Sharing Data and Models in Software Engineering Paperback / softback
by Tim (Professor, Computer Science, North Carolina State University, Raleigh, NC, USA) Menzies, Ekrem (Software Development Engineer at Microsoft) Kocaguneli, Burak (Burak Turhan, Professor of Software Engineering, University of Oulu, Finland) Turhan, Leandro (Research Fellow II, Centre of Excellence for Research in Computational Intelligence Minku, Fayola (PostDoctoral Researcher at LERO, the Irish Software Engineering Research Center, Uni Peters
Data Science for Software Engineering: Sharing Data and Models presents guidance and procedures for reusing data and models between projects to produce results that are useful and relevant.
Starting with a background section of practical lessons and warnings for beginner data scientists for software engineering, this edited volume proceeds to identify critical questions of contemporary software engineering related to data and models.
Learn how to adapt data from other organizations to local problems, mine privatized data, prune spurious information, simplify complex results, how to update models for new platforms, and more.
Chapters share largely applicable experimental results discussed with the blend of practitioner focused domain expertise, with commentary that highlights the methods that are most useful, and applicable to the widest range of projects.
Each chapter is written by a prominent expert and offers a state-of-the-art solution to an identified problem facing data scientists in software engineering.
Throughout, the editors share best practices collected from their experience training software engineering students and practitioners to master data science, and highlight the methods that are most useful, and applicable to the widest range of projects.
- Format: Paperback / softback
- Pages: 406 pages
- Publisher: Elsevier Science & Technology
- Publication Date: 01/12/2014
- Category: Software Engineering
- ISBN: 9780124172951