National Academies Press: OpenBook

Statistical Software Engineering (1996)

Chapter: Front Matter

Suggested Citation:"Front Matter." National Research Council. 1996. Statistical Software Engineering. Washington, DC: The National Academies Press. doi: 10.17226/5018.
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STATISTICAL SOFTWARE ENGINEERING

Panel on Statistical Methods in Software Engineering

Committee on Applied and Theoretical Statistics

Board on Mathematical Sciences

Commission on Physical Sciences, Mathematics, and Applications

National Research Council

National Academy Press
Washington, D.C. 1996

Suggested Citation:"Front Matter." National Research Council. 1996. Statistical Software Engineering. Washington, DC: The National Academies Press. doi: 10.17226/5018.
×

NOTICE: The project that is the subject of this report was approved by the Governing Board of the National Research Council, whose members are drawn from the councils of the National Academy of Sciences, the National Academy of Engineering, and the Institute of Medicine.

The National Academy of Sciences is a private, nonprofit, self-perpetuating society of distinguished scholars engaged in scientific and engineering research, dedicated to the furtherance of science and technology and to their use for the general welfare. Upon the authority of the charter granted to it by the Congress in 1863, the Academy has a mandate that requires it to advise the federal government on scientific and technical matters. Dr. Bruce Alberts is president of the National Academy of Sciences.

The National Academy of Engineering was established in 1964, under the charter of the National Academy of Sciences, as a parallel organization of outstanding engineers. It is autonomous in its administration and in the selection of its members, sharing with the National Academy of Sciences the responsibility for advising the federal government. The National Academy of Engineering also sponsors engineering programs aimed at meeting national needs, encourages education and research, and recognizes the superior achievement of engineers. Dr. Harold Liebowitz is president of the National Academy of Engineering.

The Institute of Medicine was established in 1970 by the National Academy of Sciences to secure the services of eminent members of appropriate professions in the examination of policy matters pertaining to the health of the public. The Institute acts under the responsibility given to the National Academy of Sciences by its congressional charter to be an adviser to the federal government and, upon its own initiative, to identify issues of medical care, research, and education. Dr. Kenneth I. Shine is president of the Institute of Medicine.

The National Research Council was organized by the National Academy of Sciences in 1916 to associate the broad community of science and technology with the Academy's purposes of furthering knowledge and advising the federal government. Functioning in accordance with general policies determined by the Academy, the Council has become the principal operating agency of both the National Academy of Sciences and the National Academy of Engineering in providing services to the government, the public, and the scientific and engineering communities. The Council is administered jointly by both Academies and the Institute of Medicine. Dr. Bruce Alberts and Dr. Harold Liebowitz are chairman and vice-chairman, respectively, of the National Research Council.

This project was supported by the Advanced Research Projects Agency, Army Research Office, National Science Foundation, and Department of the Navy's Office of the Chief of Naval Research. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the sponsors. Furthermore, the content of the report does not necessarily reflect the position or the policy of the U.S. government, and no official endorsement should be inferred.

Copyright 1996 by the National Academy of Sciences. All rights reserved.

Library of Congress Catalog Card Number 95-71101

International Standard Book Number 0-309-05344-7

Additional copies of this report are available from:
National Academy Press,
Box 285 2101 Constitution Avenue, N.W. Washington, D.C. 20055 800-624-6242 202-334-3313 (in the Washington metropolitan area)

B-676

Printed in the United States of America

Suggested Citation:"Front Matter." National Research Council. 1996. Statistical Software Engineering. Washington, DC: The National Academies Press. doi: 10.17226/5018.
×

PANEL ON STATISTICAL METHODS IN SOFTWARE ENGINEERING

DARYL PREGIBON,

AT&T Bell Laboratories,

Chair

HERMAN CHERNOFF,

Harvard University

BILL CURTIS,

Carnegie Mellon University

SIDDHARTHA R. DALAL,

Bellcore

GLORIA J. DAVIS,

NASA-Ames Research Center

RICHARD A. DEMILLO,

Bellcore

STEPHEN G. EICK,

AT&T Bell Laboratories

BEV LITTLEWOOD,

City University, London, England

CHITOOR V. RAMAMOORTHY,

University of California, Berkeley

Staff

JOHN R. TUCKER, Director

Suggested Citation:"Front Matter." National Research Council. 1996. Statistical Software Engineering. Washington, DC: The National Academies Press. doi: 10.17226/5018.
×

COMMITTEE ON APPLIED AND THEORETICAL STATISTICS

JON R. KETTENRING,

Bellcore,

Chair

RICHARD A. BERK,

University of California, Los Angeles

LAWRENCE D. BROWN,

University of Pennsylvania

NICHOLAS P. JEWELL,

University of California, Berkeley

JAMES D. KUELBS,

University of Wisconsin

JOHN LEHOCZKY,

Carnegie Mellon University

DARYL PREGIBON,

AT&T Bell Laboratories

FRITZ SCHEUREN,

George Washington University

J. LAURIE SNELL,

Dartmouth College

ELIZABETH THOMPSON,

University of Washington

Staff

JACK ALEXANDER, Program Officer

Suggested Citation:"Front Matter." National Research Council. 1996. Statistical Software Engineering. Washington, DC: The National Academies Press. doi: 10.17226/5018.
×

BOARD ON MATHEMATICAL SCIENCES

AVNER FRIEDMAN,

University of Minnesota,

Chair

LOUIS AUSLANDER,

City University of New York

HYMAN BASS,

Columbia University

MARY ELLEN BOCK,

Purdue University

PETER E. CASTRO,

Eastman Kodak Company

FAN R.K. CHUNG,

University of Pennsylvania

R. DUNCAN LUCE,

University of California, Irvine

SUSAN MONTGOMERY,

University of Southern California

GEORGE NEMHAUSER,

Georgia Institute of Technology

ANIL NERODE,

Cornell University

IMGRAM OLKIN,

Stanford University

RONALD F. PEIERLS,

Brookhaven National Laboratory

DONALD ST. P. RICHARDS,

University of Virginia

MARY F. WHEELER,

Rice University

WILLIAM P. ZIEMER,

Indiana University

Ex Officio Member

JON R. KETTENRING,

Bellcore

Chair,

Committee on Applied and Theoretical Statistics

Staff

JOHN R. TUCKER, Director

JACK ALEXANDER, Program Officer

RUTH E. O'BRIEN, Staff Associate

BARBARA W. WRIGHT, Administrative Assistant

Suggested Citation:"Front Matter." National Research Council. 1996. Statistical Software Engineering. Washington, DC: The National Academies Press. doi: 10.17226/5018.
×

COMMISSION ON PHYSICAL SCIENCES, MATHEMATICS, AND APPLICATIONS

ROBERT J. HERMANN,

United Technologies Corporation,

Chair

STEPHEN L. ADLER,

Institute for Advanced Study

PETER M. BANKS,

Environmental Research Institute of Michigan

SYLVIA T. CEYER,

Massachusetts Institute of Technology

L. LOUIS HEGEDUS,

W.R. Grace and Company

JOHN E. HOPCROFT,

Cornell University

RHONDA J. HUGHES,

Bryn Mawr College

SHIRLEY A. JACKSON,

U.S. Nuclear Regulatory Commission

KENNETH I. KELLERMANN,

National Radio Astronomy Observatory

KEN KENNEDY,

Rice University

THOMAS A. PRINCE,

California Institute of Technology

JEROME SACKS,

National Institute of Statistical Sciences

L.E. SCRIVEN,

University of Minnesota

LEON T. SILVER,

California Institute of Technology

CHARLES P. SLICHTER,

University of Illinois at Urbana-Champaign

ALVIN W. TRIVELPIECE,

Oak Ridge National Laboratory

SHMUEL WINOGRAD,

IBM T.J. Watson Research Center

CHARLES A. ZRAKET,

Mitre Corporation (retired)

NORMAN METZGER, Executive Director

Suggested Citation:"Front Matter." National Research Council. 1996. Statistical Software Engineering. Washington, DC: The National Academies Press. doi: 10.17226/5018.
×

Preface

The development and the production of high-quality, reliable, complex computer software have become critical issues in the enormous worldwide computer technology market. The capability to efficiently engineer computer software development and production processes is central to the future economic strength, competitiveness, and national security of the United States. However, problems related to software quality, reliability, and safety persist, a prominent example being the failure on several occasions of major local and national telecommunications networks. It is now acknowledged that the costs of producing and maintaining software greatly exceed the costs of developing, producing, and maintaining hardware. Thus the development and application of cost-saving tools, along with techniques for ensuring quality and reliability in software engineering, are primary goals in today's software industry. The enormity of this software production and maintenance activity is such that any tools contributing to serious cost savings will yield a tremendous payoff in absolute terms.

At a meeting of the Committee on Applied and Theoretical Statistics (CATS) of the National Research Council (NRC), participants identified software engineering as an area presenting numerous opportunities for fruitful contributions from statistics and offering excellent potential for beneficial interactions between statisticians and software engineers that might promote improved software engineering practice and cost savings. To delineate these opportunities and focus attention on contexts promising useful interactions, CATS convened a study panel to gather information and produce a report that would (1) exhibit improved methods for assessing software productivity, quality, reliability, associated risk, and safety and for managing software development processes, (2) outline a program of research in the statistical sciences and their applications to software engineering with the aim of motivating and attracting new researchers from the mathematical sciences, statistics, and software engineering fields t o tackle these important and pressing problem areas, and (3) emphasize the relevance of using rigorous statistical and probabilistic techniques in software engineering contexts and suggest opportunities for further research in this direction.

To help identify important issues and obtain a broad range of perspectives on them, the panel organized an information-gathering forum on October 11-12, 1993, at which 12 invited speakers addressed how statistical methods impinge on the software development process, software metrics, software dependability and testing, and software visualization. The forum also included consideration of nonstandard methods and select case studies (see the forum program in the appendix). The panel hopes that its report, which is based on the panel's expertise as well as information presented at the forum, will contribute to positive advances in software engineering and, as a subsidiary benefit, be a stimulus for other closely related disciplines, e.g., applied mathematics, operations research, computer science, and systems and industrial engineering. The panel is, in fact, very enthusiastic about the opportunities facing the statistical community and hopes to convey this enthusiasm in this report.

The panel gratefully acknowledges the assistance and information provided by a number of individuals, including the 12 forum speakers—T.W. Keller, D. Card, V.R. Basili, J.C. Munson, J.C. Knight, R. Lipton, T. Yamaura, S. Zweben, M.S. Phadke, E.E. Sumne r, Jr., W. Hill, and J. Stasko—four anonymous reviewers, the NRC staff of the Board on Mathematical Sciences who supported the various facets of this project, and Susan Maurizi for her work in editing the manuscript.

Page viii Cite
Suggested Citation:"Front Matter." National Research Council. 1996. Statistical Software Engineering. Washington, DC: The National Academies Press. doi: 10.17226/5018.
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Suggested Citation:"Front Matter." National Research Council. 1996. Statistical Software Engineering. Washington, DC: The National Academies Press. doi: 10.17226/5018.
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Contents

 

 

EXECUTIVE SUMMARY

 

1

1

 

INTRODUCTION

 

5

2

 

CASE STUDY: NASA SPACE SHUTTLE FLIGHT CONTROL SOFTWARE

 

9

   

Overview of Requirements

 

9

   

The Operational Life Cycle

 

10

   

A Statistical Approach to Managing the Software Production Process

 

10

   

Fault Detection

 

11

   

Safety Certification

 

12

3

 

A SOFTWARE PRODUCTION MODEL

 

13

   

Problem Formulation and Specification of Requirements

 

14

   

Design

 

14

   

Implementation

 

16

   

Testing

 

18

4

 

CRITIQUE OF SOME CURRENT APPLICATIONS OF STATISTICS IN SOFTWARE ENGINEERING

 

27

   

Cost Estimation

 

27

   

Statistical Inadequacies in Estimating

 

29

   

Process Volatility

 

30

   

Maturity and Data Granularity

 

30

   

Reliability of Model Inputs

 

31

   

Managing to Estimates

 

32

   

Assessment and Reliability

 

32

   

Reliability Growth Modeling

 

32

   

Influence of the Development Process on Software Dependability

 

36

   

Influence of the Operational Environment on Software Dependability

 

37

   

Safety-Critical Software and the Problem of Assuring Ultrahigh Dependability

 

38

   

Design Diversity, Fault Tolerance, and General Issues of Dependence

 

38

   

Judgment and Decision-making Framework

 

39

   

Structural Modeling Issues

 

40

   

Experimentation, Data Collection, and General Statistical Techniques

 

40

   

Software Measurement and Metrics

 

41

5

 

STATISTICAL CHALLENGES

 

43

   

Software Engineering Experimental Issues

 

43

   

Combining Information

 

46

   

Visualization in Software Engineering

 

48

Suggested Citation:"Front Matter." National Research Council. 1996. Statistical Software Engineering. Washington, DC: The National Academies Press. doi: 10.17226/5018.
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Statistical Software Engineering Get This Book
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This book identifies challenges and opportunities in the development and implementation of software that contain significant statistical content. While emphasizing the relevance of using rigorous statistical and probabilistic techniques in software engineering contexts, it presents opportunities for further research in the statistical sciences and their applications to software engineering.

It is intended to motivate and attract new researchers from statistics and the mathematical sciences to attack relevant and pressing problems in the software engineering setting. It describes the "big picture," as this approach provides the context in which statistical methods must be developed. The book's survey nature is directed at the mathematical sciences audience, but software engineers should also find the statistical emphasis refreshing and stimulating. It is hoped that the book will have the effect of seeding the field of statistical software engineering by its indication of opportunities where statistical thinking can help to increase understanding, productivity, and quality of software and software production.

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