Search-based software engineering: Difference between revisions

Revision as of 20:29, 8 March 2018

Revision as of 20:40, 10 March 2018

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| url = http://www0.cs.ucl.ac.uk/staff/w.langdon/ftp/papers/Langdon_2013_ieeeTEC.pdf

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A recent work by Basios et al. shows that by optimising the data structure, Google Guava can found 9% improvement on execution time, 13% improvement on memory consumption and 4% improvement on CPU usage separately<ref>{{cite journal|last1=Basios|first1=Michail|last2=Li|first2=Lingbo|last3=Wu|first3=Fan|last4=Kanthan|first4=Leslie|last5=Barr|first5=Earl T.|title=Optimising Darwinian Data Structures on Google Guava|journal=Search Based Software Engineering|date=9 September 2017|pages=161–167|doi=10.1007/978-3-319-66299-2_14|url=https://link.springer.com/chapter/10.1007/978-3-319-66299-2_14|publisher=Springer, Cham|language=en}}</ref>. Another example is

FINCH (Fertile Darwinian Bytecode Harvester), a methodology for evolving Java bytecode, enabling the evolution of extant, unrestricted Java programs, or programs in other languages (Scala, Groovy, Jython, Kawa, JavaFX Script, Clojure) that compile to Java bytecode.<ref>M. Orlov and M. Sipper, [https://drive.google.com/file/d/0B6G3tbmMcpR4bFVYbWRWVGlDN28/view Flight of the FINCH through the Java wilderness], IEEE Transactions on Evolutionary Computation, vol. 15, no. 2, pp. 166-182, 2011. </ref> FINCH's designers proposed the idea of [http://www.moshesipper.com/darwinian-software-engineering.html Darwinian Software Engineering].

===Project management===