Making Software: What Really Works, and Why We Believe It

Making Software: What Really Works, and Why We Believe It

Making Software: What Really Works, and Why We Believe It

Making Software: What Really Works, and Why We Believe It

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Overview

Many claims are made about how certain tools, technologies, and practices improve software development. But which claims are verifiable, and which are merely wishful thinking? In this book, leading thinkers such as Steve McConnell, Barry Boehm, and Barbara Kitchenham offer essays that uncover the truth and unmask myths commonly held among the software development community. Their insights may surprise you.
  • Are some programmers really ten times more productive than others?
  • Does writing tests first help you develop better code faster?
  • Can code metrics predict the number of bugs in a piece of software?
  • Do design patterns actually make better software?
  • What effect does personality have on pair programming?
  • What matters more: how far apart people are geographically, or how far apart they are in the org chart?

Contributors include:

Jorge Aranda

Tom Ball

Victor R. Basili

Andrew Begel

Christian Bird

Barry Boehm

Marcelo Cataldo

Steven Clarke

Jason Cohen

Robert DeLine

Madeline Diep

Hakan Erdogmus

Michael Godfrey

Mark Guzdial

Jo E. Hannay

Ahmed E. Hassan

Israel Herraiz

Kim Sebastian Herzig

Cory Kapser

Barbara Kitchenham

Andrew Ko

Lucas Layman

Steve McConnell

Tim Menzies

Gail Murphy

Nachi Nagappan

Thomas J. Ostrand

Dewayne Perry

Marian Petre

Lutz Prechelt

Rahul Premraj

Forrest Shull

Beth Simon

Diomidis Spinellis

Neil Thomas

Walter Tichy

Burak Turhan

Elaine J. Weyuker

Michele A. Whitecraft

Laurie Williams

Wendy M. Williams

Andreas Zeller

Thomas Zimmermann


Product Details

ISBN-13: 9780596808327
Publisher: O'Reilly Media, Incorporated
Publication date: 10/27/2010
Pages: 602
Product dimensions: 7.10(w) x 9.10(h) x 1.40(d)

About the Author

Andy Oram is an editor at O'Reilly Media, a highly respected book publisher and technology information provider. An employee of the company since 1992, Andy currently specializes in free software and open source technologies. His work for O'Reilly includes the first books ever published commercially in the United States on Linux, and the 2001 title Peer-to-Peer. His modest programming and system administration skills are mostly self-taught.

Greg Wilson has worked on high-performance scientific computing, data visualization, and computer security, and is currently project lead at Software Carpentry (http://software-carpentry.org). Greg has a Ph.D. in Computer Science from the Universityof Edinburgh, and has written and edited several technical and children's books, including "Beautiful Code" (O'Reilly, 2007).

Table of Contents

  • Preface
  • General Principles of Searching For and Using Evidence
    • Chapter 1: The Quest for Convincing Evidence
    • Chapter 2: Credibility, or Why Should I Insist on Being Convinced?
    • Chapter 3: What We Can Learn from Systematic Reviews
    • Chapter 4: Understanding Software Engineering Through Qualitative Methods
    • Chapter 5: Learning Through Application: The Maturing of the QIP in the SEL
    • Chapter 6: Personality, Intelligence, and Expertise: Impacts on Software Development
    • Chapter 7: Why Is It So Hard to Learn to Program?
    • Chapter 8: Beyond Lines of Code: Do We Need More Complexity Metrics?
  • Specific Topics in Software Engineering
    • Chapter 9: An Automated Fault Prediction System
    • Chapter 10: Architecting: How Much and When?
    • Chapter 11: Conway’s Corollary
    • Chapter 12: How Effective Is Test-Driven Development?
    • Chapter 13: Why Aren’t More Women in Computer Science?
    • Chapter 14: Two Comparisons of Programming Languages
    • Chapter 15: Quality Wars: Open Source Versus Proprietary Software
    • Chapter 16: Code Talkers
    • Chapter 17: Pair Programming
    • Chapter 18: Modern Code Review
    • Chapter 19: A Communal Workshop or Doors That Close?
    • Chapter 20: Identifying and Managing Dependencies in Global Software Development
    • Chapter 21: How Effective Is Modularization?
    • Chapter 22: The Evidence for Design Patterns
    • Chapter 23: Evidence-Based Failure Prediction
    • Chapter 24: The Art of Collecting Bug Reports
    • Chapter 25: Where Do Most Software Flaws Come From?
    • Chapter 26: Novice Professionals: Recent Graduates in a First Software Engineering Job
    • Chapter 27: Mining Your Own Evidence
    • Chapter 28: Copy-Paste as a Principled Engineering Tool
    • Chapter 29: How Usable Are Your APIs?
    • Chapter 30: What Does 10x Mean? Measuring Variations in Programmer Productivity
  • Contributors
  • Colophon
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