Generation of Tests for Programming Challenge Tasks Using Helper-Objectives

Arina Buzdalova, Maxim Buzdalov, Vladimir Parfenov

Research output: Chapter in Book/Report/Conference proceedingConference Proceeding (Non-Journal item)

Abstract

Generation of performance tests for programming challenge tasks is considered. A number of evolutionary approaches are compared on two different solutions of an example problem. It is shown that using helper-objectives enhances evolutionary algorithms in the considered case. The general approach involves automated selection of such objectives.

Original languageEnglish
Title of host publicationSearch Based Software Engineering
Subtitle of host publication5th International Symposium, SSBSE 2013, St. Petersburg, Russia, August 24-26, 2013. Proceedings
EditorsGünther Ruhe, Yuanyuan Zhang
PublisherSpringer Nature
Pages300-305
Number of pages6
ISBN (Electronic)978-3-642-39742-4, 3642397425
ISBN (Print)978-3-642-39741-7, 3642397417
DOIs
Publication statusPublished - 19 Jul 2013
Externally publishedYes

Publication series

NameLecture Notes in Computer Science
PublisherSpringer Nature
Volume8084
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Keywords

  • test generation
  • programming challenges
  • multi-objective evolutionary algorithms
  • multi-objectivization
  • helper-objectives

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