LEADER 05592nam 22007095 450 001 9910299056203321 005 20200703025547.0 010 $a3-642-45135-7 024 7 $a10.1007/978-3-642-45135-5 035 $a(CKB)3710000000106773 035 $a(EBL)1731222 035 $a(OCoLC)883570999 035 $a(SSID)ssj0001199755 035 $a(PQKBManifestationID)11641201 035 $a(PQKBTitleCode)TC0001199755 035 $a(PQKBWorkID)11205288 035 $a(PQKB)10118066 035 $a(MiAaPQ)EBC1731222 035 $a(DE-He213)978-3-642-45135-5 035 $a(PPN)178316660 035 $a(EXLCZ)993710000000106773 100 $a20140430d2014 u| 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aRecommendation Systems in Software Engineering /$fedited by Martin P. Robillard, Walid Maalej, Robert J. Walker, Thomas Zimmermann 205 $a1st ed. 2014. 210 1$aBerlin, Heidelberg :$cSpringer Berlin Heidelberg :$cImprint: Springer,$d2014. 215 $a1 online resource (560 p.) 300 $aDescription based upon print version of record. 311 $a3-642-45134-9 320 $aIncludes bibliographical references and index. 327 $a1 An Introduction to Recommendation Systems in Software Engineering -- Part I Techniques -- 2 Basic Approaches in Recommendation Systems -- 3 Data Mining -- 4 Recommendation Systems in-the-Small -- 5 Source Code Based Recommendation Systems -- 6 Mining Bug Data -- 7 Collecting and Processing Interaction Data for Recommendation Systems -- 8 Developer Profiles for Recommendation Systems -- 9 Recommendation Delivery -- Part II Evaluation -- 10 Dimensions and Metrics for Evaluating Recommendation Systems -- 11 Benchmarking -- 12 Simulation -- 13 Field Studies -- Part III Applications -- 14 Reuse-Oriented Code Recommendation Systems -- 15 Recommending Refactoring Operations in Large Software Systems -- 16 Recommending Program Transformations -- 17 Recommendation Systems in Requirements Discovery -- 18 Changes, Evolution and Bugs -- 19 Recommendation Heuristics for Improving Product Line Configuration Processes. 330 $aWith the growth of public and private data stores and the emergence of off-the-shelf data-mining technology, recommendation systems have emerged that specifically address the unique challenges of navigating and interpreting software engineering data. This book collects, structures, and formalizes knowledge on recommendation systems in software engineering. It adopts a pragmatic approach with an explicit focus on system design, implementation, and evaluation. The book is divided into three parts: ?Part I ? Techniques? introduces basics for building recommenders in software engineering, including techniques for collecting and processing software engineering data, but also for presenting recommendations to users as part of their workflow. ?Part II ? Evaluation? summarizes methods and experimental designs for evaluating recommendations in software engineering. ?Part III ? Applications? describes needs, issues, and solution concepts involved in entire recommendation systems for specific software engineering tasks, focusing on the engineering insights required to make effective recommendations. The book is complemented by the webpage rsse.org/book, which includes free supplemental materials for readers of this book and anyone interested in recommendation systems in software engineering, including lecture slides, data sets, source code, and an overview of people, groups, papers, and tools with regard to recommendation systems in software engineering. The book is particularly well-suited for graduate students and researchers building new recommendation systems for software engineering applications or in other high-tech fields. It may also serve as the basis for graduate courses on recommendation systems, applied data mining, or software engineering. Software engineering practitioners developing recommendation systems or similar applications with predictive functionality will also benefit from the broad spectrum of topics covered. 606 $aSoftware engineering 606 $aManagement information systems 606 $aComputer science 606 $aInformation storage and retrieval 606 $aSoftware Engineering$3https://scigraph.springernature.com/ontologies/product-market-codes/I14029 606 $aManagement of Computing and Information Systems$3https://scigraph.springernature.com/ontologies/product-market-codes/I24067 606 $aInformation Storage and Retrieval$3https://scigraph.springernature.com/ontologies/product-market-codes/I18032 615 0$aSoftware engineering. 615 0$aManagement information systems. 615 0$aComputer science. 615 0$aInformation storage and retrieval. 615 14$aSoftware Engineering. 615 24$aManagement of Computing and Information Systems. 615 24$aInformation Storage and Retrieval. 676 $a004 676 $a005.1 676 $a005.74 676 $a025.04 702 $aRobillard$b Martin P$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aMaalej$b Walid$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aWalker$b Robert J$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aZimmermann$b Thomas$4edt$4http://id.loc.gov/vocabulary/relators/edt 906 $aBOOK 912 $a9910299056203321 996 $aRecommendation Systems in Software Engineering$92232985 997 $aUNINA