By James Roberts
EEL 6883
Spring 2007

 Over 53% of software projects overrun by more than 50% in both budget and schedule
 Software overrun in budget is a failure
 Software overrun in schedule is a failure
 Goal of software engineering is to deliver software on time and within budget

 Automated Software Cost Estimation
– Look at history
–
–
Generalize data
Create equations
– Parametric

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SLOC – Source Lines of Code
DSI – Delivered Source Instructions
 Function Points

 COCOMO 81
 COCOMO II
 REVIC
 SLIM
 Others

 Developed by Barry Boehm in 81
 Based on historical database
 DSI is the input
 Three versions
– Basic Model
– Intermediate Model
– Detailed Model

 Updated the COCOMO 81 model
 Allows for
– Spiral development
– Rapid prototyping
– COTS integration
– OO Design
 Uses SLOC

 Revised Intermediate COCOMO
 Developed by Ray Kile
 Updated to use Air Force project data
 Adds a mode for Ada development
 Inputs are the same as COCOMO 81

 Software Life-Cycle Model
 Developed by Larry Putnam
 Uses a Rayleigh distribution
– Project personnel vs. Time
 Intended for large projects
 Fewer parameters

 Based on the SLIM model
 Windows based
 Easy to use
 Several different wizards for quickly generating an estimate
 Five steps to create an estimate

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Based on the COCOMO model
Windows based
Easy to use
Many different COCOMO variations
Create Estimate Wizard
Many parameters required
Highly configurable
Full featured demo version available

 Based on proprietary COCOMO-like models
 Windows based
 Moderately easy to use
 Create Estimate Wizard
 Few parameters required up front
 Highly configurable
 Poor demo version

 Would recommend the Softstar CoStar software
 Software Cost Estimation is important for any program manager
 These tools are vital to quickly generating estimates for success

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1.
Dave Srulowitz, M.B., Vic Helbling. Software Estimation . 2001
[cited; Available from: http://www.saspin.org/SASPIN_Apr2001_COCOMO.pdf.
2.
Briand, L.C., et al. An assessment and comparison of common software cost estimation modeling techniques . 1999.
3.
Boehm, B.W., Software Engineering Economics . 1st ed. 1981:
Prentice-Hall.
4.
COCOMO II . [cited; Available from: http://en.wikipedia.org/wiki/COCOMO_II.
5.
Boehm, B.C., B.; Horowitz, E.; Madachy, R.; Shelby, R.;
Westland, C. An Overview of the COCOMO 2.0 Software Cost Model . in Software Technology Conference . 1995.
6.
Systems, S. Overview of COCOMO . 2007 [cited; Available from: http://www.softstarsystems.com/overview.htm.

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7.
C. Abts, B.C., S. Devnani-Chulani, E. Horowitz, R. Madachy, D. Reifer, R.
Selby, B. Steece, COCOMO II Model Definition Manual. Technical report,
Center for Software Engineering, USC.
1998.
8.
Albrecht, A., Function Points: A New Way of Looking at Tools . 1979.
9.
Parametric Cost Estimating Handbook.
US Dept. of Defense,
Washington D.C., 1995.
10.
Agency, D.C.M. DCMA Guidebook - Software Acquisition Management .
2007 [cited.
11.
Boehm, B.A., C.; Chulani, S., Software Development Cost Estimation
Approaches - A Survey.
Annals of Software Engineering, 2000. 10 (1-4): p. 177-
205.
12.
Chris, F.K., An empirical validation of software cost estimation models.
Commun. ACM, 1987. 30 (5): p. 416-429.
13.
Sultanodlu, S. Software Measurement, Cost Estimation, SLIM,
COCOMO . 1998 [cited; Available from: http://yunus.hacettepe.edu.tr/~sencer/cocomo.html