Search-Based Software Engineering

This book constitutes the refereed proceedings of the 6th International Symposium on Search-Based Software Engineering, SSBSE 2014, held in Fortaleza, Brazil.
The 14 revised full papers presented together with 2 keynote addresses, 1 invited talk, 1 short paper, 3 papers of the graduate track, and 4 challenge track papers were carefully reviewed and selected from 51 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.

Inhalt

On the Effectiveness of Whole Test Suite Generation.- Detecting Program Execution Phases Using Heuristic Search.- On the Use of Machine Learning and Search-Based Software Engineering for Ill-Defined Fitness Function: A Case Study on Software Refactoring.- Producing Just Enough Documentation: The Next SAD Version Problem.- A Multi-model Optimization Framework for the Model Driven Design of Cloud Applications.- A Pattern-Driven Mutation Operator for Search-Based Product Line Architecture Design.- Mutation-Based Generation of Software Product Line Test Configurations.- Multi-objective Genetic Optimization for Noise-Based Testing of Concurrent Software.- Bi-objective Genetic Search for Release Planning in Support of Themes.- Combining Stochastic Grammars and Genetic Programming for Coverage Testing at the System Level.- Feature Model Synthesis with Genetic Programming.- A Robust Multi-objective Approach for Software Refactoring under Uncertainty.- Towards Automated A/B Testing.- Random-WeightedSearch-Based Multi-objective Optimization Revisited.- A New Learning Mechanism for Resolving Inconsistencies in Using Cooperative Co-evolution Model.- Improving Heuristics for the Next Release Problem through Landscape Visualization.- Machine Learning for User Modeling in an Interactive Genetic Algorithm for the Next Release Problem.- Transaction Profile Estimation of Queueing Network Models for IT Systems Using a Search-Based Technique.- Less is More: Temporal Fault Predictive Performance over Multiple Hadoop Releases.- Babel Pidgin: SBSE Can Grow and Graft Entirely New Functionality into a Real World System.- Pidgin Crasher: Searching for Minimised Crashing GUI Event Sequences.- Repairing and Optimizing Hadoop hashCode Implementations.