"Economics-driven Software Architecture" presents a guide for engineers and architects who need to understand the economic impact of architecture design decisions: the long term and strategic viability, cost-effectiveness, and sustainability of applications and systems. Economics-driven software development can increase quality, productivity, and profitability, but comprehensive knowledge is needed to understand the architectural challenges involved in dealing with the development of large, architecturally challenging systems in an economic way.

This book covers how to apply economic considerations during the software architecting activities of a project. Architecture-centric approaches to development and systematic evolution, where managing complexity, cost reduction, risk mitigation, evolvability, strategic planning and long-term value creation are among the major drivers for adopting such approaches. It assists the objective assessment of the lifetime costs and benefits of evolving systems, and the identification of legacy situations, where architecture or a component is indispensable but can no longer be evolved to meet changing needs at economic cost. Such consideration will form the scientific foundation for reasoning about the economics of nonfunctional requirements in the context of architectures and architecting.
Familiarizes readers with essential considerations in economic-informed and value-driven software design and analysis Introduces techniques for making value-based software architecting decisionsProvides readers a better understanding of the methods of economics-driven architecting

This book constitutes the refereed proceedings of the Fifth International Symposium on Search-Based Software Engineering, SSBSE 2013, held in St. Petersburg, Russia. The 14 revised full papers, 6 revised short papers, and 6 papers of the graduate track presented together with 2 keynotes, 2 challenge track papers and 1 tutorial paper were carefully reviewed and selected from 50 initial submissions. Search Based Software Engineering (SBSE) studies the application of meta-heuristic optimization techniques to various software engineering problems, ranging from requirements engineering to software testing and maintenance.