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Accommodating Adaptive Systems Complexity with Change Tolerance

  • Shawn BohnerEmail author
  • Ramya Ravichandar
  • Andrew Milluzzi

Abstract

As software systems grow in size and complexity, understanding and evolving them entails engineering capabilities that are change-tolerant. Inherent complexities make them susceptible to change when subjected to the vagaries of user needs, technology advances, market demands, and other change inducing factors. Today’s software often reflects adaptive systems complexity. Like the immune system, social systems, and colonies of ants, complexities often start with fuzzy rather than the rigid boundaries found in more mechanical systems. As our understanding of these systems evolve, there are natural transitions where complexity is injected to simplify a solution. As we introduce potential solutions to a problem space, the selected solution may inject potential complexities (e.g., the use of a database server simplifies one problem for the handling of data, but introduces an evolution complexity as the bow wave of platform complexities are now injected). Similarly, software is embedded within other systems and must co-evolve. This calls for an understanding and tracking of adaptive system complexity from the early stages of the life cycle. Model-Based Engineering shows promise for managing change tolerance in the evolution of long-lived software systems. Starting with Domain and Capabilities Engineering defining long-lived components of a system establishes some sense of change tolerance. In this chapter, we examine coupling and cohesion in the journey from abstract “needs” through to architecture design. We introduce the notion of Capabilities—functional abstractions that are neither amorphous as user needs nor rigid as system requirements. Engineered capabilities are used to transition into an architecture that will accommodate change. We focus initially on capabilities engineering and detail an algorithm to identify Capabilities. We extend the notion of change tolerance to other representations as we model software systems in Model-Based Engineering. Our experiential results indicate that the Capabilities-based design is less susceptible to change impacts and thereby improves the system change-tolerance, and in turn reduces the overall complexity as the system evolves.

Keywords

Unify Modeling Language Transition Space Object Constraint Language Cohesion Measure Meta Object Facility 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgements

This work has been supported, in part, by the DARPA grant “AMIIE Phase II—Cougaar Model Driven Architecture Project,” (Cougaar Software, Inc.) subcontract number CSI-2003-01. We would like to acknowledge the efforts, ideas, and support that we received from our research team including Michael Hinchey, Todd Carrico, Tim Tschampel, Denis Gracanin, Lally Singh, and Nannan He. We want to thank students at Rose-Hulman Institute of Technology who participated in the FacePamphlet projects, and especially Rob Adams, whose work on the DSL version of FacePamphlet substantiated further our findings.

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Copyright information

© Springer-Verlag London Limited 2012

Authors and Affiliations

  • Shawn Bohner
    • 1
    Email author
  • Ramya Ravichandar
    • 2
  • Andrew Milluzzi
    • 1
  1. 1.Rose-Hulman Institute of TechnologyTerre HauteUSA
  2. 2.CISCO Inc.San JoseUSA

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