Research output

Conference Paper (in Formal Publication) ()

Visualising the Search Landscape of the Triangle Program

Citation
Langdon WB, Veerapen N & Ochoa G (2017) Visualising the Search Landscape of the Triangle Program In: McDermott J, Castelli M, Sekanina L, Haasdijk E, García-Sánchez P (ed.) EuroGP 2017: Genetic Programming, Cham, Switzerland: Springer. The 20th European Conference on Genetic Programming (EuroGP), 19.4.2017 - 21.4.2017, Amsterdam, The Netherlands, pp. 96-113.

Abstract
High order mutation analysis of a software engineering benchmark, including schema and local optima networks, suggests program improvements may not be as hard to find as is often assumed. 1) Bit-wise genetic building blocks are not deceptive and can lead to all global optima. 2) There are many neutral networks, plateaux and local optima, nevertheless in most cases near the human written C source code there are hill climbing routes including neutral moves to solutions.

Keywords
genetic improvement; genetic algorithms; genetic programming; software engineering; heuristic methods; test equivalent higher order mutants; fitness landscape; local search

StatusPublished
EditorMcDermott J, Castelli M, Sekanina L, Haasdijk E, García-Sánchez P
AuthorsLangdon William B, Veerapen Nadarajen, Ochoa Gabriela
Title of seriesLecture Notes in Computer Science
Number in series10196
Publication date2017
Date of public distribution15/03/2017
Date accepted by journal09/01/2017
PublisherSpringer
Place of publicationCham, Switzerland
ISSN of series 0302-9743
ISBN 978-3-319-55695-6
eISBN 978-3-319-55696-3
LanguageEnglish
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