Show simple item record

dc.contributor.authorSarkar, Atri 17:37:49 (GMT) 17:37:49 (GMT)
dc.description.abstractA key challenge of the development and maintenance of configurable systems is to predict the performance of individual system variants based on the features selected. It is usually infeasible to measure the performance of all possible variants, due to feature combinatorics. Previous approaches predict performance based on small samples of measured variants, but it is still open how to dynamically determine an ideal sample that balances prediction accuracy and measurement effort. In this work, we adapt two widely-used sampling strategies for performance prediction to the domain of configurable systems and evaluate them in terms of sampling cost, which considers prediction accuracy and measurement effort simultaneously. To generate an initial sample, we develop two sampling algorithms. One based on a traditional method of t-way feature coverage, and another based on a new heuristic of feature-frequencies. Using empirical data from six real-world systems, we evaluate the two sampling algorithms and discuss trade-offs. Furthermore, we conduct extensive sensitivity analysis of the cost model metric we use for evaluation, and analyze stability of learning behavior of the subject systems.en
dc.publisherUniversity of Waterlooen
dc.subjectperformance predictionen
dc.subjectconfigurable systemsen
dc.subjectsampling techniquesen
dc.titleMeta-learning Performance Prediction of Highly Configurable Systems: A Cost-oriented Approachen
dc.typeMaster Thesisen
dc.pendingfalse R. Cheriton School of Computer Scienceen Scienceen of Waterlooen
uws-etd.degreeMaster of Mathematicsen
uws.contributor.advisorCzarnecki, Krzysztof
uws.contributor.affiliation1Faculty of Mathematicsen

Files in this item


This item appears in the following Collection(s)

Show simple item record


University of Waterloo Library
200 University Avenue West
Waterloo, Ontario, Canada N2L 3G1
519 888 4883

All items in UWSpace are protected by copyright, with all rights reserved.

DSpace software

Service outages