function point estimation

8/13/2019 Function Point Estimation

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www.davidconsultinggroup.com

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PROJECT SIZING AND ESTIMATING -EFFECTIVELY USING

FUNCTIONAL MEASUREMENT

Southern CaliforniaSoftware Process Improvement Network


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Copyright 2005. The David Consulting Group, Inc. 3

How do we indicate the value of sizing to our users/customers?

When we say that a project represents 50 Function Points from the

'users perspective, what does this really mean to the user? or to the

developer? How do we engage both parties in understanding size?

The User Perspective

Functional value delivered to the user/customer

Comparative analysis (size, cost per unit of work, defects)

Functional description and accountability (user)

Management of delivery expectations Credibility in project estimation


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Program Start-up

Planning

How will the information be used (objectives)?

Who is counting?

What is being counted?

History versus industry?

Path of least resistance

Easy to count (transaction based)

Agreeable user

Culture

Internal versus external

Pilot/rollout versus organization-wide

Scope (what doesnt get counted)

Continually evaluating the program


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1

DESIGN TEST IMPLEMENTDEFINE BUILD

SIZING

When to Size

1) Initial sizing during or after Requirements Phase

2) Subsequent sizing after System Design or when Change occurs3) Final sizing after Install

SIZINGSIZING

2 3


7/37Copyright 2005. The David Consulting Group, Inc. 7

Meaningful to developer and user/customer

Defined (industry recognized)

Consistent (methodology)

Easy to learn and apply

Accurate, statistically based

Available when needed (early)

Addresses project level information needs

Characteristics of an EffectiveSizing Metric



Function Point Analysis is a standardized

method for measuring the functionality

delivered to an end user.

Function Points - An EffectiveSizing Metric

Benefits:

Quantitative (Objective) Measure

Industry Data asBasis for Comparison

Expectations (Perceived Customer Value) Managed

Software Process Improvement Requirements Satisfied



A vehicle to estimate cost and resources required forsoftware development, enhancements and/ormaintenance

A tool to quantify performance levels and to monitorprogress made from software process improvementinitiatives

A tool to determine the benefit of an application to anorganization by counting functions that specificallymatch requirements

A tool to size or evaluate purchased applicationpackages

Benefits of Using FunctionPoints



Approach to Function Points

A function point count is performed to produce a

functional size measure

The size can be used to generate project estimates

Estimates should be based upon delivery rates

Analysis - plan versus actual comparisons

How good is the information received duringrequirements?

How good (accurate) is project estimating?



Review the available documentation

Meet with SME to gain a thorough

understanding of the functionality

Apply the function point methodology,

and compute a functional size

Generate an estimate based on available

delivery rates

Function Point Counting Process



Inputs

Outputs Inquiries

Internal Logical Files

External Interface Files

Input Inquiry Output

Internal

LogicalFiles

External

Interface

File

Five key components are

identified based on logical user view

Application

The Function Point Methodology



USER

LIST OF MOLDSWORKCENTERS

PARTS

PLANT MOLDS

PLANT INFORMATION CENTER

USER

BILL OF MATERIALS

PARTSLISTING

USER

ORDERPARTS

USER

CHANGEBILL

Inquiries

Internal Logical Files

Output

Inputs

InterfaceVENDORSUPPLY

VENDOR INFORMATION

Logical View of UserRequirements



Complexity

RecordElement

Types

Data Elements (# of unique data fields)

orFile

TypesReferenced

Low

Average HighLow

Low Average

HighAverage High

Components: Low Avg. High TotalInternal Logical File (ILF) __ x 7 __ x 10 __ x 15 ___External Interface File (EIF) __ x 5 __ x 7 __ x 10 ___External Input (EI) __ x 3 __ x 4 __ x 6 ___External Output (EO) __ x 4 __ x 5 __ x 7 ___External Inquiry (EQ) __ x 3 __ x 4 __ x 6 ___

___Total Unadjusted FPs

DataRelationships

Each identified component is assigned a Function Point size value based upon

the make-up and complexity of the data

1 3

3




General System Characteristics

Data Communication On-Line Update

Distributed Data Processing Complex Processing

Performance Objectives Reusability

Heavily Used Configuration Conversion & Install Ease

Transaction Rate Operational Ease

On-Line Data Entry Multiple-Site Use

End-User Efficiency Facilitate Change

The final calculation is based upon the Unadjusted FP count X VAF

14 Optional General Systems Characteristics are evaluated and used

to compute a Value Adjustment Factor (VAF)



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Function Point Calculation

Enhancement FPs as they relate to existing master count:

External Inputs (EI) (2)Add/Change Account; change; high

complexity; total unadjusted FPs = 2 x 6 = 12

External Input (EI)Issue Material; change; high complexity; total

unadjusted FPs = 1 x 6 = 6

External Input (EI)Add Tax; change; low complexity; total unadjusted

FPs = 1 x 3 = 3

Total Unadjusted FPs: 21Value Adjusted Factor: 1.01

Total Adjusted FPs: 21


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Example Counting Accuracy

Estimate:

Resulting size = 150 function points

Matching profile, rate of delivery = 10 FP/EM

Estimated effort = 15 effort months

Actuals: Results

Size 175 fps +17%Effort 19 effort months +27%


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Example Scope Accuracy

Counting Activity FP

Resulting Requirements size = 120

Resulting Design size = 144 Resulting Install size = 174

Analysis:

Inputs Outputs Inquiries Interfaces Files Total75 10 15 7 13 120

80 25 17 7 15 144

95 40 17 7 15 174


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PROJECTSIZE

X X RISKFACTORS

PROJECTCOMPLEXITY

DEFINITION CAPABILITY ESTIMATE

Schedule

EffortCosts

REQUIREMENT

FUNCTION POINT ANALYSIS

Project Estimation


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Capability Analysis

Collect project data Project metrics (e.g., effort, size, cost, duration, defects)

Project characteristics

Project attributes (e.g., skill levels, tools, process, etc.) Project complexity variables

Analyze data Performance comparisons (identification of process

strengths and weaknesses)

Industry averages and best practices

Performance modeling (identify high impact areas)


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DCG Data Base

Characteristics Complexity Variables

Project Type

Platform

Data Base

MethodLanguage

Metrics Attributes

Size Management

Cost Definition

Effort Design

Duration Build

Defects Test

Environment

Logical Algorithms Code Structure

Mathematical Algorithms Performance

Data Relationships Memory

Functional Size SecurityReuse Warranty

ProcessSkill Levels

Quality Practices

Measures


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Quantitative & QualitativeAssessments

MEASURES

Research

PROFILES

PERFORMANCE

LEVELS

CHARACTERISTICS

Software Size

Level of Effort

Time to MarketDelivered Defects

Cost

Skill Levels

Automation

Process

ManagementUser Involvement

Environment

Analysis

Results Correlate Performance Levels to Characteristics Substantiate Impact of Characteristics

Identify Best Practices


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PROJECT SIZE andCOMPLEXITY

RATE OFDELIVERY

DEFINITION CAPABILITY ESTIMATE

Schedule

EffortCosts

REQUIREMENT

FUNCTION POINT SIZE

Estimating Using HistoricalDelivery Rates

FUNCTION POINTSPer EFFORT MONTH


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Analysis of Results

Analyze estimating accuracy

Plan vs. actual comparisons

Effectiveness of delivery rates

Evaluate the system level documentation Change in scope (size) through the various stages

Clarity of requirements and design documents

Recommend improvements

Improve the level of documentation for more accuratesizing

Establish a more effective estimating practice


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D

ProductDeliverable

Performance Profiles

Time to Deliver- Duration- Number of days

Level of EffortDefects

SizePlatformLanguage

SIZEPROJECT

MEASURES PROFILES

Rate of DeliveryTime to MarketDefect Density

A

B

CD

AB

C

D

:

136

276

435

558

759

10 mnths

35 effort mnths

10 defects

Develop a Baseline of Data


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Establish A Baseline

Software

Size

Size is

expressed

in terms

of functionality

delivered to the

user

Rate of delivery is a

measure of productivityRate of Delivery

Function Points per Person Month

0

200

400

600

800

1000

12001400

1600

1800

2000

2200

0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 34 36

Performance Productivity

A representative selection

of projects is measured

Organizational Baseline


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Compare To IndustryBenchmarks

Industry baseline performance

Rate of DeliveryFunction Points per Person Month

0200

400

600

800

1000

1200

1400

1600

1800

2000

2200

0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 34 36

Software

Size


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Function PointsPer Person Month

Web 22

e-business Web 12

Client Server 15

Main Frame 13

Vendor Packages 19Data Warehouse 11

Average of Recent Projects Across

Different Platforms


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Function Points SupportedBy One FTE

Web 748

e-business Web 464Vendor Packages 760

Data Warehouse 546

Client Server 642Main Frame 943

AS 400 597

Average of Support Provided for

Corrective Maintenance by One FTE


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Analyze Results

COLLECT

QUANTITATIVE DATA

COLLECT

QUALITATIVE DATA

Process

Methods

Skills

ToolsManagement

Measured

Performance

Capability

Profiles

BaselinePerformance

Collection

Analysis

Results

Action OpportunitiesFor Improvement

Best

Practices

Size

Effort

Duration

CostQuality


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Develop parametric models that utilize historical

data points for purposes of analyzing the impact of

selected process improvements

Provide a knowledge base for improved decisionmaking

Identify areas of high impact (e.g., productivity and

quality

Create an atmosphere of measuring performance

Opportunity for comparison to industry best

practices

Model Performance


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COLLECT

QUANTITATIVE DATA

Size

Effort

DurationCost

Quality

Measured

Performance

Average Project Size 133Average FP/SM 10.7

Average Time-To-Market (Months) 6.9

Average Cost/FP $939

Delivered Defects/FP 0.0301

Baseline

Productivity

Quantitative Assessment

Perform functional sizing on all selected projects.

Collect data on project level of effort, cost, duration

and quality.

Calculate productivity rates for each project, including

functional size delivered per staff month, cost per

functional size, time to market, and defects delivered.

Results

Quantitative PerformanceEvaluation


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COLLECT

QUALITATIVE DATA

Process

Methods

Skills

Tools

Management

Capability

ProfilesAccounts Payable 55.3 47.73 82.05 50.00 46.15 43.75 50.00

Priotity One 27.6 50.00 48.72 11.36 38.46 0.00 42.31

HR Enhancements 32.3 29.55 48.72 0.00 42.31 37.50 42.31

Client Accounts 29.5 31.82 43.59 0.00 30.77 37.50 42.31

ABC Release 44.1 31.82 53.85 34.09 38.46 53.13 42.31Screen Redesign 17.0 22.73 43.59 0.00 15.38 0.00 30.77

Customer We b 40.2 45.45 23.08 38.64 53.85 50.00 34.62

Whole Life 29.2 56.82 28.21 22.73 26.92 18.75 53.85

Regional - East 22.7 36.36 43.59 0.00 30.77 9.38 30.77

Regional - West 17.6 43.18 23.08 0.00 26.92 9.38 26.92

Cashflow 40.6 56.82 71.79 0.00 38.46 43.75 38.46

Credit Automation 23.5 29.55 48.72 0.00 38.46 6.25 26.92

NISE 49.0 38.64 56.41 52.27 30.77 53.13 53.85

Help Desk Automation 49.3 54.55 74.36 20.45 53.85 50.00 38.46Formula One Upgrade 22.8 31.82 38.46 0.00 11.54 25.00 46.15

Design Build Test Environm entProjec t Name Prof ile Score Management De fini tion

Results

Qualitative Assessment

Conduct Interviews with members of each project team.

Collect Project Profile information.

Develop Performance Profiles to display strengths and

weaknesses among the selected projects.

Qualitative PerformanceEvaluation


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Accounts Payable 55.3 47.73 82.05 50.00 46.15 43.75 50.00

Priotity One 27.6 50.00 48.72 11.36 38.46 0.00 42.31

HR Enhancements 32.3 29.55 48.72 0.00 42.31 37.50 42.31

Client Accounts 29.5 31.82 43.59 0.00 30.77 37.50 42.31

ABC Release 44.1 31.82 53.85 34.09 38.46 53.13 42.31

Screen Redesign 17.0 22.73 43.59 0.00 15.38 0.00 30.77

Customer W eb 40.2 45.45 23.08 38.64 53.85 50.00 34.62

Whole Life 29.2 56.82 28.21 22.73 26.92 18.75 53.85

Regional - East 22.7 36.36 43.59 0.00 30.77 9.38 30.77

Regional - West 17.6 43.18 23.08 0.00 26.92 9.38 26.92

Cashflow 40.6 56.82 71.79 0.00 38.46 43.75 38.46


NISE 49.0 38.64 56.41 52.27 30.77 53.13 53.85Help Desk Automation 49.3 54.55 74.36 20.45 53.85 50.00 38.46Formula One Upgrade 22.8 31.82 38.46 0.00 11.54 25.00 46.15

De sign Build Test Environm entProject Name Profi le Score Management Defin it ion

Average Project Size 133

Average FP/SM 10.7




Baseline

Productivity

Average Project Size 133

Average FP/SM 24.8




Productivity

Improvement

Process Improvements:

Code Reviews and Inspections

Requirements Management

Defect Tracking Configuration Management

Performance Improvements:

Productivity ~ +131%

Time to Market ~ -49%

Defect Ratio ~ -75%

Accounts Payable 75.3 61.73 82.05 60.00 60.15 53.75 50.00

Priotity One 57.6 57.00 55.72 18.36 45.46 22.00 49.31

HR Enhanceme nts 52.3 32.55 51.72 23.00 42.31 57.50 49.31

Client Accounts 69.5 53.82 65.59 12.00 50.77 67.50 49.31

ABC Release 74.1 55.82 69.85 49.09 52.46 63.13 49.31

Screen Redesign 67.0 43.73 63.59 21.00 36.38 20.00 51.77

Customer Web 59.2 49.45 27.08 58.64 53.85 54.00 49.62

Whole Life 50.2 49.82 32.21 27.73 31.92 24.75 53.85

Regional - East 57.7 59.36 49.59 0.00 30.77 9.38 50.77

Regional - West 52.6 55.18 30.08 0.00 33.92 19.38 26.92

Cashflow 67.6 66.82 71.79 0.00 49.46 53.75 49.46


NISE 79.0 68.64 76.41 62.27 65.77 53.13 53.85

Help Desk Automation 79.3 64.55 74.36 47.45 63.85 54.00 58.46

Formula One Upgrade 52.8 49.82 52.46 0.00 31.54 25.00 56.15

Design Build Test Environm entProject Name Prof il e Sco re Man ag eme nt De fini tion

Modeled Improvements


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Conclusions

Project Management can be successful

Requirements can be managed

Projects can be sized

Performance can be successfully estimated

Process improvement can be modeled

Measurement can be accomplished


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Contact Information

David Consulting Group web site:

www.davidconsultinggroup.com

David Garmus

[email protected]
http://www.davidconsultinggroup.com/mailto:[email protected]:[email protected]://www.davidconsultinggroup.com/


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Contact Information

International Function Point Users Group (IFPUG)

www.ifpug.org

Practical Software and Systems Measurement (PSM)

www.psmsc.com

Software Engineering Institute (SEI)

www.sei.cmu.edu

Software Quality Engineering (SQE)

www.sqe.com

Quality Assurance Institute (QAI)www.qaiusa.com

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