Software Metrics

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A01=James Bieman
A01=Norman Fenton
Admissible Transformations
Age Group_Uncategorized
Age Group_Uncategorized
agile development processes
agile methodology evaluation
Author_James Bieman
Author_Norman Fenton
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BN
BN Model
Branch Coverage
Case Study
Category1=Non-Fiction
Category=UMZ
causal inference models
causal models and Bayesian networks
COCOMO Ii
COP=United States
Cyclomatic Number
Decomposition Tree
Delivery_Delivery within 10-20 working days
development
empirical
Empirical Relation System
empirical software analysis
engineering
engineers
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eq_computing
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Function Point
FUNCTIONAL SIZE MEASURES
IFPUG
Language_English
measurement theory
Measuring Software Development Products
object-oriented design
object-oriented metrics
PA=Available
PHP Programmer
point
Prediction System
Price_€50 to €100
products
PS=Active
quality
quantitative and empirical methods in software engineering
quantitative software quality methods
relation
Scatter Plot
softlaunch
software engineering
software metrics
software process assessment
soware
Soware Development
Soware Engineering
Soware Engineers
Soware Fault
Soware Measurement
Soware Products
Soware Project
Soware Quality
Technical Complexity Factor
XP Method

Product details

  • ISBN 9781439838228
  • Weight: 1012g
  • Dimensions: 156 x 234mm
  • Publication Date: 01 Oct 2014
  • Publisher: Taylor & Francis Inc
  • Publication City/Country: US
  • Product Form: Hardback
  • Language: English
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A Framework for Managing, Measuring, and Predicting Attributes of Software Development Products and ProcessesReflecting the immense progress in the development and use of software metrics in the past decades, Software Metrics: A Rigorous and Practical Approach, Third Edition provides an up-to-date, accessible, and comprehensive introduction to software metrics. Like its popular predecessors, this third edition discusses important issues, explains essential concepts, and offers new approaches for tackling long-standing problems.

New to the Third EditionThis edition contains new material relevant to object-oriented design, design patterns, model-driven development, and agile development processes. It includes a new chapter on causal models and Bayesian networks and their application to software engineering. This edition also incorporates recent references to the latest software metrics activities, including research results, industrial case studies, and standards.

Suitable for a Range of ReadersWith numerous examples and exercises, this book continues to serve a wide audience. It can be used as a textbook for a software metrics and quality assurance course or as a useful supplement in any software engineering course. Practitioners will appreciate the important results that have previously only appeared in research-oriented publications. Researchers will welcome the material on new results as well as the extensive bibliography of measurement-related information. The book also gives software managers and developers practical guidelines for selecting metrics and planning their use in a measurement program.

Norman Fenton, PhD, is a professor of risk information management at Queen Mary London University and the chief executive officer of Agena, a company that specializes in risk management for critical systems. He is renowned for his work in software engineering and software metrics. His current projects focus on using Bayesian methods of analysis to risk assessment. He has published 6 books and more than 140 refereed articles and has provided consulting to many major companies worldwide.

James M. Bieman, PhD, is a professor of computer science at Colorado State University, where he was the founding director of the Software Assurance Laboratory. His research focuses on the evaluation of software designs and processes, including ways to test nontestable software, techniques that support automated software repair, and the relationships between internal design attributes and external quality attributes. He serves on the editorial boards of the Software Quality Journal and the Journal of Software and Systems Modeling.

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