My Estimation

7/28/2019 My Estimation

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Project Management

Estimation


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LOC and FP Estimation

Lines of code and function points weredescribed as basic data from which productivity

metrics can be computed.LOC and FP data are used in two ways during

software project estimation: as estimation variablesthat are used to "size" each

element of the software, and

as baseline metricscollected from past projects andused in conjunction with estimation variables todevelop cost and effort projections.


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The LOC and FP techniques differ in the level

of detail required for decomposition.

With LOC, decomposition must be taken toextremes; with FP less detail is required

because the data required to estimate function

points are more macroscopic.

Note that LOC is estimated directly, FP

indirectly.


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Expected value?

Regardless of whether LOC or FP is used, the

planner provides a range of values for each

decomposed function. Using historical data (orintuition) the planner estimates an optimistic,

most likely, and pessimistic LOC or FP for

each function.

The expected value for LOC or FP is then

computed as a weighted average of the three.


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For example,

E = (a + 4m + b) / 6

gives greatest credence to the most likely estimate

and follows a beta probability distribution.

Once the expected value has been determined,productivity data are applied.


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COCOMO

Boehm, in his 1981 book "Software EngineeringEconomics", introduced a hierarchy of software

estimation models called COCOMO,COnstructive COst MOdel. (Version 2 in 1995)

Basic COCOMO,

Intermediate COCOMO,

Advanced COCOMO, COCOMO is a well developed model which takes project, product,

hardware and personnel attributes into account. It also includes meansof estimating development schedules. A disadvantage is that itdepends on historical data which may not always be available.


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Basic COCOMO

a static single-valued model that computes

software development effort (and cost) as a

function of program size expressed in lines ofcode.


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Intermediate COCOMO

computes software development effort as a

function of program size and a set of "cost

drivers" that include subjective assessments ofproduct, hardware, personnel, and project

attributes.


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Advanced COCOMO

incorporates all characteristics of the

intermediate version with an assessment of the

cost driver's impact on each step (analysis,design, ...) of the software engineering process.


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COCOMO & 3 classes of project

organic mode

relatively small, simple software projects in

which small teams with good applicationexperience work to a set of less than rigid

requirements

(e.g., a thermal analysis program developed fora heat transfer group);


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semi-detached modean intermediate (in size and complexity)

software project in which teams with mixedexperience levels must meet a mix of rigid and

less than rigid requirements

(e.g., a transaction processing system with fixedrequirements for terminal hardware and

database software);


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embedded mode

a software project that must be developed

within a set of tight hardware, software, andoperational constraints (e.g., flight control

software for aircraft).


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The basic COCOMO equations take the form

E = ab(KLOC) exp(b

b) E = aK

b

D = cb(E) exp(d

b) D = cE

d

where E is the effort applied in person-months,

D is the development time in chronological months, and

KLOC is the estimated number of delivered lines of code for the project

(expressed in thousands).


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The coefficients aband c

band the exponents b

band d

bare given below.

Software project ab

bb

cb

db

Organic 2.4 1.05 2.5 0.38

Semi-detached 3.0 1.12 2.5 0.35Embedded 3.6 1.20 2.5 0.32


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Extensions

The basic model is extended to consider a

set of "cost driver attributes" that can be

grouped into four major categories:Product attributes

Hardware attributes

Personnel attributes

Project attributes


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Product attributes

Required software reliability

Size of application database

Complexity of the product


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Hardware attributes

Runtime performance constraints

Memory constraints

Volatility of the virtual machine

environment

Required turnaround time


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Personnel attributes

Analyst capability

Software engineer capability

Applications experience

Virtual machine experience

Programming language experience


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Project attributes

Use of software tools

Application of software engineering

methods

Required development schedule


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Effort Adjustment Factors

Each of the 15 attributes is rated on a 6-point

scale that ranges from "very low" to "extra

high" (in importance or value). Based on therating, an effort multiplier is determined from

tables published by Boehm, and the product of

all effort multipliers results is an effort

adjustment factor(EAF.)Typical values for EAF range from 0.9 to 1.4.


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The intermediate COCOMO equation takes the form:

E = ai(KLOC) exp(bi) x EAF E = aKb

* EAF

where

E is the effort applied in personmonths and

KLOC is the estimated number of delivered lines of code for the project.

The coefficient ai and the exponent biare given below

Software project ai bi

Organic 3.2 1.05Semi-detached 3.0 1.12

Embedded 2.8 1.20


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But ...

Boehm's own comments about COCOM0 (and

by extension all models) should be heeded:

"Today, a software cost estimation model is doing well if it can

estimate software development costs within 20%of actual costs,

70% of the time, and on its own turf (that is, within the class of

projects to which it has been calibrated) .... This is not as precise as

we might like, but it is accurate enough to provide a good deal ofhelp in software engineering economic analysis and decision

making."


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Example ...

estimated LOC 33360

estimated project cost $656,680

estimated effort (PM) 144.5

and the table of coefficients earlier, and using the semi-

detached model, we get

E = 3.0 (KLOC) exp(1.12)

= 3.0(33.3)1.12

= 152 person-months


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Example contd ...

To compute project duration,

D = 2.5(E) exp(0.35)

= 2.5(152)0.35= 14.5 months

The recommended number of people for the project is

therefore,

N = E/D

= 152/14.5

= 11 people


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Automated Estimation Tools

These tools allow the planner to estimate cost and effort

and to perform what if analyses for important project

variables such as delivery date or staffing.

Those based on COCOMO all require the user to

provide a preliminary LOC estimate.

They all conduct a dialog with the planner, obtaining

appropriate project and supporting information and

producing both tabular and graphical output.


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Automated Estimation Tools

When a number of tools were applied to the

same project, a relatively large variation in

estimated results was found, and predictedvalues were sometimes very different from

actual values.

Output from estimation tools should be used as

one data point from which estimates are

derived - not as the only source for an estimate.


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Joness First-Order Estimation

Take the function-point total and raise it tothe power chosen from the following table

best average worstSystems 0.43 0.45 0.48

Business 0.41 0.43 0.46

Shrink-wrap 0.39 0.42 0.45 The exponents are based on analysis of a

database of several thousand projects


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Joness kinds of projects

Systems = operating systems, device drivers,

compilers, embedded software, firmware, real-

time systems, Business = in-house systems for an

organisation, payroll, stock control, accounting

systems, IS, IT, MIS software,

Shrink-wrap = packaged and sold commercially


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e.g.

If FP=350 and project is shrink-wrap in

an average organisation then 350 0.42 =

11.7087, giving a rough schedule of 12calendar months.

In a best-in-class organisation 350 0.39

giving a schedule of 10 months.

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