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Design of software architecture is intellectually one of the most demanding tasks in software engineering. This paper proposes an approach to automatically synthesize software architecture using genetic algorithms. The technique applies architectural patterns for mutations and quality metrics for evaluation, producing a proposal for a software architecture on the basis of functional requirements given...
The generation of software architecture using genetic algorithms is studied with architectural styles and patterns as mutations. The main input for the genetic algorithm is a rudimentary architecture representing the functional decomposition of the system, obtained as a refinement of use cases. Using a fitness function tuned for desired weights of simplicity, efficiency and modifiability, the technique...
Current trends in information technology emphasize the need of flexible systems that are able to adapt to their changing environment. The aim of this paper is to develop an infrastructure for architecture level self-adaptation, and to study its applicability in the case of distributed systems. The approach is based on dynamically inserted and removed design solutions. The built infrastructure provides...
Genetic algorithms have become a popular heuristic technique to solve difficult search problems. However, in multi-objective problem solving, like software architecture generation, the basic variation mechanisms of genetic algorithms (mutation and crossover) tend to lead to mediocre solutions as the evolution favors balancing of several quality properties. In this paper, we explore the acceleration...
A possible approach to partly automated software architecture design is the application of heuristic search methods like genetic algorithms. However, traditional genetic algorithms use a single fitness function with weighted terms for different quality attributes. This is inadequate for software architecture design that has to satisfy multiple incomparable quality requirements simultaneously. To overcome...
Techniques exist to synthesize software architecture using genetic algorithms that employ transformations based on mutations and crossover. In this paper, we demonstrate that complementary crossover can significantly improve this technique. We study two versions of complementary crossover, one in which parents are selected so that they complement each other but the genes are inherited randomly from...
This survey investigates search-based approaches to software design. The basics of the most popular meta-heuristic algorithms are presented as background to the search-based viewpoint. Software design is considered from a wide viewpoint, including topics that can also be categorized as software maintenance or re-engineering. Search-based approaches have been used in research from the high architecture...
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