<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>5</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Doerr, Carola</style></author><author><style face="normal" font="default" size="100%">Bredeche, Nicolas</style></author><author><style face="normal" font="default" size="100%">Alba, Enrique</style></author><author><style face="normal" font="default" size="100%">Bartz-Beielstein, Thomas</style></author><author><style face="normal" font="default" size="100%">Brockhoff, Dimo</style></author><author><style face="normal" font="default" size="100%">Doerr, Benjamin</style></author><author><style face="normal" font="default" size="100%">Eiben, Gusz</style></author><author><style face="normal" font="default" size="100%">Epitropakis, Michael G.</style></author><author><style face="normal" font="default" size="100%">Fonseca, Carlos M.</style></author><author><style face="normal" font="default" size="100%">Guerreiro, Andreia</style></author><author><style face="normal" font="default" size="100%">Haasdijk, Evert</style></author><author><style face="normal" font="default" size="100%">Heinerman, Jacqueline</style></author><author><style face="normal" font="default" size="100%">Hubert, Julien</style></author><author><style face="normal" font="default" size="100%">Lehre, Per Kristian</style></author><author><style face="normal" font="default" size="100%">Malagò, Luigi</style></author><author><style face="normal" font="default" size="100%">Merelo, J. J.</style></author><author><style face="normal" font="default" size="100%">Miller, Julian</style></author><author><style face="normal" font="default" size="100%">Naujoks, Boris</style></author><author><style face="normal" font="default" size="100%">Oliveto, Pietro</style></author><author><style face="normal" font="default" size="100%">Picek, Stjepan</style></author><author><style face="normal" font="default" size="100%">Pillay, Nelishia</style></author><author><style face="normal" font="default" size="100%">Preuss, Mike</style></author><author><style face="normal" font="default" size="100%">Ryser-Welch, Patricia</style></author><author><style face="normal" font="default" size="100%">Squillero, Giovanni</style></author><author><style face="normal" font="default" size="100%">Stork, Jörg</style></author><author><style face="normal" font="default" size="100%">Sudholt, Dirk</style></author><author><style face="normal" font="default" size="100%">Tonda, Alberto</style></author><author><style face="normal" font="default" size="100%">Whitley, Darrell</style></author><author><style face="normal" font="default" size="100%">Zaefferer, Martin</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Handl, Julia</style></author><author><style face="normal" font="default" size="100%">Hart, Emma</style></author><author><style face="normal" font="default" size="100%">Lewis, Peter R.</style></author><author><style face="normal" font="default" size="100%">López-Ibáñez, Manuel</style></author><author><style face="normal" font="default" size="100%">Ochoa, Gabriela</style></author><author><style face="normal" font="default" size="100%">Paechter, Ben</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Tutorials at PPSN 2016</style></title><secondary-title><style face="normal" font="default" size="100%">Parallel Problem Solving from Nature – PPSN XIV: 14th International Conference, Edinburgh, UK, September 17-21, 2016, Proceedings</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2016</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1007/978-3-319-45823-6_95</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">Springer International Publishing</style></publisher><pub-location><style face="normal" font="default" size="100%">Cham</style></pub-location><pages><style face="normal" font="default" size="100%">1012–1022</style></pages><isbn><style face="normal" font="default" size="100%">978-3-319-45823-6</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">PPSN 2016 hosts a total number of 16 tutorials covering a broad range of current research in evolutionary computation. The tutorials range from introductory to advanced and specialized but can all be attended without prior requirements. All PPSN attendees are cordially invited to take this opportunity to learn about ongoing research activities in our field!</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>27</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Jerry Swan</style></author><author><style face="normal" font="default" size="100%">Michael G. Epitropakis</style></author><author><style face="normal" font="default" size="100%">John R. Woodward</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Gen-O-Fix: An embeddable framework for Dynamic Adaptive Genetic Improvement Programming</style></title></titles><dates><year><style  face="normal" font="default" size="100%">2014</style></year><pub-dates><date><style  face="normal" font="default" size="100%">01/2014</style></date></pub-dates></dates><number><style face="normal" font="default" size="100%">CSM-195</style></number><publisher><style face="normal" font="default" size="100%">Computing Science and Mathematics, University of Stirling</style></publisher><pub-location><style face="normal" font="default" size="100%">Stirling FK9 4LA, Scotland</style></pub-location><pages><style face="normal" font="default" size="100%">1-12</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Genetic Improvement Programming (GIP) is concerned with automating the burden of software maintenance, the most costly phase of the software lifecycle. We describe Gen-O-Fix, a GIP framework which allows a software system hosted on the Java Virtual Machine to be continually improved (e.g. make better predictions; pass more regression tests; reduce power consumption). It is the first exemplar of a dynamic adaptive GIP framework, i.e. it can improve a system as it runs. It is written in the Scala programming language and uses reflection to yield source-to-source transformation. One of the design goals for Gen-O-Fix was to create a tool that is user-centric rather than researcher-centric: the end-user is required only to provide a measure of system quality and the URL of the source code to be improved. We discuss potential applications to predictive, embedded and high-performance systems.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>5</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Kocsis, Zoltan A.</style></author><author><style face="normal" font="default" size="100%">Neumann, Geoff</style></author><author><style face="normal" font="default" size="100%">Swan, Jerry</style></author><author><style face="normal" font="default" size="100%">Epitropakis, Michael G.</style></author><author><style face="normal" font="default" size="100%">Brownlee, Alexander E. I.</style></author><author><style face="normal" font="default" size="100%">Haraldsson, Sami O.</style></author><author><style face="normal" font="default" size="100%">Bowles, Edward</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Le Goues, Claire</style></author><author><style face="normal" font="default" size="100%">Yoo, Shin</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Repairing and Optimizing Hadoop hashCode Implementations</style></title><secondary-title><style face="normal" font="default" size="100%">Search-Based Software Engineering: 6th International Symposium, SSBSE 2014, Fortaleza, Brazil, August 26-29, 2014. Proceedings</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2014</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1007/978-3-319-09940-8_22</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">Springer International Publishing</style></publisher><pub-location><style face="normal" font="default" size="100%">Cham</style></pub-location><pages><style face="normal" font="default" size="100%">259–264</style></pages><isbn><style face="normal" font="default" size="100%">978-3-319-09940-8</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">We describe how contract violations in Java TM hashCode methods can be repaired using novel combination of semantics-preserving and generative methods, the latter being achieved via Automatic Improvement Programming. The method described is universally applicable. When applied to the Hadoop platform, it was established that it produces hashCode functions that are at least as good as the original, broken method as well as those produced by a widely-used alternative method from the ‘Apache Commons’ library.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">M. A. Kaliakatsos-Papakostas</style></author><author><style face="normal" font="default" size="100%">M. G. Epitropakis</style></author><author><style face="normal" font="default" size="100%">M. N. Vrahatis</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Di Chio, Cecilia</style></author><author><style face="normal" font="default" size="100%">Brabazon, Anthony</style></author><author><style face="normal" font="default" size="100%">Di Caro, Gianni</style></author><author><style face="normal" font="default" size="100%">Drechsler, Rolf</style></author><author><style face="normal" font="default" size="100%">Farooq, Muddassar</style></author><author><style face="normal" font="default" size="100%">Grahl, Jörn</style></author><author><style face="normal" font="default" size="100%">Greenfield, Gary</style></author><author><style face="normal" font="default" size="100%">Prins, Christian</style></author><author><style face="normal" font="default" size="100%">Romero, Juan</style></author><author><style face="normal" font="default" size="100%">Squillero, Giovanni</style></author><author><style face="normal" font="default" size="100%">Tarantino, Ernesto</style></author><author><style face="normal" font="default" size="100%">Tettamanzi, Andrea</style></author><author><style face="normal" font="default" size="100%">Urquhart, Neil</style></author><author><style face="normal" font="default" size="100%">Uyar, A.</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Weighted Markov Chain Model for Musical Composer Identification</style></title><secondary-title><style face="normal" font="default" size="100%">Applications of Evolutionary Computation</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2011</style></year></dates><publisher><style face="normal" font="default" size="100%">Springer Berlin / Heidelberg</style></publisher><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Several approaches based on the ‘Markov chain model’ have been proposed to tackle the composer identification task. In the paper at hand, we propose to capture phrasing structural information from inter onset and pitch intervals of pairs of consecutive notes in a musical piece, by incorporating this information into a weighted variation of a first order Markov chain model. Additionally, we propose an evolutionary procedure that automatically tunes the introduced weights and exploits the full potential of the proposed model for tackling the composer identification task between two composers. Initial experimental results on string quartets of Haydn, Mozart and Beethoven suggest that the proposed model performs well and can provide insights on the inter onset and pitch intervals on the considered musical collection.</style></abstract></record></records></xml>