cocomo ii overview

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University of Southern CaliforniaCenter for Software EngineeringC S E

USC

Sep. 2008

COCOMO II Overview

A Winsor Brown (especially from page 50 on)(Based on original by Ray Madachy [email protected])

CSCI 510 September 22, 2008

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Sep. 2008

Agenda• COCOMO introduction• Basic estimation formulas• Cost factors• Reuse model• Sizing• USC COCOMO tool demo• Data collection

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Sep. 2008

Software Cost Estimation Methods

• Cost estimation: prediction of both the person-effort and elapsed time of a project

• Methods:– Algorithmic– Expert judgement– Estimation by analogy– Parkinsonian

• Best approach is a combination of methods– compare and iterate estimates, reconcile differences

• COCOMO is the most widely used, thoroughly documented and calibrated cost model

– Price-to-win– Top-down– Bottom-up

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Sep. 2008

COCOMO Background• COCOMO - the “COnstructive COst MOdel”

– COCOMO II is the update to COCOMO 1981– ongoing research with annual calibrations made available

• Originally developed by Dr. Barry Boehm and published in 1981 book Software Engineering Economics

• COCOMO II described in new book Software Cost Estimation with COCOMO II

• COCOMO can be used as a framework for cost estimation and related activities

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Sep. 2008

• Effect of uncertaintiesover time

Software Estimation Accuracy

Feasibility Plans/Rqts. Design Develop and Test

Phases and Milestones

Relative Size

Range

OperationalConcept

Life Cycle Objectives

Life Cycle Architecture

Initial Operating Capability

x

0.5x

0.25x

4x

2x

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Sep. 2008

COCOMO Black Box Model

COCOMO II

product size estimate

product, process, platform, and personnel attributes

reuse, maintenance, and increment parameters

organizational project data

development, maintenance cost and schedule estimates

cost, schedule distribution by phase, activity, increment

recalibration to organizational data

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Sep. 2008

Major COCOMO II Features• Multi-model coverage of different development

sectors• Variable-granularity cost model inputs• Flexibility in size inputs

– SLOCS– function points– application points– other (use cases ...)

• Range vs. point estimates per funnel chart

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Sep. 2008

COCOMO Uses for Software Decision Making

• Making investment decisions and business-case analyses • Setting project budgets and schedules • Performing tradeoff analyses• Cost risk management• Development vs. reuse decisions• Legacy software phaseout decisions• Software reuse and product line decisions• Process improvement decisions

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Sep. 2008

Productivity Ranges• COCOMO provides natural framework to identify high

leverage productivity improvement factors and estimate their payoffs.

4.14

3.37

2.21

1.85

1.72

1.67

1.64

1.60

1.57

1.49

1.48

1.29

1.28

1.27

1 1.5 2 2.5 3 3.5 4 4.5

Personnel Capability

Personnel Experience

Product Complexity

Required Reliability

Use of Software Tools

Execution Time Constraint

Required Reuse

Multisite Development

Main Storage Constraint

Platform Volatility

Personnel Continuity

Required Development Schedule

Database Size

Documentation

Cos

t Fac

tor

Productivity Range

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Sep. 2008

COCOMO Submodels• Applications Composition involves rapid development or prototyping efforts

to resolve potential high-risk issues such as user interfaces, software/system interaction, performance, or technology maturity. It’s sized with application points (weighted screen elements, reports and 3GL modules).

• The Early Design model involves exploration of alternative software/system architectures and concepts of operation using function points and a course-grained set of 7 cost drivers.

• The Post-Architecture model involves the actual development and maintenance of a software product using source instructions and / or function points for sizing, with modifiers for reuse and software breakage; a set of 17 multiplicative cost drivers; and a set of 5 factors determining the project's scaling exponent.

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Sep. 2008

COCOMO Effort Formulation # of cost drivers

Effort (person-months) = A (Size)B EMi i=1

• Where:– A is a constant derived from historical project data

(currently A = 2.94 in COCOMOII.2000)– Size is in KSLOC (thousand source lines of code),

or converted from function points or object points– B is an exponent for the diseconomy of scale dependent on five additive scale

drivers according to b = .91 + .01*SFi,where SFi is a weighting factor for ith scale driver

– EMi is the effort multiplier for the ith cost driver. The geometric product results in an overall effort adjustment factor to the nominal effort.

• Automated translation effects are not included

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Sep. 2008

Diseconomy of Scale• Nonlinear relationship when exponent > 1

0

2000

4000

6000

8000

10000

12000

14000

16000

0 500 1000

KSLOC

Per

son

Mon

ths B=1.226

B=1.00

B=0.91

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Sep. 2008

• Where: – Schedule is the calendar time in months from the requirements baseline to

acceptance– C is a constant derived from historical project data

(currently C = 3.67 in COCOMOII.2000)– Effort is the estimated person-months excluding the SCED effort multiplier– B is the sum of project scale factors – SCED% is the compression / expansion percentage in the SCED cost driver

• This is the COCOMOII.2000 calibration • Formula can vary to reflect process models for reusable and

COTS software, and the effects of application composition capabilities.

COCOMO Schedule FormulationSchedule (months) = C (Effort)(.33+0.2(B-1.01)) x SCED%/100

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Sep. 2008

Coverage of Different Processes• COCOMO II provides a framework for tailoring the model

to any desired process• Original COCOMO was predicated on the waterfall process

– single-pass, sequential progression of requirements, design, code, test

• Modern processes are concurrent, iterative, incremental, and cyclic

– e.g. Rational Unified Process (RUP), the USC Model-Based Architecting and Software Engineering (MBASE) process

• Effort and schedule are distributed among different phases and activities per work breakdown structure of chosen process

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Sep. 2008

Common Process Anchor Points• Anchor points are common process milestones around

which cost and schedule budgets are organized• COCOMO II submodels address different

development stages anchored by these generic milestones:

– Life Cycle Objectives (LCO)• inception: establishing a sound business case

– Life Cycle Architecture (LCA)• elaboration: commit to a single architecture and elaborate it to cover all major risk

sources– Initial Operational Capability (IOC)

• construction: commit to transition and support operations

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Sep. 2008

MBASE Phase Distributions

125118Project Total

100100COCOMO Total

12.512Transition

62.576Construction

37.524Elaboration

12.56Inception

Schedule %Effort %Phase

• see COCOMO II book for complete phase/activity distributions

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Sep. 2008

Waterfall Phase Distributions

125119Project Total

100100COCOMO Total

12.512

Integration & Test

4858Programming

2617Product Design

207Plans & rqts

Schedule %Effort %Phase

Transition

25 26

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Sep. 2008

COCOMO II Output Ranges• COCOMO II provides one standard deviation

optimistic and pessimistic estimates.• Reflect sources of input uncertainties per

funnel chart.• Apply to effort or schedule for all of the stage

models.• Represent 80% confidence limits: below

optimistic or pessimistic estimates 10% of the time. Stage Optimistic

EstimatePessimistic

Estimate

1 0.50 E 2.0 E

2 0.67 E 1.5 E

3 0.80 E 1.25 E

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Sep. 2008

COCOMO Tailoring & Enhancements• Calibrate effort equations to organizational experience

– USC COCOMO has a calibration capability• Consolidate or eliminate redundant cost driver

attributes• Add cost drivers applicable to your organization• Account for systems engineering, hardware and

software integration

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Sep. 2008

Cost Factors• Significant factors of development cost:

– scale drivers are sources of exponential effort variation– cost drivers are sources of linear effort variation

• product, platform, personnel and project attributes• effort multipliers associated with cost driver ratings

– Defined to be as objective as possible

• Each factor is rated between very low and very high per rating guidelines– relevant effort multipliers adjust the cost up or down

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Sep. 2008

Scale Drivers• Precedentedness (PREC)

– Degree to which system is new and past experience applies• Development Flexibility (FLEX)

– Need to conform with specified requirements• Architecture/Risk Resolution (RESL)

– Degree of design thoroughness and risk elimination • Team Cohesion (TEAM)

– Need to synchronize stakeholders and minimize conflict• Process Maturity (PMAT)

– SEI CMM process maturity rating

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Sep. 2008

Cost Drivers• Product Factors

– Reliability (RELY)– Data (DATA)– Complexity (CPLX)– Reusability (RUSE)– Documentation (DOCU)

• Platform Factors– Time constraint (TIME)– Storage constraint (STOR)– Platform volatility (PVOL)

• Personnel factors– Analyst capability (ACAP)– Program capability (PCAP)– Applications experience (APEX)– Platform experience (PLEX)– Language and tool experience

(LTEX)– Personnel continuity (PCON)

• Project Factors– Software tools (TOOL)– Multisite development (SITE)– Required schedule (SCED)

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Sep. 2008

Example Cost Driver - Required Software Reliability (RELY)

• Measures the extent to which the software must perform its intended function over a period of time.

• Ask: what is the effect of a software failure? Very Low Low Nominal High Very High Extra High

RELY slightinconvenience

low, easilyrecoverablelosses

moderate,easilyrecoverablelosses

high financialloss

risk to humanlife

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Sep. 2008

Example Effort Multiplier Values for RELY

Very Low Low High Very High

Slight Inconvenience

Low, Easily Recoverable

Losses

High Financial Loss

Risk to Human Life

1.15

0.75

0.88

1.39

1.0Moderate, Easily

Recoverable Losses

Nominal

E.g. a highly reliable system costs 39% more than a nominally reliable system 1.39/1.0=1.39)or a highly reliable system costs 85% more than a very low reliability system (1.39/.75=1.85)

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Sep. 2008

Scale Factors

• Sum scale factors Wi across all of the factors to determine a scale exponent, B, using B = .91 + .01 Wi

Scale Factors (Wi) Very Low Low Nominal High Very High Extra High

Precedentedness(PREC)

thoroughlyunprecedented

largelyunprecedented

somewhatunprecedented

generallyfamiliar

largelyfamiliar

throughlyfamiliar

DevelopmentFlexibility (FLEX)

rigorous occasionalrelaxation

somerelaxation

generalconformity

someconformity

generalgoals

Architecture/RiskResolution (RESL)*

little (20%) some (40%) often (60%) generally(75%)

mostly(90%)

full (100%)

Team Cohesion(TEAM)

very difficultinteractions

some difficultinteractions

basicallycooperativeinteractions

largelycooperative

highlycooperative

seamlessinteractions

Process Maturity(PMAT)

Weighted average of “Yes” answers to CMM Maturity Questionnaire

* % significant module interfaces specified, % significant risks eliminated

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Sep. 2008

Precedentedness (PREC) and Development Flexibility (FLEX)

• Elaboration of the PREC and FLEX rating scales:

Feature Very Low Nominal / High Extra High

PrecedentednessOrganizational understanding of productobjectives

General Considerable Thorough

Experience in working with related softwaresystems

Moderate Considerable Extensive

Concurrent development of associated newhardware and operational procedures

Extensive Moderate Some

Need for innovative data processingarchitectures, algorithms

Considerable Some Minimal

Development FlexibilityNeed for software conformance with pre-established requirements

Full Considerable Basic

Need for software conformance withexternal interface specifications

Full Considerable Basic

Premium on early completion High Medium Low

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Sep. 2008

Architecture / Risk Resolution (RESL)• Use a subjective weighted average of the

characteristics:Characteristic Very Low Low Nominal High Very High Extra High

Risk Management Plan identifies all criticalrisk items, establishes milestones forresolving them by PDR.

None Little Some Generally Mostly Fully

Schedule, budget, and internal milestonesthrough PDR compatible with RiskManagement Plan

None Little Some Generally Mostly Fully

Percent of development schedule devotedto establishing architecture, given generalproduct objectives

5 10 17 25 33 40

Percent of required top software architectsavailable to project

20 40 60 80 100 120

Tool support available for resolving riskitems, developing and verifyingarchitectural specs

None Little Some Good Strong Full

Level of uncertainty in Key architecturedrivers: mission, user interface, COTS,hardware, technology, performance.

Extreme Significant Considerable Some Little Very Little

Number and criticality of risk items > 10Critical

5-10Critical

2-4Critical

1Critical

> 5 Non-Critical

< 5 Non-Critical

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Sep. 2008

Team Cohesion (TEAM)• Use a subjective weighted average of the

characteristics to account for project turbulence and entropy due to difficulties in synchronizing the project's stakeholders.

• Stakeholders include users, customers, developers, maintainers, interfacers, and others

Characteristic Very Low Low Nominal High Very High Extra HighConsistency of stakeholderobjectives and cultures

Little Some Basic Considerable Strong Full

Ability, willingness of stakeholders toaccommodate other stakeholders'objectives

Little Some Basic Considerable Strong Full

Experience of stakeholders inoperating as a team

None Little Little Basic Considerable Extensive

Stakeholder teambuilding to achieveshared vision and commitments

None Little Little Basic Considerable Extensive

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Sep. 2008

Process Maturity (PMAT)• Two methods based on the Software Engineering

Institute's Capability Maturity Model (CMM)• Method 1:

Overall Maturity Level (CMM Level 1 through 5)

• Method 2: Key Process Areas(see next slide)

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Sep. 2008

Key Process Areas• Decide the percentage of compliance for each of the

KPAs as determined by a judgement-based averaging across the goals for all 18 Key Process Areas.

Key Process Areas Almost Always(>90%)

Frequently(60-90%)

About Half(40-60%)

Occasionally(10-40%)

Rarely If Ever(<10%)

Does NotApply

Don'tKnow

1 RequirementsManagement

2 Software ProjectPlanning

3 Software ProjectTracking and Oversight

4 Software SubcontractManagement

(See COCOMO II Model Definition Manual for remaining details)

PMAT = 5 1005181

18

KPAi

i

%

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Sep. 2008

Cost Drivers

• Product Factors • Platform Factors • Personnel Factors • Project Factors

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Product Factors

• Required Software Reliability (RELY) – Measures the extent to which the software must

perform its intended function over a period of time. Ask: what is the effect of a software failure

Very Low Low Nominal High Very High Extra HighRELY slight

inconveniencelow, easilyrecoverable losses

moderate, easilyrecoverable losses

high financial loss risk to human life

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Sep. 2008

Product Factors cont’d• Data Base Size (DATA)

– Captures the effect large data requirements have on development to generate test data that will be used to exercise the program.

– Calculate the data/program size ratio (D/P):

)()(

SLOCSizeProgramByteszeDataBaseSi

PD

Very Low Low Nominal High Very High Extra HighDATA DB bytes/ Pgm SLOC < 10 10 D/P < 100 100 D/P < 1000 D/P > 1000

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Sep. 2008

Product Factors cont’d• Product Complexity (CPLX)

– Complexity is divided into five areas:• control operations, • computational operations, • device-dependent operations, • data management operations, and • user interface management operations.

– Select the area or combination of areas that characterize the product or a sub-system of the product.

– See the module complexity table, next several slides

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Sep. 2008

Product Factors cont’d• Module Complexity Ratings vs. Type of

Module – Use a subjective weighted average of the attributes,

weighted by their relative product importance.Very Low Low Nominal High Very High Extra High

ControlOperations

Straightline codewith a few non-nested structuredprogrammingoperators: DOs,CASEs,IFTHENELSEs.Simple modulecomposition viaprocedure calls orsimple scripts.

Straightforwardnesting ofstructuredprogrammingoperators.Mostly simplepredicates.

Mostly simplenesting. Someintermodulecontrol. Decisiontables. Simplecallbacks ormessagepassing,includingmiddleware-supporteddistributedprocessing.

Highly nestedstructuredprogrammingoperators with manycompoundpredicates. Queueand stack control.Homogeneous, dist.processing. Singleprocessor soft real-time ctl.

Reentrant andrecursive coding.Fixed-priorityinterrupt handling.Task synchronization,complex callbacks,heterogeneous dist.processing. Single-processor hard real-time ctl.

Multiple resourcescheduling withdynamically changingpriorities. Microcode-level control.Distributed hard real-time control.

ComputationalOperations

Evaluation ofsimpleexpressions: e.g.,A=B+C*(D-E)

Evaluation ofmoderate-levelexpressions:e.g.,D=SQRT(B**2-4.*A*C)

Use of standardmath andstatisticalroutines. Basicmatrix/vectoroperations.

Basic numericalanalysis: multivariateinterpolation, ordinarydifferential eqns.Basic truncation,roundoff concerns.

Difficult but structurednumerical analysis:near-singular matrixequations, partialdifferential eqns.Simpleparallelization.

Difficult andunstructurednumerical analysis:highly accurateanalysis of noisy,stochastic data.Complexparallelization.

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Sep. 2008

Product Factors cont’d• Module Complexity Ratings vs. Type of

Module – Use a subjective weighted average of the attributes,

weighted by their relative product importance.Very Low Low Nominal High Very High Extra High

Device-dependentOperations

Simple read,writestatementswith simpleformats.

No cognizanceneeded of particularprocessor or I/Odevicecharacteristics. I/Odone at GET/PUTlevel.

I/O processingincludes deviceselection, statuschecking and errorprocessing.

Operations at physicalI/O level (physicalstorage addresstranslations; seeks,reads, etc.).Optimized I/O overlap.

Routines for interruptdiagnosis, servicing,masking.Communication linehandling.Performance-intensiveembedded systems.

Device timing-dependent coding,micro-programmedoperations.Performance-critical embeddedsystems.

DataManagementOperations

Simple arraysin mainmemory.Simple COTS-DB queries,updates.

Single file subsettingwith no data structurechanges, no edits, nointermediate files.Moderately complexCOTS-DB queries,updates.

Multi-file input andsingle file output.Simple structuralchanges, simpleedits. ComplexCOTS-DB queries,updates.

Simple triggersactivated by datastream contents.Complex datarestructuring.

Distributed databasecoordination. Complextriggers. Searchoptimization.

Highly coupled,dynamic relationaland objectstructures. Naturallanguage datamanagement.

UserInterfaceManagement

Simple inputforms, reportgenerators.

Use of simple graphicuser interface (GUI)builders.

Simple use ofwidget set.

Widget setdevelopment andextension. Simplevoice I/O, multimedia.

Moderately complex2D/3D, dynamicgraphics, multimedia.

Complexmultimedia, virtualreality.

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Sep. 2008

Product Factors cont’d• Required Reusability (RUSE)

– Accounts for the additional effort needed to construct components intended for reuse.

• Documentation match to life-cycle needs (DOCU)– What is the suitability of the project's documentation

to its life-cycle needs.

Very Low Low Nominal High Very High Extra HighRUSE none across project across program across product line across multiple product lines

Very Low Low Nominal High Very High Extra HighDOCU Many life-cycle

needs uncoveredSome life-cycleneeds uncovered

Right-sized to life-cycle needs

Excessive for life-cycle needs

Very excessive forlife-cycle needs

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Sep. 2008

Platform Factors• Platform

– Refers to the target-machine complex of hardware and infrastructure software (previously called the virtual machine).

• Execution Time Constraint (TIME)– Measures the constraint imposed upon a system in

terms of the percentage of available execution time expected to be used by the system.

Very Low Low Nominal High Very High Extra High

TIME 50% use of available execution time 70% 85% 95%

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Sep. 2008

Platform Factors cont’d

• Main Storage Constraint (STOR)– Measures the degree of main storage constraint

imposed on a software system or subsystem.

• Platform Volatility (PVOL)– Assesses the volatility of the platform (the complex of

hardware and software the software product calls on to perform its tasks).


STOR 50% use of available storage 70% 85% 95%


PVOL major change every 12 mo.;minor change every 1 mo.

major: 6 mo.;minor: 2 wk.


major: 2 wk.;minor: 2 days

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Sep. 2008

Personnel Factors• Analyst Capability (ACAP)

– Analysts work on requirements, high level design and detailed design. Consider analysis and design ability, efficiency and thoroughness, and the ability to communicate and cooperate.

• Programmer Capability (PCAP)– Evaluate the capability of the programmers as a team rather than as

individuals. Consider ability, efficiency and thoroughness, and the ability to communicate and cooperate.

Very Low Low Nominal High Very High Extra HighACAP 15th percentile 35th percentile 55th percentile 75th percentile 90th percentile

Very Low Low Nominal High Very High Extra HighPCAP 15th percentile 35th percentile 55th percentile 75th percentile 90th percentile

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Sep. 2008

Personnel Factors cont’d• Applications Experience (AEXP)

– Assess the project team's equivalent level of experience with this type of application.

• Platform Experience (PEXP)– Assess the project team's equivalent level of experience with this

platform including the OS, graphical user interface, database, networking, and distributed middleware.


AEXP 2 months 6 months 1 year 3 years 6 years


PEXP 2 months 6 months 1 year 3 years 6 year

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Sep. 2008

Personnel Factors cont’d• Language and Tool Experience (LTEX)

– Measures the level of programming language and software tool experience of the project team.

• Personnel Continuity (PCON)– The scale for PCON is in terms of the project's annual personnel

turnover.


LTEX 2 months 6 months 1 year 3 years 6 years

Very Low Low Nominal High Very High Extra HighPCON 48% / year 24% / year 12% / year 6% / year 3% / year

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Sep. 2008

Project Factors

• Use of Software Tools (TOOL)– Assess the usage of software tools used to develop the product in

terms of their capabilities and maturity. Very Low Low Nominal High Very High Extra High

edit, code,debug

simple,frontend,backend CASE,little integration

basic lifecycletools, moderatelyintegrated

strong, maturelifecycle tools,moderatelyintegrated

strong, mature,proactive lifecycletools, well integratedwith processes,methods, reuse

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Sep. 2008

Project Factors cont’d• Multisite Development (SITE)

– Assess and average two factors: site collocation and communication support.

• Required Development Schedule (SCED)– Measure the imposed schedule constraint in terms of the percentage of

schedule stretch-out or acceleration with respect to a nominal schedule for the project.


SITE:Collocation

International Multi-city andMulti-company

Multi-city orMulti-company

Same city ormetro. area

Same building orcomplex

Fully collocated

SITE:Communications

Some phone,mail

Individual phone,FAX

Narrowbandemail

Widebandelectroniccommunication

Wideband elect.comm, occasionalvideo conf.

Interactivemultimedia


SCED 75% of nominal 85% 100% 130% 160%

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Sep. 2008

Cost Factor Rating

• Whenever an assessment of a cost driver is between the rating levels: – always round to the Nominal rating – e.g. if a cost driver rating is between High

and Very High, then select High.

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Sep. 2008

Cost Driver Rating Level Summary


RELY slightinconvenience

low, easilyrecoverablelosses

moderate, easilyrecoverable losses

high financial loss risk to human life

DATA DB bytes/Pgm SLOC < 10

10 D/P < 100 100 D/P 1000 D/P > 1000

CPLX (see Complexity Table)

RUSE none across project across program across product line across multipleproduct lines

DOCU Many life-cycleneeds uncovered

Some life-cycleneeds uncovered

Right-sized to life-cycle needs

Excessive forlife-cycle needs

Very excessive forlife-cycle needs

TIME 50% use ofavailable executiontime

70% 85% 95%

STOR 50% use ofavailable storage

70% 85% 95%

PVOL major changeevery 12 mo.;minor changeevery 1 mo.



major: 2 wk.;minor: 2 days

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Cost Driver Rating Level Summary cont’d


ACAP 15th percentile 35th percentile 55th percentile 75th percentile 90th percentile

PCAP 15th percentile 35th percentile 55th percentile 75th percentile 90th percentile

PCON 48% / year 24% / year 12% / year 6% / year 3% / year

AEXP 2 months 6 months 1 year 3 years 6 years

PEXP 2 months 6 months 1 year 3 years 6 year

LTEX 2 months 6 months 1 year 3 years 6 year

TOOL edit, code,debug

simple, frontend,backend CASE,little integration

basic lifecycletools, moderatelyintegrated

strong, maturelifecycle tools,moderatelyintegrated

strong, mature, proactivelifecycle tools, wellintegrated with processes,methods, reuse

SITE:Collocation

International Multi-city andMulti-company

Multi-city orMulti-company

Same city ormetro. area

Same building or complex Fullycollocated

SITE:Commu-nications

Some phone,mail

Individual phone,FAX

Narrowband email Widebandelectroniccommunication.

Wideband elect. comm,occasional video conf.

Interactivemultimedia

SCED 75% of nominal 85% 100% 130% 160%

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Reused and Modified Software

• Effort for adapted software (reused or modified) is not the same as for new software.

• Approach: convert adapted software into equivalent size of new software.

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Nonlinear Reuse Effects• The reuse cost function does not go through the origin due to a cost of about

5% for assessing, selecting, and assimilating the reusable component. • Small modifications generate disproportionately large costs primarily due the

cost of understanding the software to be modified, and the relative cost of interface checking.

Relativecost

Amount Modified

1.0

0.75

0.5

0.25

0.25 0.5 0.75 1.0

0.55

0.70

1.0

0.046

Usual LinearAssumption

Data on 2954NASA modules

[Selby,1988]

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Sep. 2008

COCOMO Reuse Model• A nonlinear estimation model to convert

adapted (reused or modified) software into equivalent size of new software:

A A F D M C M I M 0 4 0 3 0 3. ( ) . ( ) . ( )

E S L O CA S L O C A A A A F S U U N F M

A A F

[ ( . ( ) ( ) ) ]

, .1 0 0 2

1 0 00 5

E S L O CA S L O C A A A A F S U U N F M

A A F

[ ( ) ( ) ]

, .1 0 0

0 5

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COCOMO Reuse Model cont’d• ASLOC - Adapted Source Lines of Code• ESLOC - Equivalent Source Lines of Code• AAF - Adaptation Adjustment Factor• DM - Percent Design Modified. The percentage of the adapted software's design

which is modified in order to adapt it to the new objectives and environment. • CM - Percent Code Modified. The percentage of the adapted software's code

which is modified in order to adapt it to the new objectives and environment. • IM - Percent of Integration Required for Modified Software. The percentage of

effort required to integrate the adapted software into an overall product and to test the resulting product as compared to the normal amount of integration and test effort for software of comparable size.

• AA - Assessment and Assimilation effort needed to determine whether a fully-reused software module is appropriate to the application, and to integrate its description into the overall product description. See table.

• SU - Software Understanding. Effort increment as a percentage. Only used when code is modified (zero when DM=0 and CM=0). See table.

• UNFM - Unfamiliarity. The programmer's relative unfamiliarity with the software which is applied multiplicatively to the software understanding effort increment (0-1).

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Sep. 2008

Assessment and Assimilation Increment (AA)

AA Increment Level of AA Effort0 None

2 Basic module search and documentation

4 Some module Test and Evaluation (T&E), documentation

6 Considerable module T&E, documentation

8 Extensive module T&E, documentation

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Sep. 2008

Software Understanding Increment (SU)

• Take the subjective average of the three categories. • Do not use SU if the component is being used

unmodified (DM=0 and CM =0).Very Low Low Nominal High Very High

Structure Very lowcohesion, highcoupling,spaghetti code.

Moderately lowcohesion, highcoupling.

Reasonably well-structured; someweak areas.

High cohesion, lowcoupling.

Strong modularity,information hiding indata / controlstructures.

ApplicationClarity

No matchbetween programand applicationworld views.

Some correlationbetween programand application.

Moderatecorrelationbetween programand application.

Good correlationbetween programand application.

Clear match betweenprogram andapplication world-views.

Self-Descriptiveness

Obscure code;documentationmissing, obscureor obsolete

Some codecommentary andheaders; someusefuldocumentation.

Moderate level ofcodecommentary,headers,documentations.

Good codecommentary andheaders; usefuldocumentation;some weak areas.

Self-descriptive code;documentation up-to-date, well-organized,with design rationale.

SU Incrementto ESLOC

50 40 30 20 10

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Sep. 2008

Programmer Unfamiliarity (UNFM)

UNFM Increment Level of Unfamiliarity0.0 Completely familiar

0.2 Mostly familiar

0.4 Somewhat familiar

0.6 Considerably familiar

0.8 Mostly unfamiliar

1.0 Completely unfamiliar

• Only applies to modified software

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Sep. 2008

Commercial Off-the-Shelf (COTS) Software

• Current best approach is to treat as reused piece• A COTS cost model is under development• Calculate effective size from external interface files

and breakage• Have identified candidate COTS cost drivers

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Sep. 2008

Reuse Parameter Guidelines

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Sep. 2008


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Sep. 2008

Lines of Code• Source Lines of Code (SLOCs) = logical source

statements• Logical source statements = data declarations +

executable statements• Executable statements cause runtime actions• Declaration statements are nonexecutable

statements that affect an assembler's or compiler's interpretation of other program elements

• Codecount tool available on USC web site

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Sep. 2008

Lines of Code Counting Rules• Standard definition for

counting lines– Based on SEI definition

checklist from CMU/SEI-92-TR-20

– Modified for COCOMO II

• When a line or statement contains more than one type, classify it as the type with the highest precedence. Order of precedence is in ascending order

Statement type Includes Excludes

1. Executable

2. Non-executable:

3. Declarations

4. Compiler directives

5. Comments:

6. On their own lines

7. On lines with source code

8. Banners and non-blank spacers

9. Blank (empty) comments

10. Blank lines

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Sep. 2008

Lines of Code Counting Rules cont’d• (See COCOMO II

book for remaining details)

How produced Includes Excludes1. Programmed

2. Generated with source code generators

3. Converted with automated translators

4. Copied or reused without change

5. Modified

6. Removed

Origin Includes Excludes

1. New work: no prior existence

2. Prior work: taken or adapted from:

3. A previous version, build, or release

4. Commercial, off-the-shelf software (COTS), other than libraries

5. Government furnished software (GFS), other than reuse libraries

6. Another product

7. A vendor-supplied language support library (unmodified)

8. A vendor-supplied operating system or utility (unmodified)

9. A local or modified language support library or operating system

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Sep. 2008

Counting with Function Points• Used in both the Early Design and the Post-

Architecture models.• Based on the amount of functionality in a

software product and project factors using information available early in the project life cycle.

• Quantify the information processing functionality with the following user function types:

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Sep. 2008

Counting with Function Points cont’d– External Input (Inputs)

• Count each unique user data or user control input type that both

– Enters the external boundary of the software system being measured

– Adds or changes data in a logical internal file.

– External Output (Outputs)• Count each unique user data or control output type that

leaves the external boundary of the software system being measured.

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Sep. 2008

Counting with Function Points cont’d– Internal Logical File (Files)

• Count each major logical group of user data or control information in the software system as a logical internal file type. Include each logical file (e.g., each logical group of data) that is generated, used, or maintained by the software system.

– External Interface Files (Interfaces)• Files passed or shared between software systems should

be counted as external interface file types within each system.

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Sep. 2008

Counting with Function Points cont’d– External Inquiry (Queries)

• Count each unique input-output combination, where an input causes and generates an immediate output, as an external inquiry type.

• Each instance of the user function types is then classified by complexity level. The complexity levels determine a set of weights, which are applied to their corresponding function counts to determine the Unadjusted Function Points quantity.

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Sep. 2008

Counting with Function Points cont’d

• The usual Function Point procedure involves assessing the degree of influence of fourteen application characteristics on the software project.

• The contributions of these characteristics are inconsistent with COCOMO experience, so COCOMO II uses Unadjusted Function Points for sizing.

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Sep. 2008

Unadjusted Function Points Counting• Step 1 - Determine function counts by type.

– The unadjusted function counts should be counted by a lead technical person based on information in the software requirements and design documents.

– The number of each of the five user function types should be counted

• Internal Logical File (ILF)– Note: The word file refers to a logically related group of data and not the physical

implementation of those groups of data.

• External Interface File (EIF)• External Input (EI)• External Output (EO)• External Inquiry (EQ))

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Sep. 2008

Unadjusted Function Points Counting Procedure cont’d

• Step 2 - Determine complexity-level function counts. – Classify each function count into Low, Average and High complexity

levels depending on the number of data element types contained and the number of file types referenced. Use the following scheme:

For ILF and EIF For EO and EQ For EI

RecordElements

Data Elements FileTypes

Data Elements FileTypes

Data Elements

1 - 19 20 - 50 51+ 1 - 5 6 - 19 20+ 1 - 4 5 - 15 16+

1 Low Low Avg 0 or 1 Low Low Avg 0 or 1 Low Low Avg

2 - 5 Low Avg High 2 - 3 Low Avg High 2 - 3 Low Avg High

6+ Avg High High 4+ Avg High High 3+ Avg High High

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Sep. 2008

Unadjusted Function Points Counting Procedure cont’d

• Step 3 - Apply complexity weights. – Weight the number in each cell using the following scheme. The weights

reflect the relative value of the function to the user.

• Step 4 - Compute Unadjusted Function Points. – Add all the weighted functions counts to get one number, the Unadjusted

Function Points.

Function Type Complexity-WeightLow Average High

Internal Logical Files 7 10 15

External Interfaces Files 5 7 10

External Inputs 3 4 6

External Outputs 4 5 7

External Inquiries 3 4 6

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Sep. 2008


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Sep. 2008

USC COCOMO Demo

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Sep. 2008


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Sep. 2008

Cost Driver Ratings Profile

• Need to rate cost drivers in a consistent and objective fashion within an organization.

• Cost driver ratings profile:– Graphical depiction of historical ratings to be

used as a reference baseline to assist in rating new projects

– Used in conjunction with estimating tools to gauge new projects against past ones objectively

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Sep. 2008

Example Cost Driver Ratings Profile


RELY - required softwarereliability PROJ1

PROJ4

PROJ2PROJ3PROJ5PROJ6

effect: slightinconvenience

low, easilyrecoverable

losses

moderate,easily

recoverablelosses

high financialloss

risk to humanlife

DATA - data base size PROJ2PROJ3PROJ4

PROJ1PROJ5PROJ6

DBbytes/Prog.

SLOCS 10

10 D/P 100 100 D/P1000

D/P 1000

CPLX - product complexityPROJ3PROJ5PROJ1 PROJ4

PROJ2PROJ6

see attachedtable

____________ ____________ ____________ ____________ ____________

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Sep. 2008

Techniques to Generate Cost Driver Ratings Profile

• Single person – Time efficient, but may impose bias and person

may be unfamiliar with all projects• Group

– Converge ratings in a single meeting (dominant individual problem)

– Wideband Delphi technique (longer calendar time, but minimizes biases). See Software Engineering Economics, p. 335

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Sep. 2008

COCOMO Dataset Cost Metrics

• Size (SLOCS, function points)• Effort (Person-hours)• Schedule (Months)• Cost drivers• Scale drivers• Reuse parameters

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Sep. 2008

Recommended Project Cost Data

• For each project, report the following at the end of each month and for each release:– SIZE

• Provide total system size developed to date, and report new code size and reused / modified code size separately. This can be at a project level or lower level as the data supports and is reasonable. For languages not supported by tools such as assembly code, report the number of physical lines separately for each language.

– EFFORT• Provide cumulative staff-hours spent on software development per

project at the same granularity as the size components.

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Sep. 2008

Recommended Project Cost Data cont’d– COST DRIVERS AND SCALE DRIVERS

• For each reported size component, supply the cost driver ratings for product, platform, personnel and project attributes. For each reported size component, supply scale driver ratings.

– REUSE PARAMETERS• For each component of reused/modified code,

supply reuse parameters AA, SU, UNFM, DM, CM and IM.

• See Appendix C in COCOMO II book for additional data items

• Post-mortem reports are highly recommended

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Sep. 2008

Effort Staff-Hours Definition• Standard definition

– Based on SEI definition checklist in CMU/SEI-92-TR-21– Adapted for COCOMO II

• Does not include unpaid overtime, production and deployment activities, customer training activities

• Includes all personnel except level 3 or higher software management (i.e. directors or above who timeshare among projects)

• Person-month is defined as 152 hours

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Sep. 2008

Further Information• 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

• B. Boehm, Software Engineering Economics. Englewood Cliffs, NJ, Prentice-Hall, 1981

• Main COCOMO website at USC: http://sunset.usc.edu/research/COCOMOII

• COCOMO information at USC: (213) 740-6470• COCOMO email: [email protected]

cocomo ii overview

Documents

maintenance cost

usc cssemajor cocomo

software product

constructive cost modelcocomo

multiplicative cost

calibrated cost modelprice

software breakage

cocomo iicocomo