Menzies Releases Book on Data Science in Software Engineering
Congratulations to Dr. Tim Menzies, professor of computer science at NC State, for publishing a book entitled “Sharing Data and Models in Software Engineering.” Co-authors of the book include Ekrem Kocaguneli, Leandro Minku, Fayola Peters, and Burak Turhan.
Data science is about conversations, not just conclusions. The most useful results are those that are shared, discussed, debated, and used to guide further analysis. If results are not shared, they can be quickly forgotten. This book is about sharing ideas and how data mining can help that sharing. The book focuses on software engineering, but the methods it discusses apply to many domains.
Although sharing can provide increased insight, sharing ideas is not a simple matter. The bad news is that, usually, ideas are shared very badly. The good news is that recent research allows us to offer guidance on how to use data miners to better share lessons from data.
Book description: 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.
For more information on Dr. Menzies’ book, click here.
For more information on Dr. Menzies, click here.
Return To News Homepage