Towards Self-Adaptive Software-Intensive Legacy Systems

Abstract

Software Legacy systems typically refer to large, complex systems that have evolved to a state where they significantly resist further modification and evolution. Over the past decade, the life of many of these cash cows of the software industry has been extended by migrating them to modern platforms. Recently, in part due to the proliferation of the Web, those same systems seem to be morphing again into highly configurable systems of systems. According to a recent SEI study, software-intensive systems of systems are likely to evolve into Ultra-Large-Scale (ULS) Systems. In this talk we will argue that software-intensive legacy systems need to morph into self-adaptive and self-managing systems to be able to cope with the challenges of continuous evolution. The simultaneous explosion of information and integration of technology and the continuous evolution from software intensive systems to systems of systems to ULS systems requires new and innovative approaches for building, running and managing software systems. A consequence of this continuous evolution is that software systems must become more versatile, flexible, resilient, dependable, robust, continuously available, energy-efficient, recoverable, customizable, self-healing, configurable, or self- optimizing by adapting to changing contexts and environments. One of the most promising approaches to achieving such properties is to equip software systems with self-adaptation mechanisms. The challenge therefore for the software reverse engineering and reengineering communities is to investigate methods and techniques to instrument software-intensive systems with monitoring and self-adaptive mechanisms.