Advanced discovery mechanisms in model repositories
Summary As model‐driven engineering gains traction and poses as the new paradigm for software engineering, it raises a need for efficient approaches and tools to manage, discover, and retrieve relevant modeling artifacts. Hence, industry and academia are conceiving effective ways to store, search, a...
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Veröffentlicht in: | Software, practice & experience practice & experience, 2024-11, Vol.54 (11), p.2214-2248 |
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creator | Indamutsa, Arsene Di Rocco, Juri Almonte, Lissette Di Ruscio, Davide Pierantonio, Alfonso |
description | Summary
As model‐driven engineering gains traction and poses as the new paradigm for software engineering, it raises a need for efficient approaches and tools to manage, discover, and retrieve relevant modeling artifacts. Hence, industry and academia are conceiving effective ways to store, search, and retrieve heterogeneous model artifacts that employ advanced discovery mechanisms. This paper presents MDEForge‐Search, a novel approach to discovering heterogeneous model artifacts over MDEForge, a distributed cloud‐based model repository. We designed advanced discovery mechanisms that retrieve heterogeneous artifacts within their context (megamodel) and reuse them across model management services. In addition, a domain‐specific approach has been proposed to formulate queries in terms of keywords, search tags, conditional operators, quality model assessment services and a transformation chain discoverer. Finally, the applicability of our approach was assessed in a recommender system modeling framework, which, thanks to the operated integration, can rely on the availability of more than 5000 model artifacts currently persisted in our cloud‐based model repository. |
doi_str_mv | 10.1002/spe.3332 |
format | Article |
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As model‐driven engineering gains traction and poses as the new paradigm for software engineering, it raises a need for efficient approaches and tools to manage, discover, and retrieve relevant modeling artifacts. Hence, industry and academia are conceiving effective ways to store, search, and retrieve heterogeneous model artifacts that employ advanced discovery mechanisms. This paper presents MDEForge‐Search, a novel approach to discovering heterogeneous model artifacts over MDEForge, a distributed cloud‐based model repository. We designed advanced discovery mechanisms that retrieve heterogeneous artifacts within their context (megamodel) and reuse them across model management services. In addition, a domain‐specific approach has been proposed to formulate queries in terms of keywords, search tags, conditional operators, quality model assessment services and a transformation chain discoverer. Finally, the applicability of our approach was assessed in a recommender system modeling framework, which, thanks to the operated integration, can rely on the availability of more than 5000 model artifacts currently persisted in our cloud‐based model repository.</description><identifier>ISSN: 0038-0644</identifier><identifier>EISSN: 1097-024X</identifier><identifier>DOI: 10.1002/spe.3332</identifier><language>eng</language><publisher>Bognor Regis: Wiley Subscription Services, Inc</publisher><subject>advanced discovery mechanisms ; cloud‐based model repository ; Management services ; Modelling ; model‐driven engineering ; Quality assessment ; Recommender systems ; Repositories ; search engine ; Searching ; Software engineering</subject><ispartof>Software, practice & experience, 2024-11, Vol.54 (11), p.2214-2248</ispartof><rights>2024 John Wiley & Sons Ltd.</rights><rights>2024 John Wiley & Sons, Ltd.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c2542-b50e3fe4018be833205d0ff436c4052cf6e12c87a0225ae4405a2354f3a2b50c3</cites><orcidid>0000-0001-7416-1809</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%2Fspe.3332$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1002%2Fspe.3332$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>314,780,784,1416,27923,27924,45573,45574</link.rule.ids></links><search><creatorcontrib>Indamutsa, Arsene</creatorcontrib><creatorcontrib>Di Rocco, Juri</creatorcontrib><creatorcontrib>Almonte, Lissette</creatorcontrib><creatorcontrib>Di Ruscio, Davide</creatorcontrib><creatorcontrib>Pierantonio, Alfonso</creatorcontrib><title>Advanced discovery mechanisms in model repositories</title><title>Software, practice & experience</title><description>Summary
As model‐driven engineering gains traction and poses as the new paradigm for software engineering, it raises a need for efficient approaches and tools to manage, discover, and retrieve relevant modeling artifacts. Hence, industry and academia are conceiving effective ways to store, search, and retrieve heterogeneous model artifacts that employ advanced discovery mechanisms. This paper presents MDEForge‐Search, a novel approach to discovering heterogeneous model artifacts over MDEForge, a distributed cloud‐based model repository. We designed advanced discovery mechanisms that retrieve heterogeneous artifacts within their context (megamodel) and reuse them across model management services. In addition, a domain‐specific approach has been proposed to formulate queries in terms of keywords, search tags, conditional operators, quality model assessment services and a transformation chain discoverer. Finally, the applicability of our approach was assessed in a recommender system modeling framework, which, thanks to the operated integration, can rely on the availability of more than 5000 model artifacts currently persisted in our cloud‐based model repository.</description><subject>advanced discovery mechanisms</subject><subject>cloud‐based model repository</subject><subject>Management services</subject><subject>Modelling</subject><subject>model‐driven engineering</subject><subject>Quality assessment</subject><subject>Recommender systems</subject><subject>Repositories</subject><subject>search engine</subject><subject>Searching</subject><subject>Software engineering</subject><issn>0038-0644</issn><issn>1097-024X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><recordid>eNp1kE1LAzEQhoMoWKvgT1jw4mXr5LPrsZRahYKCCt5Cmp1gyu5mTdrK_ntT69XTwPC87wwPIdcUJhSA3aUeJ5xzdkJGFO6nJTDxcUpGALwqQQlxTi5S2gBQKpkaET6r96azWBe1TzbsMQ5Fi_bTdD61qfBd0YYamyJiH5LfhugxXZIzZ5qEV39zTN4fFm_zx3L1vHyaz1alZVKwci0BuUMBtFpjlV8CWYNzgisrQDLrFFJmq6kBxqRBkZeGcSkcNyxnLR-Tm2NvH8PXDtNWb8Iudvmk5pQypXKlytTtkbIxpBTR6T761sRBU9AHJTor0QclGS2P6LdvcPiX068vi1_-BxbNYLQ</recordid><startdate>202411</startdate><enddate>202411</enddate><creator>Indamutsa, Arsene</creator><creator>Di Rocco, Juri</creator><creator>Almonte, Lissette</creator><creator>Di Ruscio, Davide</creator><creator>Pierantonio, Alfonso</creator><general>Wiley Subscription Services, Inc</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>8FD</scope><scope>F28</scope><scope>FR3</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><orcidid>https://orcid.org/0000-0001-7416-1809</orcidid></search><sort><creationdate>202411</creationdate><title>Advanced discovery mechanisms in model repositories</title><author>Indamutsa, Arsene ; Di Rocco, Juri ; Almonte, Lissette ; Di Ruscio, Davide ; Pierantonio, Alfonso</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c2542-b50e3fe4018be833205d0ff436c4052cf6e12c87a0225ae4405a2354f3a2b50c3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>advanced discovery mechanisms</topic><topic>cloud‐based model repository</topic><topic>Management services</topic><topic>Modelling</topic><topic>model‐driven engineering</topic><topic>Quality assessment</topic><topic>Recommender systems</topic><topic>Repositories</topic><topic>search engine</topic><topic>Searching</topic><topic>Software engineering</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Indamutsa, Arsene</creatorcontrib><creatorcontrib>Di Rocco, Juri</creatorcontrib><creatorcontrib>Almonte, Lissette</creatorcontrib><creatorcontrib>Di Ruscio, Davide</creatorcontrib><creatorcontrib>Pierantonio, Alfonso</creatorcontrib><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Technology Research Database</collection><collection>ANTE: Abstracts in New Technology & Engineering</collection><collection>Engineering 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, practice & experience</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Indamutsa, Arsene</au><au>Di Rocco, Juri</au><au>Almonte, Lissette</au><au>Di Ruscio, Davide</au><au>Pierantonio, Alfonso</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Advanced discovery mechanisms in model repositories</atitle><jtitle>Software, practice & experience</jtitle><date>2024-11</date><risdate>2024</risdate><volume>54</volume><issue>11</issue><spage>2214</spage><epage>2248</epage><pages>2214-2248</pages><issn>0038-0644</issn><eissn>1097-024X</eissn><abstract>Summary
As model‐driven engineering gains traction and poses as the new paradigm for software engineering, it raises a need for efficient approaches and tools to manage, discover, and retrieve relevant modeling artifacts. Hence, industry and academia are conceiving effective ways to store, search, and retrieve heterogeneous model artifacts that employ advanced discovery mechanisms. This paper presents MDEForge‐Search, a novel approach to discovering heterogeneous model artifacts over MDEForge, a distributed cloud‐based model repository. We designed advanced discovery mechanisms that retrieve heterogeneous artifacts within their context (megamodel) and reuse them across model management services. In addition, a domain‐specific approach has been proposed to formulate queries in terms of keywords, search tags, conditional operators, quality model assessment services and a transformation chain discoverer. Finally, the applicability of our approach was assessed in a recommender system modeling framework, which, thanks to the operated integration, can rely on the availability of more than 5000 model artifacts currently persisted in our cloud‐based model repository.</abstract><cop>Bognor Regis</cop><pub>Wiley Subscription Services, Inc</pub><doi>10.1002/spe.3332</doi><tpages>35</tpages><orcidid>https://orcid.org/0000-0001-7416-1809</orcidid></addata></record> |
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subjects | advanced discovery mechanisms cloud‐based model repository Management services Modelling model‐driven engineering Quality assessment Recommender systems Repositories search engine Searching Software engineering |
title | Advanced discovery mechanisms in model repositories |
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