COCOMO Suite

1
COCOMO Suite
Ray Madachy madachy_at_usc.edu CSCI 510 September
21, 2005
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Agenda

• COCOMO II refresher
• Modeling methodology and model status
• Suite overview
• Emerging extensions
• Model unification
• Addendum selected model details
• References and further information

3
COCOMO II Overview

• Software product size estimate
• Software product, process, computer, and personal
  attributes
• Software reuse, maintenance, and increment
  parameters
• Software organizations Project data

COCOMO

• Software development and maintenance
• Costs (effort)
• Schedule estimates
• Distributed by phase, activity, increment

COCOMO locally calibrated to organizations data
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Purpose of COCOMO II

• To help people reason about the cost and schedule
  implications of their software decisions
• Software investment decisions
• When to develop, reuse, or purchase
• What legacy software to modify or phase out
• Setting project budgets and schedules
• Negotiating cost/schedule/performance tradeoffs
• Making software risk management decisions
• Making software improvement decisions
• Reuse, tools, process maturity, outsourcing

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COCOMO II Model Stages
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COCOMO II Scope of Outputs

• Provides the estimated software development
  effort and schedule for MBASE/RUP
• Elaboration
• Construction

LCO
LCA
IOC
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Agenda

• COCOMO II refresher
• Modeling methodology and model status
• Suite overview
• Emerging extensions
• Model unification
• Addendum selected model details
• References and further information

8
USC-CSE Modeling Methodology
Analyze existing literature Step 1
Concurrency and feedback implied
Perform Behavioral analyses Step 2
Identify relative significance Step 3
Perform expert-judgment Delphi assessment,
formulate a-priori model Step 4
Gather project data Step 5
Determine Bayesian A-Posteriori model Step 6
Gather more data refine model Step 7
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Status of Models
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General COCOMO Form
PM A (? Size)?B ?(EM)
Where PM Person Months A calibration
factor Size measure(s) of functional size of
a software module that has an additive effect on
software development effort B scale factor(s)
that have an exponential or nonlinear effect on
software development effort EM effort
multipliers that influence software development
effort
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Agenda

• COCOMO II refresher
• Modeling methodology and model status
• Suite overview
• Emerging extensions
• Model unification
• Addendum selected model details
• References and further information

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COCOMO Suite Quantities Estimated
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COCOMO Suite Sizing
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COCOMO Suite Phase/Activity Distribution
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Typical Model Usage
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High Level Partitioning of Cost Models
COSOSIMO
SOS
System of System
Architecting
COSYSMO
Integration/Test
System
System Integration/Test
Architecting
Requirements Analysis
Software
Software Acceptance Test
COCOMO II
Preliminary Design
Integration
Detailed Design
Unit Test
Coding
COCOTS
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Agenda

• COCOMO II refresher
• Modeling methodology and model status
• Suite overview
• Emerging extensions
• Model unification
• Addendum selected model details
• References and further information

18
Emerging Extensions

• COCOMO-Dependent Extensions
• COQUALMO software quality
• iDAVE software dependability
• COPLIMO product line investment
• CORADMO rapid application software development
• COPROMO productivity improvement
• Emerging Independent Extensions
• COCOTS software commercial off the shelf
• COSYSMO systems engineering
• COSOSIMO systems of systems
• Dynamic COCOMO dynamic vs. static modeling

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Constructive Quality Model COQUALMO

• Predicts the number of residual defects in a
  software product
• Enables 'what-if' analyses that demonstrate the
  impact of
• various defect removal techniques
• effects of personnel, project, product and
  platform characteristics on software quality.
• Provides insights into
• Probable ship time
• Assessment of payoffs for quality investments
• Understanding of interactions amongst quality
  strategies

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COQUALMO Operational Concept
COCOMO II
Software development effort, cost and schedule
estimate
COQUALMO
Software Size Estimate
Defect Introduction Model
Software platform, Project, product and personnel
attributes
Number of residual defects Defect density per
unit of size
Defect Removal Model
Defect removal profile levels Automation,
Reviews, Testing
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COQUALMO Defect Removal Rating Scales
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COQUALMO Defect Removal Estimates - Nominal
Defect Introduction Rates
Delivered Defects / KSLOC
Composite Defect Removal Rating
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Information Dependability Attribute Value
Estimator iDAVE

• iDAVE estimates and tracks software
  dependability Return on Investment (ROI)
• Help determine how much dependability is enough
• Help analyze and select the most cost-effective
  combination of software dependability techniques
• Use estimates as a basis for tracking
  performance
• Based on COCOMO II and COQUALMO cost models and
  Value Estimating Relationships (VERs)
• Used to reason about the ROI of software
  dependability investments
• Dependability defined as a composite property
  that integrates such attributes as availability,
  reliability, safety, security, survivability and
  maintainability

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iDAVE Operational Concept
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Constructive Product Line Investment Model
COPLIMO

• Supports software product line cost estimation
  and ROI analysis within the scope of product line
  life cycle
• Consists of two components
• Product line development cost model
• Annualized post-development life cycle extension
• Based on COCOMO II software cost model
• Statistically calibrated to 161 projects,
  representing 18 diverse organizations

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COPLIMO Operational Concept
COPLIMO

• For set of products
• Average product size (COCOMO II cost drivers)
• Percent mission-unique, reused-with-modifications,
  black-box reuse
• Relative cost of reuse (RCR) and relative cost of
  writing for reuse (RCWR) factors

• As functions of
• products, years in
• life cycle
• Non-product line effort
• Product line investment (effort)
• Product line savings (ROI)

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Constructive Rapid Application Development Model
CORADMO

• Calculates/predicts for smaller, rapid
  application development projects
• Schedule
• Personnel
• Adjusted effort
• Allocates effort and schedule to the stages,
  which are anchored at points in a development
  life cycle
• Scope includes inception, elaboration, and
  construction

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CORADMO Factors

• Reuse and Very High Level Languages
• Development Process Reengineering and
  Streamlining
• Collaboration Efficiency
• Architecture/Risk Resolution
• Prepositioning Assets
• RAD Capability and Experience

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Constructive Productivity Model COPROMO

• Determines impact of technology investments on
  model parameter settings
• Predicts the most cost effective allocation of
  investment resources in new technologies intended
  to improve productivity
• Uses COCOMO II, COPSEMO, and CORADMO models as
  assessment framework
• Well-calibrated to 161 projects for effort,
  schedule
• Subset of 106 1990s projects for
  current-practice baseline
• Extensions for Rapid Application Development
  formulated

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Constructive COTS Model COCOTS

• Estimates the effort associated with the
  integration of Commercial-Off-The-Shelf (COTS)
  software products
• Scope includes inception, elaboration, and
  construction
• Model has four components
• Assessment
• Tailoring
• Glue code
• System volatility
• Effort reported by COCOTS is the sum of the
  efforts from each of the four components
• Can be used in conjunction with COCOMO II to
  estimate new software development with COTS
  integration

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COCOTS Operational Concept

• COTS Classes
• Candidates/Class
• Tailoring Complexity
• Glue code size cost drivers
• COCOMO II application effort (separate from COTS)
• COTS volatility rework ()
• Rework due to COTS requirements changes ()
• Rework due to non-COTS requirements changes ()

Assessment
Tailoring
COCOTS
Effort
Glue Code
Volatility
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COCOMO vs. COCOTS Cost Sources

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Constructive System Engineering Cost Model
COSYSMO

• Covers full system engineering lifecycle (maps to
  ISO/IEC 15288)
• Life cycle stages being used in COSYSMO Project
• Estimates standard Systems Engineering WBS tasks
  (based on EIA/ANSI 632)
• Developed with USC-CSE Corporate Affiliate
  sponsorship and INCOSE participation

Conceptualize
Operate, Maintain, or Enhance
Replace or Dismantle
Transition to Operation
Oper Test Eval
Develop
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COSYSMO Operational Concept
Requirements Interfaces Scenarios
Algorithms 3 Volatility Factors
Size Drivers
COSYSMO
Effort
Effort Multipliers

• Application factors
• 8 factors
• Team factors
• 6 factors
• Schedule driver

Calibration
WBS guided by EIA/ANSI 632
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COSYSMO Effort Multipliers

• Application Factors
• Requirements understanding
• Architecture complexity
• Level of service requirements
• Migration complexity
• Technology Maturity
• Documentation Match to Life Cycle Needs
• and Diversity of Installations/Platforms
• of Recursive Levels in the Design

• Team Factors
• Stakeholder team cohesion
• Personnel/team capability
• Personnel experience/continuity
• Process maturity
• Multisite coordination
• Tool support

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Constructive System-of-System Cost Model
COSOSIMO

• Parametric model to estimate the effort
  associated with the definition and integration of
  software-intensive system of systems components
• SoS abstraction
• Architecting
• Source selection
• Systems acquisition
• Integration and test
• Change management effort
• Includes at least one size driver and 6
  exponential scale factors related to effort
• Targets input parameters that can be determined
  in early phases

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COSOSIMO Operational Concept
Size Drivers

• Interface-related eKSLOC
• Number of logical interfaces at SoS level
• Number of operational scenarios
• Number of components

COSOSIMO
SoS Definition and Integration Effort
Exponential Scale Factors

• Integration simplicity
• Integration risk resolution
• Integration stability
• Component readiness
• Integration capability
• Integration processes

Calibration
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Agenda

• COCOMO II refresher
• Modeling methodology and model status
• Suite overview
• Emerging extensions
• Model unification
• Addendum selected model details
• References and further information

39
Model Unification Main Issues

• For each individual model as well as the unified
  model
• Objectives Strategies
• Inputs/scope of work
• Output/scope of estimate
• Assumptions of each model
• Stakeholders for each model
• Counting Rules
• Sponsorship (FCS, Model-Based Acq.)
• PhD dissertation critical mass
• Data sources

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Unification Goals

• Allow more comprehensive cost exploration with
  respect to
• Development decisions
• Investment decisions
• Established project budget and schedules
• Client negotiations and requested changes
• Cost, schedule, performance, and functionality
  tradeoffs
• Risk management decisions
• Process improvement decisions

• Affiliate request Provide a single unified tool
  to allow users to
• Specify
• System and software components comprising the
  software system of interest
• Composition and characteristics of components
• Receive
• A set of comprehensive outputs for system
  engineering, software development, and
  system-of-systems integration
• Adjusted using the appropriate special-purpose
  extensions

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Issue 1 Objectives Strategies

• First pass and future enhancements
• Framework (Goal-Quality-Metric model approach)
• Restate objectives for existing models
• COCOMO II
• COCOTS
• COSYSMO
• COSOSIMO
• CORADMO
• COQUALMO
• Develop objectives for unified cost model
• Operational scenario(s) for each model

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Issue 2 Inputs/scope of work

• Need to define on several levels
• To determine scope of work to be estimated
• To determine system of interest/viewpoint and
  system component characteristics
• To determine specific sub-model inputs
• Life cycle model
• Single user interface
• A single definition for each parameter/driver
  (eg. TEAM, PMAT, etc.) vs, context-specific
  definitions for parameters with common names
  across models
• Need to determine which components can be
  estimated as relatively independent pieces vs.
  tightly coupled components

43
Issue 3 Output/scope of estimate

• Single value for all integrated models (default
  152 hours per person-month)
• Normalized PM for calibration
• Backward compatibility to existing models
• What set of bins should be used for initial
  effort outputs?
• What additional levels of granularity should be
  provided?
• By phase/stage?
• By labor category?
• By activities?
• Break out by sub-models?
• Increments? (i.e., COINCOMO)
• How will an Integrated Master Schedule be
  developed?
• Effort schedule as a function of risk
• Projected productivity

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Issue 4 Assumptions of each model
Model Life Cycle Stages
COCOMO II COCOTS COSYSMO COSOSIMO
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Issue 5 Users for each model

• Acquirers, SW developers, estimators, systems
  engineers, managers, executives, or accountants
  who are interested in
• Software development (COCOMO II)
• Commercial off the shelf software (COCOTS)
• Systems engineering (COSYSMO)
• Software quality (COQUALMO)
• Software rapid application development (COPSEMO,
  CORADMO)
• Software system of systems integration (COSOSIMO)
• ROI/Investment analysis (iDave, COPLIMO)

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Issue 6 Counting Rules Definitions

• Inputs
• Size drivers (VHLLs, FPs, APs, Use Case Points,
  KSLOC, REQS, ALG, I/F, SCEN, Components, etc.)
• Model inputs (cost drivers, scale factors)
• Outputs
• Effort distributions
• Phase, activity, or labor categories
• Schedule
• Defects
• cost
• Risk
• Productivity

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Additional Analysis in Progress

• Cost Drivers
• Scale Factors

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Long Term Vision
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Agenda

• COCOMO II refresher
• Modeling methodology and model status
• Suite overview
• Emerging extensions
• Model unification
• Addendum selected model details
• COCOTS
• COPLIMO
• COSYSMO
• COSOSIMO
• References and further information

50
COTS Software Integration Lifecycle

• COTS Software Integration Lifecycle
• 1) Qualify COTS product
• 2) Perform system requirements
• 3) Administer COTS software acquisition
• 4) Prototype the system including COTS software
• 5) Fully integrate COTS software and interface
  code
• 6) Test completed prototype

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COTS Integration Sources of Effort

• COTS Assessment (pre- and post- commitment)
• Of functionality, performance, interoperability,
  etc.
• COTS Tailoring and Tuning
• Effects of platform, other COTS products
• Glue Code Development
• Similar to other Cost Xpert estimation
• Application Volatility Due to COTS
• COTS volatility, shortfalls, learning curve
• Added Application VV Effort
• COTS option and stress testing
• Debugging complications, incorrect fixes

52
Traditional vs. COTS Cost Sources

• LCO/
• Reqts.
• Review

• LCA/
• Design Review

• IOC/
• Beta Test

3) COTS/Application Glue Code Development and
Test
1) COTS Assessment
2) COTS Tailoring
Staffing
Application Code Development
4) Increased Application Effort due to COTS
Volatility
Time
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Current Scope of COTS Model

• COTS model covers
• assessment
• tailoring
• glue code development and integration
• impact of new releases (volatility)
• It does not cover
• cost of re-engineering business processes
• vendor management
• licenses
• training (for COTS integrators or end users)
• COTS platform or tool experience or maturity
• Covered by PLEX, LTEX, PVOL, TOOL environmental
  factors

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Assessment Effort Inputs

• Initial Filtering of COTS products
• estimate of the total number of candidate COTS
  components to be filtered
• More detailed assessment of specific candidates
  against attributes that are important
• class(es) of COTS components to be assessed
• for each class,
• number assessed
• attributes considered

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Assessment Submodel
Initial Filtering Effort (IFE)
)
(
)
(
S
Average Filtering Effort for product class
COTS Candidates in class filtered
Over all classes
Detailed Assessment Effort (DAE)
)
(
)
(
S
Average Assessment Effort for product class
COTS Candidates in class detailed assessed
Over all classes, by project domain
Qualified by assessment attributes most
associated with that class
Final Project Assessment Effort (FPAE) IFE DAE
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Assessment Attributes
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Tailoring Effort Inputs

• COTS tailoring - activities required to prepare
  or initialize a component for use in a specific
  system
• Tailoring includes
• parameter specification
• script writing
• GUI screen specification
• Report specification
• Security/Access Protocol initialization and set
  up
• For each class of COTS component,
• rate the complexity of tailoring for each of the
  above activities

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Tailoring Submodel
where
TCQr,class Tailoring Complexity Qualifier,
calibrated within a class, for each of
five possible ratings from Very Low to Very
High, and with the
TCQNOMINAL 1.0
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Tailoring Complexity Table
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Glue Code Inputs

• Definition of glue code
• code needed to facilitate data or information
  exchange between the COTS component and the
  system into which it is being integrated
• code needed to provide required functionality
  missing in the COTS component AND which depends
  on or must interact with the COTS component
• Estimate of the total delivered lines of glue
  code
• Estimate of glue code rework due to COTS
  volatility or requirements volatility

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Glue Code Inputs (continued)

• Integration Personnel
• Integrator experience with product (VL - VH)
• Integrator personnel capability (VL - VH)
• Integrator experience with COTS integration
  process (L - VH)
• Integrator personnel continuity (VL - VH)
• COTS Component
• COTS product maturity (VL - VH)
• COTS supplier product extension willingness (L -
  VH)
• COTS product interface complexity (L - VH)
• COTS supplier product support (L - VH)
• COTS supplier provided training and documentation
  (VL - VH)

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Glue Code Inputs (continued)

• Application/System
• Constraints on system/subsystem reliability (L -
  VH)
• Constraints on system/subsystem technical
  performance (N-VH)
• System portability (N - VH)
• Application architectural engineering (VL - VH)

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Glue Code Submodel

• A - a linear scaling constant
• Size - of the glue code in SLOC or FP
• Breakage - of the glue code due to change in
• requirements and/or COTS volatility
• Effort Multipliers - 13 parameters, each with
  settings
• ranging VL to VH
• B - an architectural scale factor with settings
  VL to VH

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Glue Code Cost Drivers
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Volatility Inputs

• Captures impact of new COTS releases on the
  custom/new application effort
• Inputs
• Estimate of new development effort (derived via
  Cost Xpert - traditional)
• Percentage of new development rework due to
• requirements changes
• COTS volatility
• Note This submodel is being revised

66
Volatility Submodel
Approximate Model Detailed Model with Cost
Xpert Parameters BRAK COTS application
code breakage due to COTS volatility BRAK
application code breakage otherwise S
Cost Xpert scale factor EAF
Effort Adjustment Factor (product of
effort multipliers)

67
Total COTS Integration Cost Estimate
xTotal Integration Effort (in Person-Months)
Assessment Effort Tailoring Effort Glue
Code Effort Volatility Effort where
Assessment Effort Filtering Effort Final
Selection Effort Total integration Cost
(Total Integration Effort) (/Person-Month)
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Agenda

• COCOMO II refresher
• Modeling methodology and model status
• Suite overview
• Emerging extensions
• Model unification
• Addendum selected model details
• COCOTS
• COPLIMO
• COSYSMO
• COSOSIMO
• References and further information

69
COPLIMO Background

• Benefits vs. Costs of product line
• Does product line pay off?
• Traditional product line cost estimation models
  mostly underestimate the ROI for product lines by
  focusing only on development savings
• Apply RCWR surcharge to entire product not only
  to the reused portions
• If life cycle costs are considered, high payoff
  comes from a smaller code base to undergo
  maintenance
• COPLIMO life cycle model
• Addresses the shortfalls with a representative
  set of parameters based on experience in aircraft
  and spacecraft product line domains
• Based on COCOMO II parameters calibrated to 161
  projects, empirical data on nonlinear reuse
  effects

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COPLIMO Model Overview

• Based on COCOMO II software cost model
• Statistically calibrated to 161 projects,
  representing 18 diverse organizations
• Based on standard software reuse economic terms
• RCWR Relative Cost of Writing for Reuse
• RCR Relative Cost of Reuse
• Avoids investment overestimation, savings
  underestimation
• Avoids RCWR for non-reused components
• Includes savings from smaller life-cycle code
  base
• Provides experience-based default parameter
  values
• Simple Excel spreadsheet model
• Easy to modify, extend, interoperate

71
COPLIMO - RCWR

• Development for Reuse (RUSE)
• In COCOMO II database, 11 out of 161 projects
  rated as VH for RUSE, and 1 rated as XH
• Productivity Range of RUSE
• Highest rating / Lowest rating 1.24/0.95 1.31
• And two other contributing variables
• Required Reliability (RELY)
• Degree of Documentation (DOCU)

72
COPLIMO RCWR (Cont.)

• Required Reliability (RELY)
• Constraints At least Nominal for Nominal and
  High RUSE ratings, at least High for Very High
  and Extra High RUSE ratings
• Degree of Documentation (DOCU)
• Constraint No more than one level below the RUSE
  rating

73
COPLIMO RCR

• Reused, or Black Box (unmodified code) RCR model
• Assessment and Assimilation (AA) factor
• Adapted, or White Box (modified code) RCR model
• AA
• Non-Linear Model

74
Basic COPLIMO Development Cost Model (1)

• Simplifying assumptions about uniformity and
  stability
• Every product roughly the same size (PSIZE)
• Roughly the same fractions of product-specific
  (PFRAC), adapted (AFRAC), and reused (RFRAC)
  software
• Inputs and outputs

75
Basic COPLIMO Development Cost Model (2)

• RCR parameters

• RCWR
• RCWR RUSE DOCU RELY
• 1 product development effort
• Non-PL Effort for developing N similar products
• PMNR (N) N ? A? (PSIZE)B ? ? (EM)
• Where PSIZE is the general software product size,
  A and B are the COCOMO II calibration coefficient
  and scale factor, and ? (EM) is the product of
  the effort multipliers for the COCOMO II cost
  drivers
• PL Effort (the first product)
• PMR (1) PMNR (1) PFRAC RCWR(AFRACRFRAC)
• Note RCWR not applied to non-reused portion,
  where many other models overestimate RCWR

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Basic COPLIMO Annualized Life Cycle Cost Model

• Annual Change Traffic (ACT)
• Relative fraction of a products software that is
  modified per year
• Simplifying assumption Constant-ACT
• Life cycle effort without reuse
• N complete products undergo maintenance
• Life cycle effort with reuse
• PFRAC maintenance for N instances
• RFRAC maintenance for 1 instance
• AFRAC maintenance for 1 instance and N-1 variants

78
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Discussions

• Software product line payoffs are significant
  esp. across life cycle
• This does not mean any attempt at product line
  reuse will generate large savings
• Challenges
• Technical
• Domain engineering and product line architecting
• Management and Culture
• People unwilling to corporate
• Not invented here attitudes
• Success factor empowered product line manager

81
Conclusions

• Software product line payoffs are significant
  esp. across life cycle
• COPLIMO avoids investment overestimation
  savings underestimation
• COPLIMO helps to determine whether and when it
  pays to launch a product line
• COPLIMO enables assessment of situation-dependenci
  es, hence lead to better product line decisions.
• Future work
• Support for more sensitivity analysis
• Model refinement and calibration
• Integration with other COCOMO II family models,
  such as COCOTS

82
COPLIMO Backup Charts
83
COPLIMO RCR

• Reused, or Black Box (unmodified code) RCR model
• Assessment and
• Assimilation (AA) factor
• Adapted, or White Box (modified code) RCR model
• AA
• Non-Linear Model

84
Guidelines for Quantifying Adapted Software
85
Basic COPLIMO Development Cost Model (3)

• Determining RCR
• Equiv. size of product- specific portion
• Equiv. size of reused portion
• Equiv. size of adapted portion
• Total EKSLOC
• Effort
• ROI (PL Effort Savings for K products - PL
  Reuse Investment) / PL Reuse Investment

PMR (N) N ? A? (EKSIZE)B ? ? (EM)
86
Basic COPLIMO Annualized Life Cycle Cost Model
(1)

• Annual Change Traffic (ACT)
• Relative fraction of a products software that is
  modified per year
• Life cycle effort without reuse
• Annual maintained software
• L times maintenance effort
• Life cycle effort with reuse
• Three categories of annual maintenance and AMSIZE

87
Agenda

• COCOMO II refresher
• Modeling methodology and model status
• Suite overview
• Emerging extensions
• Model unification
• Addendum selected model details
• COCOTS
• COPLIMO
• COSYSMO
• COSOSIMO
• References and further information

88
COSYSMO Introduction

• Covers full system engineering lifecycle (maps to
  ISO/IEC 15288)
• Life cycle stages being used in COSYSMO Project
• Estimates standard Systems Engineering WBS tasks
  (based on EIA/ANSI 632)
• Developed with USC-CSE Corporate Affiliate
  sponsorship and INCOSE participation

Conceptualize
Operate, Maintain, or Enhance
Replace or Dismantle
Transition to Operation
Oper Test Eval
Develop
89
How is Systems Engineering Defined?

• EIA/ANSI 632
• Processes for Engineering a System
• Acquisition and Supply
• Supply Process
• Acquisition Process
• Technical Management
• Planning Process
• Assessment Process
• Control Process
• System Design
• Requirements Definition Process
• Solution Definition Process

• Product Realization
• Implementation Process
• Transition to Use Process
• Technical Evaluation
• Systems Analysis Process
• Requirements Validation Process
• System Verification Process
• End Products Validation Process

90
COSYSMO Operational Concept
Requirements Interfaces Scenarios
Algorithms 3 adjustment factors
Size Drivers
COSYSMO
Effort
Effort Multipliers

• Application factors
• 8 factors
• Team factors
• 6 factors

Calibration
91
Model Form
Where PMNS effort in Person Months (Nominal
Schedule) A calibration constant derived from
historical project data k REQ, IF, ALG,
SCN wx weight for easy, nominal, or
difficult size driver quantity of k
size driver E represents diseconomy of scale
(currently equals 1) EM effort multiplier for
the jth cost driver. The geometric product
results in an overall effort adjustment factor to
the nominal effort.
92
14 Cost Drivers (Effort Multipliers)
Application Factors (8)

• Requirements understanding
• Architecture understanding
• Level of service requirements
• Migration complexity
• Technology Maturity
• Documentation Match to Life Cycle Needs
• and Diversity of Installations/Platforms
• of Recursive Levels in the Design

93
14 Cost Drivers (continued)
Team Factors (6)

• Stakeholder team cohesion
• Personnel/team capability
• Personnel experience/continuity
• Process maturity
• Multisite coordination
• Tool support

94
Agenda

• COCOMO II refresher
• Modeling methodology and model status
• Suite overview
• Emerging extensions
• Model unification
• Addendum selected model details
• COCOTS
• COPLIMO
• COSYSMO
• COSOSIMO
• References and further information

95
How Much Effort to Integrate a System of Systems?
System of Systems ? person-years (PY)
Sensing 500 PY
Vehicles 500 PY
Common 400 PY
Infrastructure 600 PY
Command Control 1000 PY

• Systems developed by system contractors
• Total effort 3000 person-years
• System of systems integration functions
• SoS abstraction, architecting, source selection,
  systems acquisition, integration, test, change
  management effort
• How much to budget for integration?
• What factors make budget higher or lower?
• How to develop and validate an estimation model?

96
Constructive System-of-System Integration Cost
Model (COSOSIMO)

• Parametric model to estimate the effort
  associated with the definition and integration of
  software-intensive system of systems components
• Includes at least one size driver and 6
  exponential scale factors related to effort
• Targets input parameters that can be determined
  in early phases
• Goal is to have zero overlap with COCOMO II and
  COSYSMO

97
COSOSIMO Operational Concept
Size Drivers

• Interface-related eKSLOC
• Number of logical interfaces at SoS level
• Number of components
• Number of operational scenarios

COSOSIMO
SoS Definition and Integration Effort
Exponential Scale Factors

• Integration simplicity
• Integration risk resolution
• Integration stability
• Component readiness
• Integration capability
• Integration processes

Calibration

• Each size driver weighted by
• Complexity
• Volatility
• Degree of COTS/reuse

98
COSOSIMO Model Equations

• Two level model that
• First determines integration effort
• for first level subsystems.
• Then, using subsystem integration
• effort and SoS characteristics,
• determines SoS integration effort

SOS
Level 0
Level 1
Sm
S2
S1

S11
S12
S1n
S21
S22
S2n
Sm1
Sm2
Smn



99
COSOSIMO Model Parameters

• IPM Integration effort in Person Months
• Si The ith subsystem within the SoS
• A Constant derived from historical project data
• Size Determined by computing the weighted
  average of the size driver(s)
• ni Number of Subsystem level 2 components
  comprising the ith subsystem
• m Number of Subsystem level 1 components
  comprising the SoS
• Bi Effort exponent for the ith subsystem based
  on the subsystems 6 exponential scale factors.
  The sum of the scale factors results in an
  overall exponential effort adjustment factor to
  the nominal effort.
• B0 Effort exponent for the SoS based on the SOS
  6 exponential scale factors. The sum of the scale
  factors results in an overall exponential effort
  adjustment factor to the nominal effort.

100
Agenda

• COCOMO II refresher
• Modeling methodology and model status
• Suite overview
• Emerging extensions
• Model unification
• Addendum selected model details
• COCOTS
• COPLIMO
• COSYSMO
• COSOSIMO
• References and further information

101
References

• Abts, C., Extending The COCOMO II Software Cost
  Model To Estimate Effort And Schedule For
  Software Systems Using Commercial-off-the-shelf
  (COTS) Software Components The COCOTS Model, USC
  PhD dissertation, May 2004
• B. Boehm, C. Abts, W. Brown, S. Chulani, B.
  Clark, E. Horowitz, R. Madachy, D. Reifer, B.
  Steece, Software Cost Estimation with COCOMO II,
  Prentice-Hall, 2000
• Chulani, "Bayesian Analysis of Software Cost and
  Quality Models, USC PhD dissertation, April
  1999.
• Clark, B., Clark, B., Early COCOTS, September
  2004.
• Lane, J. Constructive Cost Model for
  System-of-System Integration, 3rd ACM-IEEE
  International Symposium on Empirical Software
  Engineering, Redondo Beach, CA, August, 2004
• Valerdi, R., Boehm, B., Reifer, D., COSYSMO A
  Constructive Systems Engineering Cost Model
  Coming Age, Proceedings, 13th Annual INCOSE
  Symposium, Crystal City, VA. July 2003.
• Boehm B, Valerdi R Lane J, Brown W, COCOMO Suite
  Methodology and Evolution, Crosstalk, 2005
• Yang Y, Boehm B, Madachy R, COPLIMO A
  Product-Line Investment Analysis Model,
  Proceedings of the Eighteenth International Forum
  on COCOMO and Software Cost Modeling, USC, Los
  Angeles, CA, October 2003

102
Further Information

• Main COCOMO website at USC http//sunset.usc.edu/
  research/COCOMOII
• COCOMO information at USC [phone]
• COCOMO email cocomo-info_at_sunset.usc.edu