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IMPROVING THE SOFTWARE PROCESS WITH SPC
Anita D. CarletonSenior Member of the Technical StaffSoftware
Engineering Institute4500 Fifth AvenuePittsburgh, PA 15213E-mail:
[email protected]: (412) 268-7718Fax: (412) 268-5758
ABSTRACT
As most people know, statistical process control (SPC)
techniques are not new. SPC and its associated controlcharts were
developed by Walter Shewhart in the 1920s to gain control of
production costs and quality.
But these techniques have not been widely adopted in software
organizations. The focus of this presentation willbe to discuss how
SPC applies to improving the software process. We will present
examples of how software orga-nizations can apply SPC techniques so
they can predict (at least within limits) how a phenomenon may be
expectedto perform or vary in the future.
KEY WORDS
software process, software process improvement, statistical
process control
PURPOSE AND TARGET AUDIENCE
The purpose of this session is to provide an understanding of
the concepts and issues that lie behind SPC anddiscuss the steps
associated with effectively implementing and using SPC to manage
and improve software processes.
The target audience includes professionals whose key focus is on
using measurements to manage and improvesoftware processes.
KEY POINTS
We will discuss Figure 1, which shows a framework for measuring
process behavior (figure to appear in theforthcoming book by
Addison Wesley Measuring the Software Process: Statistical Process
Control for ProcessImprovement by William Florac and Anita
Carleton).
We will also discuss what insights can be learned from SPC
analysis of the software process:
Gain better insight during development as to how well activities
are following the process and how muchdeviation in process
performance is being observed.
Allow decision-making about risk and additional corrective
actions to be considered earlier in the lifecycle.
Gain insight into alternative analytical techniques that can be
used to better understand and improve soft-ware processes and to
better predict results and outcomes.
T108.carleton (179-180) 4/1/99 3:32 PM Page 179
180 ASQs 53rd Annual Quality Congress Proceedings
Know if a system was better or worse than prior systems
Understand what is a signal and what is not a signal and when to
react to a signal Say, the data says . . . Get earlier indication
of concerns Understand performance of one subsystem to another
CONCLUSION
The benefits to the attendees includes introducing and helping
attendees gain familiarity with some usefulprocesses, practices,
and methods for:
Using measurement data to control and improve process
performance Understanding issues and examples of what organizations
are facing as they address SPC for software Understanding what it
means to control and predict the software process
Figure 1. Framework for measuring process behavior.
T108.carleton (179-180) 4/1/99 3:32 PM Page 180
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