Early Effort Estimation of Business Data-processing Enhancements

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Early Effort Estimation of Business
Data-processing Enhancements

• CS 689
• November 30, 2000
• By
• Kurt Detamore

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Background

• Software effort estimation has been researched
  for several years
• Most research has involved medium to large
  development projects
• Concentration on small projects for external
  customers

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Importance of Accurate Estimates

• Increased customer satisfaction
• Increased productivity of development staff
• Competitive advantage in a bidding war for
  services contract

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Problem

• The estimation of small development projects,
  specifically, the development of customizations
  or enhancements to existing products to meet
  customer needs has not been studied.
• Estimation of small projects in many cases is a
  best guess estimate.

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Existing Tools

• COCOMO (Boehm)
• COCOMO II (Boehm)
• SLIM (Putnam)
• Function Point Analysis (Albrecht)
• Feature-based model (Mukhopadhyay)

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References

1. B. W. Boehm, Software Engineering Economics.
   Englewood Cliffs, NJ, Prentice-Hall, 1981.
2. L. H. Putnam, A General Empirical Solution to
   the Macro Software Sizing and Estimating
   Problem, IEEE Transactions on Software
   Engineering, vol. SE-4, pp. 345-361, July 1978.
3. A. J. Albrecht and J. Gaffney, Software
   function, source lines of code, and development
   effort prediction A software science
   validation, IEEE Transactions on Software
   Engineering, vol. SE-9, pp. 639-648, June 1983.
4. B. W. Boehm, et al., An Overview of the COCOMO
   2.0 Software Cost Model, Software Technology
   Conference, April 1995.
5. C. F. Kemerer, An empirical validation of
   software cost estimation models, Communications
   of the ACM, vol. 30, pp. 416-429, May 1987.

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References (contd)

1. T. Mukhopadhyay and S. Kekre, Software effort
   models for early estimation of process control
   applications, IEEE Transactions on Software
   Engineering, vol. 18, pp. 915-924, October 1992.
2. B. A. Kitchenham and N. R. Taylor, Software
   project development cost estimation, Journal of
   Systems and Software, vol. 5, pp. 267-278,
   November 1985.
3. S. Conte, H. Dunsmore, and V. Shen, Software
   Engineering Metrics and Models,
   Benjamin/Cummings, Menlo Park, CA, 1986.

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Limitations of COCOMO

• Must be calibrated to provide accurate results
• Not accurate for incrementally developed projects
• Uses lines of code to calculate estimates

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Limitations of SLIM

• Proprietary calculations
• Requires significant technical knowledge to
  implement
• Requires two of the following
• Size greater than 5000 lines
• Effort greater than 1.5 man.years
• Development time greater than 6 months
• Uses lines of code to calculate estimates

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Function Point Analysis

• Must be calibrated to be accurate
• Fourteen general characteristics factors rated on
  a scale from 0 (no influence) to 5 (essential)
• Developed using business data processing systems
• Non-technical staff can be trained to execute
  this method
• Guidelines exist for counting function points in
  enhancement projects
• Function Points can be counted after requirements
  analysis

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Fourteen General Characteristics Factors

1. Does the system require reliable backup and
   recovery?
2. Are data communications required?
3. Are there distributed processing functions?
4. Is performance critical?
5. Will the system run in an existing, heavily
   utilized operating environment?
6. Does the system use on-line data entry?
7. Does the on-line data entry require the input
   transaction to be built over multiple screens or
   operations?

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Fourteen General Characteristics Factors

1. Are the master files updated on-line?
2. Are the inputs, outputs, files or enquiries
   complex?
3. Is the internal processing complex?
4. Is the code designed to be re-usable?
5. Are conversion and installation included in the
   design?
6. Is the system designed for multiple installations
   in different organizations?
7. Is the application designed to facilitate change
   and ease of use by the user?

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Feature-based Model

• Designed to use as an early estimation tool
• Requires only limited information
• Developed for Process Control Applications

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Calculations for Feature-based Model

• Model for calculating function counts from
  user-defined features
• Model for calculating lines of code from
  user-defined features

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Research Objectives

• Develop a calibrated Function Point Analysis
  (FPA) estimation model with a margin of error
  less than 40
• Develop an early estimation model using the
  application features as the key to estimation
  with a margin of error less than 25

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Research Design

• Use the FPA model
• Evaluate approximately 40 projects completed over
  the past two years
• Individual project size between 5 days and 150
  days of total effort
• Calculate the language level of the proprietary
  language in use
• Calibrate the 14 general characteristics factors

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Research Design (contd)

• Develop feature-based model
• Identify groups of features to determine function
  counts and/or lines of code
• Addition of fields to screens
• Creation of new screens
• Creation of new functionality within a screen
• Evaluate existing projects to determine constant
  values for the formulas

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Data Analysis

• Calculate magnitude of relative error for FPA and
  feature-based models
• Calculate correlation of the estimates for each
  model

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Facilities and Resources

• No special resources are needed
• Tools used
• Microsoft Excel
• WinStat

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Schedule

• January 2001 Proposal accepted and training on
  FPA completed
• February to June 2001 FPA research
• Possible publication of FPA research results
• July to November 2001 Feature-based model
  analysis
• December 2001 Article submitted for publication
  to IEEE Transactions on Software Engineering

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Deliverables

• Calibrated FPA model
• Feature-based model adapted for business
  data-processing applications
• Research report which details accuracy and
  consistency of models

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Conclusion

• Research on effort estimation of small,
  incremental development projects has not been
  adequately provided up to this point
• The results of this research will provide tools
  to improve the accuracy and consistency of
  estimates for these development projects

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Any Questions?