Deriving Metrics 81
On the other side of it, how effectively we use the few metrics is more important
than the vocabulary volume. When managers use metric vocabulary in day-to-day
dialogues with team members, a new culture can be created. Here is the case of one
manager who wanted to make his software more maintainable. He chose to ask his pro-
grammer for a definition of maintainability; the response was swift, the programmer
found out, from the literature, a formula for maintainability index. e manager left the
subject at that and did not press for either the use of this index or the maintainability
data on the code. e very definition of the maintainability index triggered a chain of
responses from the programmer, from a realization that maintainability is important to
improve code maintainability. Numbers were gathered only later, in subsequent trials.
e numbers were not shared with others. All that the programmer needed was direc-
tion, and the manager showed that he was a great leader by giving the direction.
Lessons:
Metrics thrive under great leadership.
Some metrics are very personal.
Box 5.5 Meet the exPeRt—Watt s. huMPhRey
Watt S. Humphrey (1927–2010), known as the father of software quality,
was born in Battle Creek, Michigan. He enlisted in the Navy at 17 years of
age to help ght in World War II. After his enlistment was up, he enrolled
in the University of Chicago where he graduated with a bachelor’s degree in
physics. He earned his master’s degree in physics from the Illinois Institute of
Technology and then a master’s degree in business administration from the
University of Chicago.
He started his career with Sylvania in Boston and then moved to IBM,
where he rose through the ranks to become director of development and vice
president of technical development. In that job, he supervised software devel-
opment in 15 laboratories that were spread out in seven countries. ere were
4000 software engineers working under him.
82 Simple Statistical Methods for Software Engineering
Review Questions
1. What are the five categories of metrics used in software projects?
2. What is the GQM paradigm? What are its limitations?
3. What is the GQ(I)M paradigm? What are the advantages of GQ(I)M over
GQM?
4. What is the primary motivator of project metrics?
5. How are process metrics selected?
Exercises
1. Develop a metric plan to manage software testing.
2. Develop a metric plan to control design complexity.
3. Develop a metric plan to control code quality.
4. Develop a metric plan to control requirements volatility.
5. Develop a metric plan to manage software maintenance.
References
1. V. R. Balili and G. Caldiera, Goal Question Metric Paradigm, John Wiley, 1994.
2. R. E. Park, W. B. Goethert, W. A. Florac, Goal Driven Software Measurement—
AGuidebook, SEI Handbook CMU/SEI-96-HB-002, 1996.
3. R. S. Kaplan and D. P. Norton, e Balanced Scorecard: Translating Strategy into Action,
Harvard Business Review Press, Harvard College, 1996.
At 60 years of age, when many people are thinking of retiring, Mr.
Humphrey embarked on a new career at Carnegie Mellon University, where
he established the software process program that instilled a discipline to soft-
ware development.
His colleague, Anita Carleton, the director of the Carnegie Mellon
Software Engineering Institute’s Software Engineering Process Management
Program, said that before Mr. Humphrey came along, software engineers
created programs by coding and testing. He changed the culture of the dis-
cipline to develop a more systematic approach to planning, developing, and
releasing new software.
His work earned him the National Medal of Technology, which was pre-
sented to him by President George W. Bush in 2005.
Deriving Metrics 83
Suggested Readings
Aczel, A. D. and J. Sounderpandian, Complete Business Statistics, McGraw-Hill, London,
2008.
Austin, R. D., Measuring and Managing Performance in Organizations, John Wiley & Sons, Inc.,
Hoboken, NJ, June 1, 1996.
Defeo, J. and J. M. Juran, Jurans Quality Handbook: e Complete Guide to Performance
Excellence, 6th ed., McGraw-Hill Professional, London, 2010.
Juran, J. M. and A. Blanton Godfrey, Juran Quality Hand Book, 5th ed., McGraw-Hill
Professional, London, 2010. Available at http://www.pqm-online.com/assets/files/lib
/juran.pdf.
Kan, S. H., Metrics and Models in Software Quality Engineering, Addison-Wesley Longman
Publishing Co. Inc., Boston, 2002.
Kitchenham, B., Software Metrics: Measurement for Software Process Improvement, Blackwell
Publishers, Inc., Cambridge, MA, 1996.
Laird, L. M. and M. C. Brennan, Software Measurement and Estimation: A Practical Approach,
Quantitative Software Engineering Series, Wiley-Blackwell, 2006.
Parasoft Corporation, When, Why, and How: Code Analysis, August 7, 2008. Available at
http://www.codeproject.com/Articles/28440/When-Why-and-How-Code-Analysis.
Parmenter, D., Key Performance Indicator, John Wiley & Sons, 2007.
Pearson, Software Quality Metrics Overview, Metrics and Models in Software Quality
Engineering, 2nd ed., 2002. Available at http://www.pearsonhighered.com /samplechapter
/0201729156.pdf.
Software Metrics, Available at http://www.sqa.net/softwarequalitymetrics.html.
Software Process and Project Metrics, Chapter 4, ITU Department of Computer Engineering–
Software Engineering. Available at http://web.itu.edu.tr/gokmen/SE-lecture-2.pdf.
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