Mutation Analysis for SQL Database Applications
Testing database applications is crucial for ensuring good quality software as undetected faults can result in unrecoverable data corruption. SQL is the most widely used interface language for relational database systems. Our approach aims to achieve better testing by selecting fault revealing datab...
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creator | Cabeca, A.G. Jino, M. Leitao-Junior, P.S. |
description | Testing database applications is crucial for ensuring good quality software as undetected faults can result in unrecoverable data corruption. SQL is the most widely used interface language for relational database systems. Our approach aims to achieve better testing by selecting fault revealing databases. We propose the use of mutation analysis on SQL statements and discuss two scenarios for applying strong and weak mutation techniques. Experiments using real applications, real faults and real data were performed to: (i) evaluate the applicability of the approach, and (ii) compare fault-revealing abilities of input databases. |
doi_str_mv | 10.1109/ICSEA.2009.30 |
format | Conference Proceeding |
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Experiments using real applications, real faults and real data were performed to: (i) evaluate the applicability of the approach, and (ii) compare fault-revealing abilities of input databases.</description><identifier>ISBN: 1424447798</identifier><identifier>ISBN: 9781424447794</identifier><identifier>EISBN: 0769537774</identifier><identifier>EISBN: 9780769537771</identifier><identifier>DOI: 10.1109/ICSEA.2009.30</identifier><language>eng</language><publisher>IEEE</publisher><subject>Collaborative software ; Costs ; Data analysis ; database testing ; Genetic mutations ; mutation testing ; Programming ; quality assurance ; Scheduling ; software testing ; Sorting ; SQL ; Taxonomy ; Uncertainty</subject><ispartof>2009 Fourth International Conference on Software Engineering Advances, 2009, p.146-151</ispartof><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/5298467$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,777,781,786,787,2052,27906,54901</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/5298467$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Cabeca, A.G.</creatorcontrib><creatorcontrib>Jino, M.</creatorcontrib><creatorcontrib>Leitao-Junior, P.S.</creatorcontrib><title>Mutation Analysis for SQL Database Applications</title><title>2009 Fourth International Conference on Software Engineering Advances</title><addtitle>ICSEA</addtitle><description>Testing database applications is crucial for ensuring good quality software as undetected faults can result in unrecoverable data corruption. SQL is the most widely used interface language for relational database systems. Our approach aims to achieve better testing by selecting fault revealing databases. We propose the use of mutation analysis on SQL statements and discuss two scenarios for applying strong and weak mutation techniques. Experiments using real applications, real faults and real data were performed to: (i) evaluate the applicability of the approach, and (ii) compare fault-revealing abilities of input databases.</description><subject>Collaborative software</subject><subject>Costs</subject><subject>Data analysis</subject><subject>database testing</subject><subject>Genetic mutations</subject><subject>mutation testing</subject><subject>Programming</subject><subject>quality assurance</subject><subject>Scheduling</subject><subject>software testing</subject><subject>Sorting</subject><subject>SQL</subject><subject>Taxonomy</subject><subject>Uncertainty</subject><isbn>1424447798</isbn><isbn>9781424447794</isbn><isbn>0769537774</isbn><isbn>9780769537771</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2009</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNotjE1Lw0AUAFdE0NYePXnJH0j6Xvbj7R5DrFqIlFI9l5dkFxZiG7Lx0H-vqKc5zDBCPCAUiODW2_qwqYoSwBUSrsQCyDgtiUhdiwWqUilF5OytWKUUWygNGasU3on129fMczyfsurEwyXFlIXzlB32TfbEM7ecfFaN4xC73yrdi5vAQ_Krfy7Fx_PmvX7Nm93Ltq6aPCLpOUettQUb0LHvuCXFJpQE6KG1HAKi-7G2J-qsNtz2zF1PyFIiBwee5VI8_n2j9_44TvGTp8tRl84qQ_IbwDNDCw</recordid><startdate>200909</startdate><enddate>200909</enddate><creator>Cabeca, A.G.</creator><creator>Jino, M.</creator><creator>Leitao-Junior, P.S.</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>200909</creationdate><title>Mutation Analysis for SQL Database Applications</title><author>Cabeca, A.G. ; Jino, M. ; Leitao-Junior, P.S.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i175t-1555808f19aecab74a6f2701e0b8aff1198088d77c856abdaacd71a331af90ea3</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2009</creationdate><topic>Collaborative software</topic><topic>Costs</topic><topic>Data analysis</topic><topic>database testing</topic><topic>Genetic mutations</topic><topic>mutation testing</topic><topic>Programming</topic><topic>quality assurance</topic><topic>Scheduling</topic><topic>software testing</topic><topic>Sorting</topic><topic>SQL</topic><topic>Taxonomy</topic><topic>Uncertainty</topic><toplevel>online_resources</toplevel><creatorcontrib>Cabeca, A.G.</creatorcontrib><creatorcontrib>Jino, M.</creatorcontrib><creatorcontrib>Leitao-Junior, P.S.</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Cabeca, A.G.</au><au>Jino, M.</au><au>Leitao-Junior, P.S.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Mutation Analysis for SQL Database Applications</atitle><btitle>2009 Fourth International Conference on Software Engineering Advances</btitle><stitle>ICSEA</stitle><date>2009-09</date><risdate>2009</risdate><spage>146</spage><epage>151</epage><pages>146-151</pages><isbn>1424447798</isbn><isbn>9781424447794</isbn><eisbn>0769537774</eisbn><eisbn>9780769537771</eisbn><abstract>Testing database applications is crucial for ensuring good quality software as undetected faults can result in unrecoverable data corruption. SQL is the most widely used interface language for relational database systems. Our approach aims to achieve better testing by selecting fault revealing databases. We propose the use of mutation analysis on SQL statements and discuss two scenarios for applying strong and weak mutation techniques. Experiments using real applications, real faults and real data were performed to: (i) evaluate the applicability of the approach, and (ii) compare fault-revealing abilities of input databases.</abstract><pub>IEEE</pub><doi>10.1109/ICSEA.2009.30</doi><tpages>6</tpages></addata></record> |
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source | IEEE Electronic Library (IEL) Conference Proceedings |
subjects | Collaborative software Costs Data analysis database testing Genetic mutations mutation testing Programming quality assurance Scheduling software testing Sorting SQL Taxonomy Uncertainty |
title | Mutation Analysis for SQL Database Applications |
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