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Next-Generation Systems and Software Cost Estimation. Wilson Rosa Technical Advisor Air Force Cost Analysis Agency (AFCAA) October 28, 2008. Problem Statement. Emerging technologies such as Systems of Systems (SoS) Model Driven Architecture (MDA) Enterprise Resource Planning (ERP)

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next generation systems and software cost estimation

Next-Generation Systems and Software Cost Estimation

Wilson Rosa

Technical Advisor

Air Force Cost Analysis Agency (AFCAA)

October 28, 2008

problem statement
Problem Statement
  • Emerging technologies such as
    • Systems of Systems (SoS)
    • Model Driven Architecture (MDA)
    • Enterprise Resource Planning (ERP)
    • Service-Oriented Architecture (SOA)
    • Commercial Off the Shelf (COTS)
    • Design for Reuse (RUSE)

are complicating AFCAA's job of producing accurate software cost estimates

next generation systems challenges
Next-Generation Systems Challenges
  • Lines of Code not appropriate for
    • Model Driven Architecture
    • COTS-Based Systems (SOA, ERP, etc.)
  • No guidelines for estimating beyond software design:
    • Infrastructure (servers, LAN, routers, etc.)
    • Concurrent Users
    • Enterprise Services (collaboration, discovery, etc.)
    • Data Migration, External Interfaces
    • Interoperability and Interdependency
  • Unfamiliar with total system size and cost drivers
  • Lack of Empirical Research – SOA, ERP, SoS, MDA
data challenges
Data Challenges
  • AFCAA has multiple software datasets
  • Unable to combine software datasets because of inconsistencies and lack of standardization
    • Schedule seems to be reported at program and not CSCI level -- all CSCI’s have same schedule
    • No reporting of % re-design, % re-coding, % re-test
    • No common counting method – logical, physical, etc.
    • No standard application type definitions
    • No common code counting tool
    • Product size only reported in lines of code
    • No reporting of COCOMO, SEER, PRICE parameters
    • No reporting of quality measures – defects, MTBF, etc.
parametric model challenges
Parametric Model Challenges
  • Most DoD Program Offices rely on software parametric models which have not been calibrated with recent DoD data
  • Parametric Models only cover software design not total system – infrastructure, users, etc.
  • Calibration will help reduce the program office estimating error rate
consequence significant cost growth
Consequence: Significant Cost Growth (%)

Source : *John McCrillis, 36th DOD Cost Analysis Symposium (2003)

**Defense Automated Cost Information System

  • Cost Agencies in conjunction with University of Southern Californiawill publish a manual to help analysts develop quick software estimates using reliable metrics from recent programs
data sources
Data Sources

Note: Expecting over 1600 CSCIs by 2010

data normalization
Data Normalization
  • USC will interview program offices and developers to obtain additional information…
    • COCOMO II Parameters
    • Reuse Type – auto generated, re-hosted, translated, modified
    • Reuse Source – in-house, third party
    • Degree-of-Modification – %DM, %CM, %IM
    • Method – Model Driven Architecture, Object-Oriented, Traditional
  • Available Data
    • DoDAF – System Views, Operational Views, etc.
    • Software Resource Data Report – Software Size, Effort, Schedule
    • Cost Analysis Requirements Description (CARD)
      • System Description, Users, Infrastructure, locations, interfaces, etc.
software cost manual content
Software Cost Manual Content

Chapter 1: Basic Software Cost Estimation

Chapter 2: Product Size Metrics

Chapter 3: Historical Growth

Chapter 4: Default Effective Size (ESLOC) Parameters

Chapter 5: Historical Productivity Dataset

Chapter 6: Default COCOMO Parameters

Chapter 7: SLIM-ESTIMATE Calibration

Chapter 8: Risk and Uncertainty Parameters

Chapter 9: Data Cleansing

Chapter 10: Space Software Cost Estimation

Chapter 11: Software Maintenance

chapter 4 esloc parameters
Chapter 4: ESLOC Parameters
  • Default values from recent programs
  • Based on Reuse Type and Reuse Source


chapter 5 historical productivity
Chapter 5: Historical Productivity
  • Overview and Guidelines
  • Historical Productivity Dataset by Application
  • Default Productivity Ranges by Application


significance of software cost metrics manual
Significance of Software Cost Metrics Manual
  • Collected data can be used for
    • Systems of Systems cost research
    • COCOMO improvement initiatives
    • Understanding relationships between Next-Generation Processes and COCOMO cost drivers can encourage researchers to explore new strategies to improve available cost models…
way ahead
Way Ahead
  • Short Term (2009-2010)
    • Send Software Data Call to program offices, developers, and USC Affiliates
    • Write Chapters 4 & 5 (2009)
    • Publish Software Cost Metrics Manual (2010)
  • Long Term (2010-2012)
    • ERP Cost Guide (2010)
    • Impact of MDA on Software Productivity (2010)
    • SOA Cost Study (2012)

Note: Any data you provide will not be attributed to your company or program,

but will be combined with like data from other sources and generic zed"

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