Empirical Study of the Effects of Different Similarity Measures on Test Case Prioritization
Similarity-based test case prioritization algorithms have been applied to regression testing. The common characteristic of these algorithms is to reschedule the execution order of test cases according to the distances between pair-wise test cases. The distance information can be calculated by differ...
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| Veröffentlicht in: | Mathematical problems in engineering 2016-01, Vol.2016 (2016), p.1-19 |
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| creator | Zhang, Yanmei Chen, Deng Jiang, Shujuan Wang, Rongcun |
| description | Similarity-based test case prioritization algorithms have been applied to regression testing. The common characteristic of these algorithms is to reschedule the execution order of test cases according to the distances between pair-wise test cases. The distance information can be calculated by different similarity measures. Since the topologies vary with similarity measures, the distances between pair-wise test cases calculated by different similarity measures are different. Similarity measures could significantly influence the effectiveness of test case prioritization. Therefore, we empirically evaluate the effects of six similarity measures on two similarity-based test case prioritization algorithms. The obtained results are statistically analyzed to recommend the best combination of similarity-based prioritization algorithms and similarity measures. The experimental results, confirmed by a statistical analysis, indicate that Euclidean distance is more efficient in finding defects than other similarity measures. The combination of the global similarity-based prioritization algorithm and Euclidean distance could be a better choice. It generates not only higher fault detection effectiveness but also smaller standard deviation. The goal of this study is to provide practical guides for picking the appropriate combination of similarity-based test case prioritization techniques and similarity measures. |
| doi_str_mv | 10.1155/2016/8343910 |
| format | Article |
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The common characteristic of these algorithms is to reschedule the execution order of test cases according to the distances between pair-wise test cases. The distance information can be calculated by different similarity measures. Since the topologies vary with similarity measures, the distances between pair-wise test cases calculated by different similarity measures are different. Similarity measures could significantly influence the effectiveness of test case prioritization. Therefore, we empirically evaluate the effects of six similarity measures on two similarity-based test case prioritization algorithms. The obtained results are statistically analyzed to recommend the best combination of similarity-based prioritization algorithms and similarity measures. The experimental results, confirmed by a statistical analysis, indicate that Euclidean distance is more efficient in finding defects than other similarity measures. The combination of the global similarity-based prioritization algorithm and Euclidean distance could be a better choice. It generates not only higher fault detection effectiveness but also smaller standard deviation. The goal of this study is to provide practical guides for picking the appropriate combination of similarity-based test case prioritization techniques and similarity measures.</description><identifier>ISSN: 1024-123X</identifier><identifier>EISSN: 1563-5147</identifier><identifier>DOI: 10.1155/2016/8343910</identifier><language>eng</language><publisher>Cairo, Egypt: Hindawi Publishing Corporation</publisher><subject>Algorithms ; Effectiveness ; Empirical analysis ; Euclidean geometry ; Fault detection ; Mathematical analysis ; Mathematical problems ; Picking ; Regression ; Similarity ; Similarity measures ; Software ; Standard deviation ; Statistical analysis ; Topology</subject><ispartof>Mathematical problems in engineering, 2016-01, Vol.2016 (2016), p.1-19</ispartof><rights>Copyright © 2016 Rongcun Wang et al.</rights><rights>Copyright © 2016 Rongcun Wang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c393t-a17320c573cc187d5519c0e80342fe29be04fe1527de56489c47b9d0a6a3a1713</citedby><cites>FETCH-LOGICAL-c393t-a17320c573cc187d5519c0e80342fe29be04fe1527de56489c47b9d0a6a3a1713</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,776,780,27901,27902</link.rule.ids></links><search><contributor>Insfran, Emilio</contributor><creatorcontrib>Zhang, Yanmei</creatorcontrib><creatorcontrib>Chen, Deng</creatorcontrib><creatorcontrib>Jiang, Shujuan</creatorcontrib><creatorcontrib>Wang, Rongcun</creatorcontrib><title>Empirical Study of the Effects of Different Similarity Measures on Test Case Prioritization</title><title>Mathematical problems in engineering</title><description>Similarity-based test case prioritization algorithms have been applied to regression testing. The common characteristic of these algorithms is to reschedule the execution order of test cases according to the distances between pair-wise test cases. The distance information can be calculated by different similarity measures. Since the topologies vary with similarity measures, the distances between pair-wise test cases calculated by different similarity measures are different. Similarity measures could significantly influence the effectiveness of test case prioritization. Therefore, we empirically evaluate the effects of six similarity measures on two similarity-based test case prioritization algorithms. The obtained results are statistically analyzed to recommend the best combination of similarity-based prioritization algorithms and similarity measures. The experimental results, confirmed by a statistical analysis, indicate that Euclidean distance is more efficient in finding defects than other similarity measures. The combination of the global similarity-based prioritization algorithm and Euclidean distance could be a better choice. It generates not only higher fault detection effectiveness but also smaller standard deviation. The goal of this study is to provide practical guides for picking the appropriate combination of similarity-based test case prioritization techniques and similarity measures.</description><subject>Algorithms</subject><subject>Effectiveness</subject><subject>Empirical analysis</subject><subject>Euclidean geometry</subject><subject>Fault detection</subject><subject>Mathematical analysis</subject><subject>Mathematical problems</subject><subject>Picking</subject><subject>Regression</subject><subject>Similarity</subject><subject>Similarity measures</subject><subject>Software</subject><subject>Standard deviation</subject><subject>Statistical analysis</subject><subject>Topology</subject><issn>1024-123X</issn><issn>1563-5147</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2016</creationdate><recordtype>article</recordtype><sourceid>RHX</sourceid><sourceid>BENPR</sourceid><recordid>eNqF0E1LxDAQBuAiCq4fN88S8CJoNZM0TXKUdf0ARUEFwUPJplM2S7ddkxZZf71ZuiB48ZQJ88wwvElyBPQCQIhLRiG_VDzjGuhWMgKR81RAJrdjTVmWAuPvu8leCHNKGQhQo-Rjslg676ypyUvXlyvSVqSbIZlUFdourL_XLtYem468uIWrjXfdijyiCb3HCBryiqEjYxOQPHvXxrb7Np1rm4NkpzJ1wMPNu5-83Uxex3fpw9Pt_fjqIbVc8y41IDmjVkhuLShZCgHaUlSUZ6xCpqdIswpBMFmiyDOlbSanuqQmNzzOAt9PToe9S99-9vGYYuGCxbo2DbZ9KEBBTqWSWkV68ofO29438boCpFJaiVzxqM4HZX0bgseqWHq3MH5VAC3WSRfrpItN0pGfDXzmmtJ8uf_08aAxGqzMrwZgudL8B7vLhhg</recordid><startdate>20160101</startdate><enddate>20160101</enddate><creator>Zhang, Yanmei</creator><creator>Chen, Deng</creator><creator>Jiang, Shujuan</creator><creator>Wang, Rongcun</creator><general>Hindawi Publishing Corporation</general><general>Hindawi Limited</general><scope>ADJCN</scope><scope>AHFXO</scope><scope>RHU</scope><scope>RHW</scope><scope>RHX</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7TB</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>CWDGH</scope><scope>DWQXO</scope><scope>FR3</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>JQ2</scope><scope>K7-</scope><scope>KR7</scope><scope>L6V</scope><scope>M7S</scope><scope>P5Z</scope><scope>P62</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PTHSS</scope></search><sort><creationdate>20160101</creationdate><title>Empirical Study of the Effects of Different Similarity Measures on Test Case Prioritization</title><author>Zhang, Yanmei ; Chen, Deng ; Jiang, Shujuan ; Wang, Rongcun</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c393t-a17320c573cc187d5519c0e80342fe29be04fe1527de56489c47b9d0a6a3a1713</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2016</creationdate><topic>Algorithms</topic><topic>Effectiveness</topic><topic>Empirical analysis</topic><topic>Euclidean geometry</topic><topic>Fault detection</topic><topic>Mathematical analysis</topic><topic>Mathematical problems</topic><topic>Picking</topic><topic>Regression</topic><topic>Similarity</topic><topic>Similarity measures</topic><topic>Software</topic><topic>Standard deviation</topic><topic>Statistical analysis</topic><topic>Topology</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Zhang, Yanmei</creatorcontrib><creatorcontrib>Chen, Deng</creatorcontrib><creatorcontrib>Jiang, Shujuan</creatorcontrib><creatorcontrib>Wang, Rongcun</creatorcontrib><collection>الدوريات العلمية والإحصائية - e-Marefa Academic and Statistical Periodicals</collection><collection>معرفة - المحتوى العربي الأكاديمي المتكامل - e-Marefa Academic Complete</collection><collection>Hindawi Publishing Complete</collection><collection>Hindawi Publishing Subscription Journals</collection><collection>Hindawi Publishing Open Access</collection><collection>CrossRef</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>Materials Science & Engineering Collection</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest Central</collection><collection>Advanced Technologies & Aerospace Database (1962 - current)</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Middle East & Africa Database</collection><collection>ProQuest Central</collection><collection>Engineering Research Database</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Computer Science Collection</collection><collection>Computer Science Database</collection><collection>Civil Engineering Abstracts</collection><collection>ProQuest Engineering Collection</collection><collection>Engineering Database</collection><collection>ProQuest advanced technologies & aerospace journals</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>Engineering collection</collection><jtitle>Mathematical problems in engineering</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Zhang, Yanmei</au><au>Chen, Deng</au><au>Jiang, Shujuan</au><au>Wang, Rongcun</au><au>Insfran, Emilio</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Empirical Study of the Effects of Different Similarity Measures on Test Case Prioritization</atitle><jtitle>Mathematical problems in engineering</jtitle><date>2016-01-01</date><risdate>2016</risdate><volume>2016</volume><issue>2016</issue><spage>1</spage><epage>19</epage><pages>1-19</pages><issn>1024-123X</issn><eissn>1563-5147</eissn><abstract>Similarity-based test case prioritization algorithms have been applied to regression testing. The common characteristic of these algorithms is to reschedule the execution order of test cases according to the distances between pair-wise test cases. The distance information can be calculated by different similarity measures. Since the topologies vary with similarity measures, the distances between pair-wise test cases calculated by different similarity measures are different. Similarity measures could significantly influence the effectiveness of test case prioritization. Therefore, we empirically evaluate the effects of six similarity measures on two similarity-based test case prioritization algorithms. The obtained results are statistically analyzed to recommend the best combination of similarity-based prioritization algorithms and similarity measures. The experimental results, confirmed by a statistical analysis, indicate that Euclidean distance is more efficient in finding defects than other similarity measures. The combination of the global similarity-based prioritization algorithm and Euclidean distance could be a better choice. It generates not only higher fault detection effectiveness but also smaller standard deviation. The goal of this study is to provide practical guides for picking the appropriate combination of similarity-based test case prioritization techniques and similarity measures.</abstract><cop>Cairo, Egypt</cop><pub>Hindawi Publishing Corporation</pub><doi>10.1155/2016/8343910</doi><tpages>19</tpages><oa>free_for_read</oa></addata></record> |
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| source | Wiley-Blackwell Open Access Collection; Alma/SFX Local Collection; EZB Electronic Journals Library |
| subjects | Algorithms Effectiveness Empirical analysis Euclidean geometry Fault detection Mathematical analysis Mathematical problems Picking Regression Similarity Similarity measures Software Standard deviation Statistical analysis Topology |
| title | Empirical Study of the Effects of Different Similarity Measures on Test Case Prioritization |
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