An investigation of distributed computing for combinatorial testing
Summary Combinatorial test generation, also called t‐way testing, is the process of generating sets of input parameters for a system under test, by considering interactions between values of multiple parameters. In order to decrease total testing time, there is an interest in techniques that generat...
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creator | La Chance, Edmond Hallé, Sylvain |
description | Summary
Combinatorial test generation, also called
t‐way testing, is the process of generating sets of input parameters for a system under test, by considering interactions between values of multiple parameters. In order to decrease total testing time, there is an interest in techniques that generate smaller test suites. In our previous work, we used graph techniques to produce high‐quality test suites. However, these techniques require a lot of computing power and memory, which is why this paper investigates distributed computing for
t‐way testing. We first introduce our distributed graph colouring method, with new algorithms for building the graph and for colouring it. Second, we present our distributed hypergraph vertex covering method and a new heuristic. Third, we show how to build a distributed IPOG algorithm by leveraging either graph colouring or hypergraph vertex covering as vertical growth algorithms. Finally, we test these new methods on a computer cluster and compare them to existing
t‐way testing tools.
Combinatorial test generation is the process of generating sets of input parameters for a system under test, by considering interactions between t values of multiple parameters; the paper investigates the use of distributed algorithms to generate such test suites. It proposes reductions of the
t‐way test suite generation to two problems on graphs and provides distributed algorithms to solve them; these algorithms are then used as vertical growth algorithms to build a distributed version of IPOG. Finally, we test these new methods on a computer cluster and compare them to existing
t‐way testing tools. |
doi_str_mv | 10.1002/stvr.1842 |
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Combinatorial test generation, also called
t‐way testing, is the process of generating sets of input parameters for a system under test, by considering interactions between values of multiple parameters. In order to decrease total testing time, there is an interest in techniques that generate smaller test suites. In our previous work, we used graph techniques to produce high‐quality test suites. However, these techniques require a lot of computing power and memory, which is why this paper investigates distributed computing for
t‐way testing. We first introduce our distributed graph colouring method, with new algorithms for building the graph and for colouring it. Second, we present our distributed hypergraph vertex covering method and a new heuristic. Third, we show how to build a distributed IPOG algorithm by leveraging either graph colouring or hypergraph vertex covering as vertical growth algorithms. Finally, we test these new methods on a computer cluster and compare them to existing
t‐way testing tools.
Combinatorial test generation is the process of generating sets of input parameters for a system under test, by considering interactions between t values of multiple parameters; the paper investigates the use of distributed algorithms to generate such test suites. It proposes reductions of the
t‐way test suite generation to two problems on graphs and provides distributed algorithms to solve them; these algorithms are then used as vertical growth algorithms to build a distributed version of IPOG. Finally, we test these new methods on a computer cluster and compare them to existing
t‐way testing tools.</description><identifier>ISSN: 0960-0833</identifier><identifier>EISSN: 1099-1689</identifier><identifier>DOI: 10.1002/stvr.1842</identifier><language>eng</language><publisher>Chichester: Wiley Subscription Services, Inc</publisher><subject>Algorithms ; Alliances ; Combinatorial analysis ; combinatorial testing ; Computer networks ; distributed computing ; Distributed processing ; Graph coloring ; Graph theory ; Parameters ; phi‐way testing ; test case generation ; Testing time</subject><ispartof>Software testing, verification & reliability, 2023-06, Vol.33 (4), p.n/a</ispartof><rights>2023 The Authors. published by John Wiley & Sons Ltd.</rights><rights>2023. This article is published under http://creativecommons.org/licenses/by-nc-nd/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c2922-abfdaa40eee40c6de91d7964d3973f319b20538681775de8f89d2eb52c2f12783</cites><orcidid>0000-0002-4406-6154</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1002%2Fstvr.1842$$EPDF$$P50$$Gwiley$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1002%2Fstvr.1842$$EHTML$$P50$$Gwiley$$Hfree_for_read</linktohtml><link.rule.ids>314,777,781,1412,27905,27906,45555,45556</link.rule.ids></links><search><creatorcontrib>La Chance, Edmond</creatorcontrib><creatorcontrib>Hallé, Sylvain</creatorcontrib><title>An investigation of distributed computing for combinatorial testing</title><title>Software testing, verification & reliability</title><description>Summary
Combinatorial test generation, also called
t‐way testing, is the process of generating sets of input parameters for a system under test, by considering interactions between values of multiple parameters. In order to decrease total testing time, there is an interest in techniques that generate smaller test suites. In our previous work, we used graph techniques to produce high‐quality test suites. However, these techniques require a lot of computing power and memory, which is why this paper investigates distributed computing for
t‐way testing. We first introduce our distributed graph colouring method, with new algorithms for building the graph and for colouring it. Second, we present our distributed hypergraph vertex covering method and a new heuristic. Third, we show how to build a distributed IPOG algorithm by leveraging either graph colouring or hypergraph vertex covering as vertical growth algorithms. Finally, we test these new methods on a computer cluster and compare them to existing
t‐way testing tools.
Combinatorial test generation is the process of generating sets of input parameters for a system under test, by considering interactions between t values of multiple parameters; the paper investigates the use of distributed algorithms to generate such test suites. It proposes reductions of the
t‐way test suite generation to two problems on graphs and provides distributed algorithms to solve them; these algorithms are then used as vertical growth algorithms to build a distributed version of IPOG. Finally, we test these new methods on a computer cluster and compare them to existing
t‐way testing tools.</description><subject>Algorithms</subject><subject>Alliances</subject><subject>Combinatorial analysis</subject><subject>combinatorial testing</subject><subject>Computer networks</subject><subject>distributed computing</subject><subject>Distributed processing</subject><subject>Graph coloring</subject><subject>Graph theory</subject><subject>Parameters</subject><subject>phi‐way testing</subject><subject>test case generation</subject><subject>Testing time</subject><issn>0960-0833</issn><issn>1099-1689</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>24P</sourceid><sourceid>WIN</sourceid><recordid>eNp1kE1LAzEQhoMoWKsH_8GCJw_bTpJtNjmW4hcUBK1eQ3aTlJQ2qUm20n_vrvXqZYaB550XHoRuMUwwAJmmfIgTzCtyhkYYhCgx4-IcjUAwKIFTeomuUtoAABNMjNBi7gvnDyZlt1bZBV8EW2iXcnRNl40u2rDbd9n5dWFDHK7GeZVDdGpb5CHm19fowqptMjd_e4w-Hh9Wi-dy-fr0spgvy5YIQkrVWK1UBcaYClqmjcC6FqzSVNTUUiwaAjPKGcd1PdOGWy40Mc2MtMRiUnM6Rnenv_sYvrq-W25CF31fKQnHtKYg-jFG9yeqjSGlaKzcR7dT8SgxyMGRHBzJwVHPTk_st9ua4_-gfF99vv0mfgCLVGnJ</recordid><startdate>202306</startdate><enddate>202306</enddate><creator>La Chance, Edmond</creator><creator>Hallé, Sylvain</creator><general>Wiley Subscription Services, Inc</general><scope>24P</scope><scope>WIN</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>8FD</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><orcidid>https://orcid.org/0000-0002-4406-6154</orcidid></search><sort><creationdate>202306</creationdate><title>An investigation of distributed computing for combinatorial testing</title><author>La Chance, Edmond ; Hallé, Sylvain</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c2922-abfdaa40eee40c6de91d7964d3973f319b20538681775de8f89d2eb52c2f12783</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Algorithms</topic><topic>Alliances</topic><topic>Combinatorial analysis</topic><topic>combinatorial testing</topic><topic>Computer networks</topic><topic>distributed computing</topic><topic>Distributed processing</topic><topic>Graph coloring</topic><topic>Graph theory</topic><topic>Parameters</topic><topic>phi‐way testing</topic><topic>test case generation</topic><topic>Testing time</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>La Chance, Edmond</creatorcontrib><creatorcontrib>Hallé, Sylvain</creatorcontrib><collection>Wiley Online Library Open Access</collection><collection>Wiley Free Content</collection><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Technology Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><jtitle>Software testing, verification & reliability</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>La Chance, Edmond</au><au>Hallé, Sylvain</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>An investigation of distributed computing for combinatorial testing</atitle><jtitle>Software testing, verification & reliability</jtitle><date>2023-06</date><risdate>2023</risdate><volume>33</volume><issue>4</issue><epage>n/a</epage><issn>0960-0833</issn><eissn>1099-1689</eissn><abstract>Summary
Combinatorial test generation, also called
t‐way testing, is the process of generating sets of input parameters for a system under test, by considering interactions between values of multiple parameters. In order to decrease total testing time, there is an interest in techniques that generate smaller test suites. In our previous work, we used graph techniques to produce high‐quality test suites. However, these techniques require a lot of computing power and memory, which is why this paper investigates distributed computing for
t‐way testing. We first introduce our distributed graph colouring method, with new algorithms for building the graph and for colouring it. Second, we present our distributed hypergraph vertex covering method and a new heuristic. Third, we show how to build a distributed IPOG algorithm by leveraging either graph colouring or hypergraph vertex covering as vertical growth algorithms. Finally, we test these new methods on a computer cluster and compare them to existing
t‐way testing tools.
Combinatorial test generation is the process of generating sets of input parameters for a system under test, by considering interactions between t values of multiple parameters; the paper investigates the use of distributed algorithms to generate such test suites. It proposes reductions of the
t‐way test suite generation to two problems on graphs and provides distributed algorithms to solve them; these algorithms are then used as vertical growth algorithms to build a distributed version of IPOG. Finally, we test these new methods on a computer cluster and compare them to existing
t‐way testing tools.</abstract><cop>Chichester</cop><pub>Wiley Subscription Services, Inc</pub><doi>10.1002/stvr.1842</doi><tpages>26</tpages><orcidid>https://orcid.org/0000-0002-4406-6154</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Algorithms Alliances Combinatorial analysis combinatorial testing Computer networks distributed computing Distributed processing Graph coloring Graph theory Parameters phi‐way testing test case generation Testing time |
title | An investigation of distributed computing for combinatorial testing |
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