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Line 260: \| url = http://www0.cs.ucl.ac.uk/staff/w.langdon/ftp/papers/Langdon_2013_ieeeTEC.pdf }}</ref> A recent work by Basios et al. shows that by optimising the data structure, Google Guava found 9% improvement on execution time, 13% improvement on memory consumption and 4% improvement on CPU usage separately.<ref>{{cite book\|last1=Basios\|first1=Michail\|last2=Li\|first2=Lingbo\|last3=Wu\|first3=Fan\|last4=Kanthan\|first4=Leslie\|last5=Barr\|first5=Earl T.\|title=Search Based Software Engineering \|chapter=Optimising Darwinian Data Structures on Google Guava~~\|journal=Search~~ ~~Based Software Engineering~~\|volume=10452\|date=9 September 2017\|pages=161–167\|doi=10.1007/978-3-319-66299-2_14\|language=en\|series=Lecture Notes in Computer Science\|isbn=978-3-319-66298-5\|url=http://discovery.ucl.ac.uk/10062895/1/ssbse_dariwnian_guava.pdf}}</ref> ===Project management=== Line 284: ==Tools== Tools available for SBSE include OpenPAT,<ref> {{cite ~~journal~~book \|last1 = Mayo \|first1 = M. \|last2 = Spacey \|first2 = S. \|title = Search Based Software Engineering \|~~title~~ chapter = Predicting Regression Test Failures Using Genetic Algorithm-Selected Dynamic Performance Analysis Metrics ~~\|journal = Proceedings of the 5th International Symposium on Search-Based Software Engineering (SSBSE)~~ \|series = Lecture Notes in Computer Science \|volume = 8084 Line 296: \|year = 2013 \|doi = 10.1007/978-3-642-39742-4_13 \|chapter-url= https://researchcommons.waikato.ac.nz/bitstream/10289/7763/1/SBSE13.pdf \|hdl= 10289/7763 \|isbn = 978-3-642-39741-7

Search-based software engineering: Difference between revisions