and highly stimulating problems. The facet of visual computing is essential in handling of software processes and software products. The intent of this study is to provide a general overview of this new development in Software Engineering. In particular, we highlight a number of selected and most visible trends occurring at the junction of CI and Software Engineering. Furthermore we discuss several specific applications of the technology of CI to software cost estimation, analysis of software measures and neural models of software quality. Support from the Natural Sciences and Engineering Research Council of Canada (NSERC) and the Alberta Software Engineering Research Consortium (ASERC) is gratefully acknowledged.