Evolutionary Computation and Optimization Algorithms in Software Engineering

Evolutionary computation brings new tools for software engineering by informing the systematic, disciplined, quantifiable processes of developing, operating, and maintaining software. Evolutionary Computation and Optimization Algorithms in Software Engineering: Applications and Techniques lays the foundation for the successful integration of evolutionary computation into software engineering. It surveys techniques ranging from genetic algorithms, to swarm optimization theory, to ant colony optimization, demonstrating their uses and capabilities. These techniques are applied to aspects of software engineering such as software testing, quality assessment, reliability assessment, and fault prediction models, among others, to providing researchers, scholars and students with the knowledge needed to expand this burgeoning application.

Monica Chis received her BS degree in Computer Science from Babes-Bolyai University, Cluj-Napoca, Romania in 1995. She is currently Project Manager at SIEMENS IT Solutions and Services, Romania. She was working in a private University in Cluj-Napoca, Romania as Senior Lecturer. Her research activities focuses on data mining, computational intelligence and swarm intelligence, applications of evolutionary computation in data mining, software engineering, software engineering and evolutionary computation, e-learning, time series data mining, social networks. She has published research articles in book chapters and conference proceedings. She served on the program committee for international conferences and she is additional reviewer for international conferences and journals. She has some important collaboration with foreign companies in the field of project management, research and data analysis.