Software Defect Prediction using Bayesian Networks and Kernel Methods - Ahmet Okutan
-30% ar kodu BOOKS
Piegāde 12-18 darba dienu laikā
30 dienu atgriešanas politika
There are lots of different software metrics discovered and used for defect prediction in the literature. Instead of dealing with so many metrics, it would be practical and easy if we could determine the set of metrics that are most important and focus on them more to predict defectiveness. In this book, we use Bayesian modeling to determine the influential relationships among software metrics and defect pr ... Pilns apraksts
Jums varētu patikt arī
TOP
If Anyone Builds It, Everyone Dies: Why Superhuman AI Would Kill Us All
Eliezer Yudkowsky, Nate Soares
-30% ar kodu BOOKS
Piegādātāja noliktavā
TOP
Gödel, Escher, Bach: An Eternal Golden Braid
-30% ar kodu BOOKS
Piegādātāja noliktavā
TOP
AI Engineering: Building Applications with Foundation Models
-30% ar kodu BOOKS
Piegādātāja noliktavā
TOP
The Rust Programming Language
Steve Klabnik, Carol Nichols, Chris Krycho
-30% ar kodu BOOKS
Piegādātāja noliktavā
TOP
The Art of Game Design: A Book of Lenses
-30% ar kodu BOOKS
Piegādātāja noliktavā
TOP
How To Think About AI: A Guide For The Perplexed
-30% ar kodu BOOKS
Piegādātāja noliktavā
TOP
Empire of AI: Dreams and Nightmares in Sam Altman's OpenAI
-30% ar kodu BOOKS
Piegādātāja noliktavā
TOP
The Pragmatic Programmer: journey to mastery, 20th Anniversary Edition, 2/e: your journey to mastery, 20th Anniversary Edition
-30% ar kodu BOOKS
Piegādātāja noliktavā
TOP
HBR Guide to Generative AI for Managers
-30% ar kodu BOOKS
Piegādātāja noliktavā
TOP
Hackers. 25th Anniversary Edition: Heroes of the Computer Revolution
-30% ar kodu BOOKS
Piegādātāja noliktavā
TOP
The Web Application Hacker's Handbook: Discovering and Exploiting Security Flaws
-30% ar kodu BOOKS
Piegādātāja noliktavā
TOP
How Linux Works: What Every Superuser Should Know
-30% ar kodu BOOKS
Piegādātāja noliktavā
TOP
Artificial Intelligence: A Modern Approach, Global Edition
-30% ar kodu BOOKS
Piegādātāja noliktavā
TOP
Python Crash Course: A Hands-On, Project-Based Introduction to Programming
-30% ar kodu BOOKS
Piegādātāja noliktavā
TOP
Fundamentals of Software Architecture: A Modern Engineering Approach
-30% ar kodu BOOKS
Piegādātāja noliktavā
TOP
Speak Data: Artists, Scientists, Thinkers, and Dreamers on How We Live Our Lives in Numbers
-30% ar kodu BOOKS
Piegādātāja noliktavā
TOP
Linux Basics for Hackers, 2nd Edition: Getting Started with Networking, Scripting, and Security in Kali
-30% ar kodu BOOKS
Piegādātāja noliktavā
TOP
C Programming Language
Brian W. Kernighan, Brian Kernighan, Dennis Ritchie
-30% ar kodu BOOKS
Piegādātāja noliktavā
TOP
Proofs from THE BOOK
Martin Aigner, Günter M. Ziegler
-30% ar kodu BOOKS
Piegādātāja noliktavā
Aprašymas
There are lots of different software metrics discovered and used for defect prediction in the literature. Instead of dealing with so many metrics, it would be practical and easy if we could determine the set of metrics that are most important and focus on them more to predict defectiveness. In this book, we use Bayesian modeling to determine the influential relationships among software metrics and defect proneness. Furthermore, we propose a novel technique for defect prediction that uses plagiarism detection tools. We use kernel programming to model the relationship between source code similarity and defectiveness and suggest that source code similarity is a good means of predicting both defectiveness and the number of defects in software systems.
Vairāk informācijas
| Autors | Ahmet Okutan |
|---|---|
| Izdevējs | SPS |
| Izlaides gads | 2015 |
| Vāka tips | Mīkstais vāks |
| EAN | 9783639703467 |