LEADER 04482nam 22006975 450 001 9910409677903321 005 20200706211322.0 010 $a3-030-30106-0 024 7 $a10.1007/978-3-030-30106-4 035 $a(CKB)4100000010770853 035 $a(DE-He213)978-3-030-30106-4 035 $a(MiAaPQ)EBC6151487 035 $a(PPN)243225865 035 $a(EXLCZ)994100000010770853 100 $a20200330d2020 u| 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aMining Software Engineering Data for Software Reuse /$fby Themistoklis Diamantopoulos, Andreas L. Symeonidis 205 $a1st ed. 2020. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2020. 215 $a1 online resource (XXI, 242 p. 174 illus., 103 illus. in color.) 225 1 $aAdvanced Information and Knowledge Processing,$x1610-3947 311 $a3-030-30105-2 327 $aPart 1: Introduction and Background -- Introduction -- Theoretical Background and State-of-the-art -- Part II: Requirements Mining -- Modelling Software Requirements -- Mining Software Requirements -- Part III: Source Code Mining -- Source Code Indexing for Component Reuse -- Mining Source Code for Component Reuse -- Mining Source Code for Snippet Reuse -- Mining Solutions for Extended Snippet Reuse -- Part IV: Quality Assessment -- Providing Reusability-aware Recommendations -- Assessing the Reusability of Source Code Components -- Part V: Conclusion and Future Work -- Conclusion -- Future Work -- Bibliography . 330 $aThis monograph discusses software reuse and how it can be applied at different stages of the software development process, on different types of data and at different levels of granularity. Several challenging hypotheses are analyzed and confronted using novel data-driven methodologies, in order to solve problems in requirements elicitation and specification extraction, software design and implementation, as well as software quality assurance. The book is accompanied by a number of tools, libraries and working prototypes in order to practically illustrate how the phases of the software engineering life cycle can benefit from unlocking the potential of data. Software engineering researchers, experts, and practitioners can benefit from the various methodologies presented and can better understand how knowledge extracted from software data residing in various repositories can be combined and used to enable effective decision making and save considerable time and effort through software reuse. Mining Software Engineering Data for Software Reuse can also prove handy for graduate-level students in software engineering. 410 0$aAdvanced Information and Knowledge Processing,$x1610-3947 606 $aSoftware engineering 606 $aEngineering?Data processing 606 $aData mining 606 $aOpen source software 606 $aComputer programming 606 $aManagement information systems 606 $aSoftware Engineering$3https://scigraph.springernature.com/ontologies/product-market-codes/I14029 606 $aData Engineering$3https://scigraph.springernature.com/ontologies/product-market-codes/T11040 606 $aData Mining and Knowledge Discovery$3https://scigraph.springernature.com/ontologies/product-market-codes/I18030 606 $aOpen Source$3https://scigraph.springernature.com/ontologies/product-market-codes/I29090 606 $aSoftware Management$3https://scigraph.springernature.com/ontologies/product-market-codes/522050 615 0$aSoftware engineering. 615 0$aEngineering?Data processing. 615 0$aData mining. 615 0$aOpen source software. 615 0$aComputer programming. 615 0$aManagement information systems. 615 14$aSoftware Engineering. 615 24$aData Engineering. 615 24$aData Mining and Knowledge Discovery. 615 24$aOpen Source. 615 24$aSoftware Management. 676 $a005.1 700 $aDiamantopoulos$b Themistoklis$4aut$4http://id.loc.gov/vocabulary/relators/aut$0908695 702 $aSymeonidis$b Andreas L$4aut$4http://id.loc.gov/vocabulary/relators/aut 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910409677903321 996 $aMining Software Engineering Data for Software Reuse$92032256 997 $aUNINA