Value-Based Software Engineering

  • Stefan Biffl
  • Aybüke Aurum
  • Barry Boehm
  • Hakan Erdogmus
  • Paul Grünbacher

Table of contents

  1. Front Matter
    Pages I-XXII
  2. Barry W. Boehm, Apurva Jain
    Pages 15-37
  3. Hakan Erdogmus, John Favaro, Michael Halling
    Pages 39-66
  4. Paul Grünbacher, Sabine Köszegi, Stefan Biffl
    Pages 133-154
  5. Michael Berry, Aybüke Aurum
    Pages 155-177
  6. Ann Fruhling, Gert-Jan de Vreede
    Pages 201-223
  7. Rudolf Ramler, Stefan Biffl, Paul Grünbacher
    Pages 225-244
  8. Sebastian Maurice, Günther Ruhe, Omolade Saliu, An Ngo-The
    Pages 247-261
  9. David L. Atkins, Audris Mockus, Harvey Siy
    Pages 327-344
  10. Donald J. Reifer
    Pages 345-366
  11. Back Matter
    Pages 367-388

About this book

Introduction

Ross Jeffery When, as a result of pressure from the CEO, the Chief Information Officer poses the question “Just what is this information system worth to the organization?” the IT staff members are typically at a loss. “That’s a difficult question,” they might say; or “well it really depends” is another answer. Clearly, neither of these is very satisfactory and yet both are correct. The IT community has struggled with qu- tions concerning the value of an organization’s investment in software and ha- ware ever since it became a significant item in organizational budgets. And like all questions concerning value, the first step is the precise determination of the object being assessed and the second step is the identification of the entity to which the value is beneficial. In software engineering both of these can be difficult. The p- cise determination of the object can be complex. If it is an entire information s- tem in an organizational context that is the object of interest, then boundary defi- tion becomes an issue. Is the hardware and middleware to be included? Can the application exist without any other applications? If however the object of interest is, say, a software engineering activity such as testing within a particular project, then the boundary definition becomes a little easier. But the measure of benefit may become a little harder.

Keywords

Information Technology (IT) Software Evaluation Software Measurement development knowledge management management organization risk management science and technology simulation software software development software engineering technology usa

Editors and affiliations

  • Stefan Biffl
    • 1
  • Aybüke Aurum
    • 2
  • Barry Boehm
    • 3
  • Hakan Erdogmus
    • 4
  • Paul Grünbacher
    • 5
  1. 1.Institute for Software TechnologyVienna University of TechnologyWienAustria
  2. 2.School of Information Systems, Technology and ManagementUniversity of New South WalesSydneyAustralia
  3. 3.Center for Software EngineeringUniversity of Southern CaliforniaLos AngelesUSA
  4. 4.Software Engineering NRC Institute for Information TechnologyNational Research Council CanadaOttawaCanada
  5. 5.Systems Engineering & AutomationJohannes Kepler University LinzLinzAustria

Bibliographic information

  • DOI https://doi.org/10.1007/3-540-29263-2
  • Copyright Information Springer-Verlag Berlin Heidelberg 2006
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Computer Science
  • Print ISBN 978-3-540-25993-0
  • Online ISBN 978-3-540-29263-0
  • About this book