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Question of the day

If you were the boss, what would you do for cost estimation?

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Cost Estimation

Estimates based on LOC

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Prediction Formulas

E=X

>1

<1

=1

TTYP1 – which one did Henry Ford experience?

Size

cost

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Cost Estimation Models LOC models

– Boehm's COCOMO– Putnam's Model (SLIM)

non-LOC models– Function Points

combination– COCOMO2

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Boehm's COCOMO

Software Engineering Economics Prentice-Hall c1981 type COCOMO in a search engine - many

www sites

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COnstructive COst MOdel

Basic– macro - overview of whole project with one

metric of KSLOC Intermediate

– multiplicative adjustment factors Detailed

– applying model to each phase

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Modes of Software Development

Organic– detached, often batch

Semidetached– e.g. transaction processing

Embedded– e.g. os kernel

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Programmer Effort

Application Programs– PM = 2.4 * (KDSI)1.05

Utility Programs– PM = 3.0 * (KDSI)1.12

Systems Programs– PM = 3.6 * (KDSI)1.20

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Example for effort Size Appl Util Sys 5K 13.0 18.2 24.8 10K 26.9 39.5 57.1 15K 41.2 62.2 92.8 20K 55.8 86.0 131.1 25K 70.5 110.4 171.3 30K 85.3 135.3 213.2 35K 100.3 160.8 256.6 40K 115.4 186.8 301.1 45K 130.6 213.2 346.9 50K 145.9 239.9 393.6

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Development Time (Months)

Application Programs– TDEV = 2.5 * (PM) 0.38

Utility Programs– TDEV = 2.5 * (PM) 0.35

Systems Programs– TDEV = 2.5 * (PM) 0.32

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Example for development time

size appl util sys 5K 6.63 6.90 6.99 10K 8.74 9.06 9.12 15K 10.27 10.62 10.66 20K 11.52 11.88 11.90 25K 12.60 12.97 12.96 30K 13.55 13.93 13.91 35K 14.40 14.80 14.75 40K 15.19 15.59 15.53 45K 15.92 16.33 16.25 50K 16.61 17.02 16.92

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Average Staffing Levels

Calculate by dividing PM by TDEV

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Example for staffing levels

size appl util sys 5K 1.96 2.63 3.55 10K 3.08 4.37 6.26 15K 4.01 5.87 8.71 20K 4.84 7.23 11.02 25K 5.60 8.51 13.21 30K 6.30 9.72 15.33 35K 6.97 10.87 17.39 40K 7.60 11.98 19.39 45K 8.20 13.05 21.35 50K 8.79 14.09 23.27

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Productivity

The productivity is defined as LOC per time unit.

The usual units are LOC/Programmer-Day

Divide final size of project by total programmer-days of effort for the whole software development

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TTYP2

What is the effort, productivity, staffing and delivery time for an application project that takes 82K loc?

What is the effort, productivity, staffing and delivery time for a system project that take 200K loc?

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COCOMO Effort Multipliers

product attributes – required reliability 0.75 - 1.40

– data-base size 0.94 - 1.16

– product complexity 0.70 - 1.65 computer attributes

– execution time constraint 1.00 - 1.66

– main storage constraint 1.00 - 1.56

– virtual machine volatility 0.87 - 1.30

– computer turnaround time 0.87 - 1.15

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Putnam's Cost Estimation Model

macro-estimation model that uses LOC relationship between cost and the amount of

time available for the development effort. The model supports the 'mythical man-

month' idea

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Putnam's Model

Uses the Rayleigh Curve– Shows Instantaneous Programmer-power vs

Time– Empirically verified on other projects

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Rayleigh Curve

The rayleigh curve is a product of at times e raised to the -bt squared

The at dominates at first giving a steep rise and then the negative power of e lowers the value slowly

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Rayleigh Curve

y : instantaneous programmer-power K : total lifecycle cost ( in programmer-years) t : time from beginning of project td: delivery time e= 2.71828...

y Kt

te

d

ttd

22

22

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Software Equation

There must be a relationship between the lifecycle development effort, the development time and the size of the project.

This relationship is given in the Software Equation

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Software Equation

Ss = C*K1/3 td4/3

– where:

– Ss is the estimated size of the software system

– K is the total lifecycle effort in programmer-years

– C is the technology constant

– td is the development time (in years)

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Putnam by spread-sheet

S td (years) K .4K ProgProd100000 1 100000 40000 0.0125100000 1.5 19753 7901 0.0633100000 2 6250 2500 0.2000100000 2.5 2560 1024 0.4883100000 3 1235 494 1.0125100000 3.5 666 267 1.8758100000 4 391 156 3.2000100000 4.5 244 98 5.1258100000 5 160 64 7.8125100000 5.5 109 44 11.4383100000 6 77 31 16.2000100000 6.5 56 22 22.3133100000 7 42 17 30.0125

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Summary

What could you do as a manager to improve cost estimation?