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COCOMO

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The Constructive Cost Model COCOMO is a procedural software cost estimation model developed by Barry W Boehm The model parameters are derived from fitting a regression formula using data from historical projects 61 projects for COCOMO 81 and 163 projects for COCOMO II

Contents

  • 1 History
  • 2 Basic COCOMO
  • 3 Intermediate COCOMOs
  • 4 Detailed COCOMO
  • 5 See also
  • 6 References
  • 7 Further reading
  • 8 External links

Historyedit

The constructive cost model was developed by Barry Boehm in the late 1970s1 and published in Boehm's 1981 book Software Engineering Economics2 as a model for estimating effort, cost, and schedule for software projects It drew on a study of 63 projects at TRW Aerospace where Boehm was Director of Software Research and Technology The study examined projects ranging in size from 2,000 to 100,000 lines of code, and programming languages ranging from assembly to PL/I These projects were based on the waterfall model of software development which was the prevalent software development process in 1981

References to this model typically call it COCOMO 81 In 1995 COCOMO II was developed and finally published in 2000 in the book Software Cost Estimation with COCOMO II3 COCOMO II is the successor of COCOMO 81 and is claimed to be better suited for estimating modern software development projects; providing support for more recent software development processes and was tuned using a larger database of 161 projects The need for the new model came as software development technology moved from mainframe and overnight batch processing to desktop development, code reusability, and the use of off-the-shelf software components This article refers to COCOMO 81

COCOMO consists of a hierarchy of three increasingly detailed and accurate forms The first level, Basic COCOMO is good for quick, early, rough order of magnitude estimates of software costs, but its accuracy is limited due to its lack of factors to account for difference in project attributes Cost Drivers Intermediate COCOMO takes these Cost Drivers into account and Detailed COCOMO additionally accounts for the influence of individual project phases

Basic COCOMOedit

Basic COCOMO compute software development effort and cost as a function of program size Program size is expressed in estimated thousands of source lines of code SLOC, KLOC

COCOMO applies to three classes of software projects:

  • Organic projects - "small" teams with "good" experience working with "less than rigid" requirements
  • Semi-detached projects - "medium" teams with mixed experience working with a mix of rigid and less than rigid requirements
  • Embedded projects - developed within a set of "tight" constraints It is also combination of organic and semi-detached projectshardware, software, operational,

The basic COCOMO equations take the form

Effort Applied E = abKLOCbbman-months Development Time D = cbEffort Applieddb monthsPeople required P = Effort Applied / Development Time count

where, KLOC is the estimated number of delivered lines expressed in thousandsof code for project The coefficients ab, bb, cb and db are given in the following table note:the values listed below are from the original analysis, with a modern reanalysis4 producing different values:

Software projectabbbcbdb
Organic2410525038
Semi-detached3011225035
Embedded3612025032

Basic COCOMO is good for quick estimate of software costs However it does not account for differences in hardware constraints, personnel quality and experience, use of modern tools and techniques, and so on

Intermediate COCOMOsedit

Intermediate COCOMO computes software development effort as function of program size and a set of "cost drivers" that include subjective assessment of product, hardware, personnel and project attributes This extension considers a set of four "cost drivers", each with a number of subsidiary attributes:-

  • Product attributes
    • Required software reliability
    • Size of application database
    • Complexity of the product
  • Hardware attributes
    • Run-time performance constraints
    • Memory constraints
    • Volatility of the virtual machine environment
    • Required turnabout time
  • Personnel attributes
    • Analyst capability
    • Software engineering capability
    • Applications experience
    • Virtual machine experience
    • Programming language experience
  • Project attributes
    • Use of software tools
    • Application of software engineering methods
    • Required development schedule

Each of the 15 attributes receives a rating on a six-point scale that ranges from "very low" to "extra high" in importance or value An effort multiplier from the table below applies to the rating The product of all effort multipliers results in an effort adjustment factor EAF Typical values for EAF range from 09 to 14

Cost DriversRatings
Very LowLowNominalHighVery HighExtra High
Product attributes
Required software reliability075088100115140 
Size of application database 094100108116 
Complexity of the product070085100115130165
Hardware attributes
Run-time performance constraints  100111130166
Memory constraints  100106121156
Volatility of the virtual machine environment 087100115130 
Required turnabout time 087100107115 
Personnel attributes
Analyst capability146119100086071 
Applications experience129113100091082 
Software engineer capability142117100086070 
Virtual machine experience121110100090  
Programming language experience114107100095  
Project attributes
Application of software engineering methods124110100091082 
Use of software tools124110100091083 
Required development schedule123108100104110 

The Intermediate Cocomo formula now takes the form:

E=aiKLoCbiEAF

where E is the effort applied in person-months, KLoC is the estimated number of thousands of delivered lines of code for the project, and EAF is the factor calculated above The coefficient ai and the exponent bi are given in the next table

Software projectaibi
Organic32105
Semi-detached30112
Embedded28120

The Development time D calculation uses E in the same way as in the Basic COCOMO

Detailed COCOMOedit

Detailed COCOMO incorporates all characteristics of the intermediate version with an assessment of the cost driver's impact on each step analysis, design, etc of the software engineering process

The detailed model uses different effort multipliers for each cost driver attribute These Phase Sensitive effort multipliers are each to determine the amount of effort required to complete each phase In detailed cocomo,the whole software is divided in different modules and then we apply COCOMO in different modules to estimate effort and then sum the effort

In detailed COCOMO, the effort is calculated as function of program size and a set of cost drivers given according to each phase of software life cycle

A Detailed project schedule is never static

The Six phases of detailed COCOMO are:-

  • plan and requirement
  • system design
  • detailed design
  • module code and test
  • integration and test
  • Cost Costructive Model

See alsoedit

  • COCOMO II Model http://wwwsoftstarsystemscom/cocomo2htm
  • Comparison of development estimation software
  • Cost overrun
  • COSYSMO
  • Estimation in software engineering
  • Function point
  • Object point
  • Putnam model
  • SEER-SEM
  • Software development effort estimation
  • Software engineering economics

Referencesedit

  1. ^ Stutzke, Richard "Software Estimating Technology:A Survey" Retrieved 9 Oct 2016 DOC
  2. ^ Boehm, Barry 1981 Software Engineering Economics Prentice-Hall ISBN 0-13-822122-7 
  3. ^ Barry Boehm, Chris Abts, A Winsor Brown, Sunita Chulani, Bradford K Clark, Ellis Horowitz, Ray Madachy, Donald J Reifer, and Bert Steece Software Cost Estimation with COCOMO II with CD-ROM Englewood Cliffs, NJ:Prentice-Hall, 2000 ISBN 0-13-026692-2
  4. ^ "COCOMO:Not worth serious attention" The Shape of Code 19 May 2016 Retrieved 4 November 2016 

Further readingedit

  • Kemerer, Chris F May 1987 "An Empirical Validation of Software Cost Estimation Models" PDF Communications of the ACM 30 5:416–42 doi:101145/2289922906 

External linksedit

  • COCOMO 81 data on tera-PROMISE
  • Analysis of the COCOMO 81 data obtains a different value for the Organic exponent


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