Quiver — An intelligent decision support system for software architecture and design

These concepts of Decision making and the approach towards informed decisions have evolved into the class of systems called Decision Support Systems(DSS). The four factors involving accuracy of the model, representation format, response time and cognitive style, are critical to success of these systems. The most important characteristic for quality of the system is the accuracy of the model. Successful DSS make judgements that model the best human technicians. Over the years the focus on learning from domain experts and prediction or inference has increased manyfold. So is the technological advancement in these areas. Software Engineering has evolved over many years but stays significantly human centric as it relies significantly on the technical decisions made by humans. Modeling the problem statement and arriving at architecture and design fuses in the minds of software architects and designers and considered highly human centric. It is identified that improved architectural decision making involving reference architectures with context, solution and rationale well explained using decision trees could benefit decision making. Considering the insights gained from previous work and the generic nature of existing frameworks and architectures, the authors propose an Intelligent Decision-making Support System in the area of Software Architecture and Design.

I. Introduction

Decision making and a systematic approach towards informed decision making have been a much investigated subject in cognitive science and management disciplines. The concept of computer based decision support was introduced as early as 1970 (Little 1970 and Scott 1971). The steps involving performing evaluation or comparison, selecting from the alternatives, applying the course of action and learning based on decisions represent the core process which is widely discussed (Simon 1987, Haber 1990). It is a recognized fact that the executive decision makers are today more than ever hindered by the complexity, uncertainty, risks, competitive environment parameters to name a few. The significance is so high that decisions have huge impact on the job security of executives (Rower and Davis 1996). The ability to identify the relevant factors from the noise or clutter is turning turning out to be business critical.