An interdisciplinary model of complexity in embedded intelligent real-timesystems

Embedded Intelligent Real-Time Systems (EIRTS) are proliferating in many sa fety-critical large-scale systems where safety and reliability are importan t. EIRTS are often introduced in safety-critical large-scale systems to imp rove the reliability and safety, although, in many cases, they also increas e the system's complexity. Defining, understanding, and measuring the compl exity in EIRTS can aid us in designing and building more reliable and effec tive EIRTS, particularly in safety-critical settings. In this paper, we focus on the challenges associated with modeling and meas urement of complexity in EIRTS and the possible impact areas of this comple xity in safety-critical large-scale settings. We propose an interdisciplina ry model for EIRTS complexity that shows four different complexities, metri cs for measuring them, and impact areas for each complexity type. An applic ation of our model to a real-life EIRTS is also shown along with quantifica tion and operationalization of architectural/structural complexity which is one of four proposed complexities in our model. (C) 2001 Elsevier Science B.V. All rights reserved.