Software Cost Estimation - NTUAkkontog/ECE750-3/metrics-2-notes.pdf3 Software cost estimation •...

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Software Cost Estimation

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• These slides are based on:– Lecture slides by Ian Summerville, see

http://www.comp.lancs.ac.uk/computing/resources/ser/

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Software cost estimation

• Predicting the resources required for a software process

©Ian Sommerville 1995

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Topics covered• Productivity• Estimation techniques• Algorithmic cost modelling• Project duration and staffing


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Software cost components• Effort costs (the dominant factor in most

projects)– salaries of engineers involved in the project– costs of building, heating, lighting– costs of networking and communications– costs of shared facilities (e.g library, staff restaurant,

etc.)– costs of pensions, health insurance, etc.

• Other costs– Hardware and software costs– Travel and training costs– … ©Ian Sommerville 1995 [modified]

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Costing and pricing• There is not a simple relationship between the

development cost and the price charged to the customer

• Software pricing factors– Market opportunity – low price to enter the market,

e.g., initially “free software”– Cost estimation uncertainty– Contractual terms– Requirements volatility– Financial health– …

©Ian Sommerville 1995 [modified]

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• A measure of the rate at which individual engineers involved in software development produce software and associated documentation– Not quality-oriented although quality assurance

is a factor in productivity assessment

• Measure useful functionality produced per time unit & programmer

Programmer productivity


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• Size related measures based on some output from the software process. This may be lines of delivered source code (SLOC), object code instructions, etc.– E.g., SLOC / person-month

• Function-related measures based on an estimate of the functionality of the delivered software. Function-points are the best known of this type of measure– E.g., FP / person-month

Productivity metrics


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• What's a line of code?– Many different ways to count lines (e.g., with

or without comments, counting statements rather than lines, or counting lines in a automatically formatted code)

– Need to know the measurement method before comparing SLOC numbers

• Assumes linear relationship between system size and volume of documentation

Lines of code


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• Problems of LOC-based comparisons– The lower level the language, the more

productive the programmer– The more verbose the programmer, the higher

the productivity• Function points provide a more accurate

measure of productivity than LOC

Cross-language comparisons


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System development times

Analysis Design Coding Testing DocumentationAssembly codeHigh-level language

3 weeks3 weeks

5 weeks5 weeks

8 weeks8 weeks

10 weeks6 weeks

2 weeks2 weeks

Size Effort ProductivityAssembly codeHigh-level language

5000 lines1500 lines

28 weeks20 weeks

714 lines/month300 lines/month


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Productivity

The “Vicious Square”

+ +

--

- -

+ +

Quality Scope

Development time Cost

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• All metrics based on volume/unit time are flawed because they do not take quality into account

• Productivity may generally be increased at the cost of quality

• It is not clear how productivity/quality metrics are related

Quality and productivity


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• Real-time embedded systems, 40-160 LOC/P-month

• Systems programs , 150-400 LOC/P-month• Commercial applications, 200-800

LOC/P-month

Productivity estimates


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The four variables• The main four variables of a project

– Development cost– Time– Quality– Scope

• Only three of these variables can be (more or less) freely adjusted• Development cost, time and quality are bad control variables

– The number of developers can only be incrementally increased (negative effects beyond the optimal count)

– Deadlines are often predetermined externally (e.g., market window, important presentation)

– Low quality upsets customers and developers• Scope is the only real control variable

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Accuracy of Estimation

Feasibility Requirements Design Code Deliveryx

2x

4x

0.25x

0.5x

As a project progresses, more information aboutthe progress becomes available and the accuracyof estimation can be increased over time.

x – the actual cost of the system

Estimates on projects studied by BarryBoehm occupied the area between the curves

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Estimation techniques• Expert judgement• Estimation by analogy• Parkinson's Law• Pricing to win• Top-down estimation• Bottom-up estimation• Function point estimation• Algorithmic cost modelling


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Expert judgement• One or more experts in both software

development and the application domain use their experience to predict software costs. Process iterates until some consensus is reached.

• Advantages: Relatively cheap estimation method. Can be accurate if experts have direct experience of similar systems

• Disadvantages: Very inaccurate if there are no experts!


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Estimation by analogy• The cost of a project is computed by comparing

the project to a similar project in the same application domain

• Advantages: Accurate if project data available• Disadvantages: Impossible if no comparable

project has been tackled. Needs systematically maintained cost database


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Parkinson's Law• The project costs whatever resources are

available• Advantages: No overspend• Disadvantages: System is usually

unfinished


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Pricing to win• The project costs whatever the customer has to

spend on it• Advantages: You get the contract• Disadvantages: The probability that the

customer gets the system he or she wants is small. Costs do not accurately reflect the work required


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Top-down estimation• Approaches may be applied using a top-down

approach. Start at system level and work out how the system functionality is provided

• Takes into account costs such as integration, configuration management and documentation

• Can underestimate the cost of solving difficult low-level technical problems


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Bottom-up estimation• Start at the lowest system level. The cost of each

component is estimated individually. These costs are summed to give final cost estimate

• Accurate method if the system has been designed in detail

• May underestimate costs of system level activities such as integration and documentation


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Function Points

• The idea of function point was first proposed by Albrecht in 1979.

• The function point of a system is a measure of the “functionality” of the system.

• Steps– Counting the information domain – counting FPs– Assessing complexity of the software – adjusting FPs– Applying an empirical relationship to come up with

LOC or P-months based on the adjusted FPs• This method cannot be performed automatically


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Counting Function Points

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Counting Function Points

• User inputs. Each user input that provides distinct application oriented data to the software is counted.

• User outputs. Each user output that provides application oriented information to the user is counted. Individual data items within a report are not counted separately.

• User inquiries. This is an on-line input that results in the generation of some response.

• Files. Each master file is counted.• External interfaces. Each interface that is used to transmit

information to another system is counted.

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Adjusting Function PointsAnswer the following questions using a scale of [0-5]: 0 not important; 5 absolutely essential. We call them influence factors (Fi).1. Does the system require reliable backup and recovery?2. Are data communications required?3. Are there distributed processing functions?4. Is performance critical?5. Will the system run in an existing, heavily utilized operational env.?6. Does the system require on-line data entry?

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Adjusting Function Points7. Does the on-line data entry require the input transaction to

be built over multiple screens or operations (user efficiency)?

8. Are the master files updated on-line?9. Are the inputs, outputs, files, or inquiries complex?10. Is the internal processing complex?11. Is the code designed to be reusable?12. Is installation included in the design?13. Is the system designed for multiple installations?14. Is the application designed to facilitate change and ease of

use by the user?

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Map FPs to LOC• Use an empirical relationship

– Function point = count total × [0.65 + 0.01 × (sum of the 14 Fi)]– Companies may want to refine their own version

• According to a 1989 study, implementing a function point in a given programming language requires the following number of lines of code– Assembly 320– C 128– COBOL 106– C++ 64– Visual Basic 32– SQL 12

• See www.ifpug.org for more information on FP

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Example: Your PBX project

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Example: Your PBX project

• Total of FPs = 25• F4 = 4, F10 = 4, other Fi’s are set to 0. Sum of all

Fi’s = 8.• FP = 25 x (0.65 + 0.01 x 8) = 18.25• Lines of code in C = 18.25 x 128 LOC = 2336

LOC• In the past, students have implemented their

projects using about 2500 LOC.

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Algorithmic cost modelling• Cost is estimated as a mathematical function of

product, project and process attributes whose values are estimated by project managers

• The function is derived from a study of historical costing data

• Most commonly used product attribute for cost estimation is LOC (code size)

• Most models are basically similar but with different attribute values


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The COCOMO model• Developed at TRW, a US defence contractor• Based on a cost database of more than 60

different projects• Exists in three stages

– Basic - Gives a 'ball-park' estimate based on product attributes

– Intermediate - Modifies basic estimate using project and process attributes

– Advanced - Estimates project phases and parts separately


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Project classes

• Organic mode small teams, familiar environment, well-understood applications, no difficult non-functional requirements (EASY)

• Semi-detached mode Project team may have experience mixture, system may have more significant non-functional constraints, organization may have less familiarity with application (HARDER)

• Embedded Hardware/software systems, tight constraints, unusual for team to have deep application experience (HARD)

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Basic COCOMO Formula• Organic mode: PM = 2.4 (KDSI) 1.05

• Semi-detached mode: PM = 3 (KDSI) 1.12

• Embedded mode: PM = 3.6 (KDSI) 1.2

• KDSI = Kilo Delivered Source Instructions


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Effort estimates1000

800

600

400

200

00

20 40 60 80 100 120

KDSI

Person-months

Embedded

Intermediate

Simple


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• Organic mode project, 32KLOC– PM = 2.4 (32) 1.05 = 91 person months– TDEV = 2.5 (91) 0.38 = 14 months– N = 91/15 = 6.5 people

• Embedded mode project, 128KLOC– PM = 3.6 (128)1.2 = 1216 person-months– TDEV = 2.5 (1216)0.32 = 24 months– N = 1216/24 = 51

COCOMO examples


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• Implicit productivity estimate – Organic mode = 16 LOC/day– Embedded mode = 4 LOC/day

• Time required is a function of total effort NOT team size

• Not clear how to adapt model to personnel availability

COCOMO assumptions


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• Takes basic COCOMO as starting point• Identifies personnel, product, computer and

project attributes which affect cost• Multiplies basic cost by attribute

multipliers which may increase or decrease costs

Intermediate COCOMO


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• Personnel attributes– Analyst capability– Virtual machine experience– Programmer capability– Programming language experience– Application experience

• Product attributes– Reliability requirement– Database size– Product complexity

Personnel attributes


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• Computer attributes– Execution time constraints– Storage constraints– Virtual machine volatility– Computer turnaround time

• Project attributes– Modern programming practices– Software tools– Required development schedule

Computer attributes


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• These are attributes which were found to be significant in one organization with a limited size of project history database

• Other attributes may be more significant for other projects

• Each organization must identify its own attributes and associated multiplier values

Attribute choice


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• All numbers in cost model are organization specific. The parameters of the model must be modified to adapt it to local needs

• A statistically significant database of detailed cost information is necessary

Model tuning


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Predicted costs

0 20 40 60 80 100Size

Effort

Curve fitted tomeasured effort

Predictedeffort


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• Embedded software system on microcomputer hardware.

• Basic COCOMO predicts a 45 person-month effort requirement

• Attributes = RELY (1.15), STOR (1.21), TIME (1.10), TOOL (1.10)

• Intermediate COCOMO predicts – 45*1.15*1.21.1.10*1.10 = 76 person-months.

• Total cost = 76*$7000 = $532, 000

Example


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• Organic: TDEV = 2.5 (PM) 0.38

• Semi-detached: TDEV = 2.5 (PM) 0.35

• Embedded mode: TDEV = 2.5 (PM) 0.32

• Personnel requirement: N = PM/TDEV– This last formula needs to be adjusted (see

next slide)

Development time estimates


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Staffing requirements• Staff required can’t be computed by diving the

development time by the required schedule• The number of people working on a project varies

depending on the phase of the project• The more people who work on the project, the

more total effort is usually required• Very rapid build-up of people often correlates

with schedule slippage• Adding more people to a delayed project will

delay it even more


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Rayleigh manpower curvesN

umbe

r of

peo

ple

Time


RcResources Rc=(t/k2) e-t2/2k2

k1 k2 k3

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Estimation methods - Summary

• Function points– SRS -> LOC– SRS -> PM

• COCOMO– LOC -> PM– May use FP as a front-end to COCOMO

• COCOMO II– Refined version with different estimation models based

on• Requirements (FP->PM),• Early design (FP->PM), and• Architecture (FP or LOC->PM)

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Estimation methods - Summary• Each method has strengths and weaknesses• Estimation should be based on several methods• If these do not return approximately the same

result, there is insufficient information available• Some action should be taken to find out more in

order to make more accurate estimates• Pricing to win is sometimes the only applicable

method


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