Search-Based Software Engineering
Springer International Publishing (Verlag)
978-3-319-09939-2 (ISBN)
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.
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.
Erscheint lt. Verlag | 8.8.2014 |
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Reihe/Serie | Lecture Notes in Computer Science | Programming and Software Engineering |
Zusatzinfo | XXXII, 268 p. 75 illus. |
Verlagsort | Cham |
Sprache | englisch |
Maße | 155 x 235 mm |
Gewicht | 462 g |
Themenwelt | Mathematik / Informatik ► Informatik ► Software Entwicklung |
Schlagworte | Algorithm analysis and problem complexity • Aspect-Oriented Programming • combinatorial optimization • Design Patterns • Genetic algorithms • genetic programming • machine learning • meta-heuristic optimization • Multi-Objective Optimization • Refactoring • Requirements Engineering • Reverse Engineering • search based software engineering • software architecture • Software engineering • Software Product Lines • Software Testing • Variability modeling |
ISBN-10 | 3-319-09939-6 / 3319099396 |
ISBN-13 | 978-3-319-09939-2 / 9783319099392 |
Zustand | Neuware |
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