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Algorithmic Software Cost Modeling
Algorithmic software cost modeling uses mathematical functions to estimate project costs based on inputs like project characteristics, development processes, and product attributes. COCOMO is a widely used algorithmic cost modeling method that estimates effort in person-months and development time based on source lines of code and cost adjustment factors. It has basic, intermediate, and detailed models and accounts for factors like application domain experience, process quality, and technology changes.
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Algorithmic Software Cost Modeling
- 1. Algorithmic Software Cost Modeling KasunRanga Wijeweera (krw19870829@gmail.com)
- 2. Algorithmic Cost Modeling •A mathematical function is used to estimate the cost – Inputs: Project, Process, Product – Decided by project managers • Historical data are studied to derive the function • Commonly used product attribute is LOC (code size)
- 3. Software Productivity • Therate at which individual software engineers involve in development process is known as software productivity • Although quality assurance is a factor in productivity assessment, the productivity is not quality oriented • The useful functionality produced per time unit should be measured
- 4. Productivity Measures • Sizerelated measures: – Lines of delivered source code – Object code instructions – Etc • Function related measures: – Functionality of the delivered software – E.g. Function points
- 5. Lines of Code •What programs should be considered as part of the system? • Assumption of the model: – The relationship between system size and volume of documentation is linear • Key thing to remember: – Uncertainty is more important than the initial line – Seek justifiable bounds
- 6. Productivity Comparison • Lowlevel language verses high level language • Verbose code verses compact code
- 7. Function Points • Programcharacteristics are considered – External inputs and outputs – User interactions – External interfaces – Files used by the system • Corresponding weights are assigned to each characteristic
- 8. FPs and LOC •FPs can be used to estimate LOC – LOC = AVC * (Number of FPs) – AVC is a factor which depends on the programming language • Assembly language: AVC = 200 to 300 • 4 GL language: AVC = 2 to 40 • FPs are subjective and dependent on the estimator – FP automation is impossible
- 9. Productivity Estimates • Realtime embedded systems – 40 to 60 LOC per month • Systems programs – 150 to 400 LOC per month • Commercial applications – 200 to 900 LOC per month
- 10. Productivity Factors • Applicationdomain experience • Process quality • Product size • Technology support • Working environment
- 11. Changing Technologies • Previousestimating experience does not carry over to new systems due to changes in technology – Use of web services – Use of CASE tools and program generators – Development for and with reuse – Using scripting languages
- 12. COCOMO • Constructive CostModel (COCOMO) • Estimates are derived as functions of variables • Data of past projects must be available • First published by Dr. Barry Boehm in 1981 • Derived through statistical regression of data from 63 past projects
- 13. Example Size 2000 SLOC 8000 SLOC 32000 SLOC 128000 SLOC MM 521 91 392 Schedule Months 5 8 14 24 Staff 1.1 2.7 6.5 16 SLOC/ MM 400 376 352 327
- 14. Basic Effort Equation •(Effort) = A * (Size) ^ (Exponent) • (Effort) = (EAF) * A * (Size) ^ (Exponent) • Estimates the man-months (MM) of effort for software development project – 1 MM = 152 hours of development • Size is the source lines of code (SLOC)
- 15. Modes and Modelsof COCOMO • Three modes – Organic mode – Semidetached mode – Embedded mode • Three models – Basic model – Intermediate model – Detailed model
- 16. Modes of COCOMO •Organic mode – Similar to an earlier project – Familiar and stable environment – E.g. Accounting system • Semidetached mode – Between Organic and Embedded modes • Embedded mode – New project involving new inventions – E.g. Real-time systems
- 17. Models of COCOMO •Basic model – Roughly estimates project cost, performance and schedule • Intermediate model – EAF (Effort Adjustment Factor) is used from 15 cost drivers • Detailed model – Different Effort Multipliers are used for each phase of project
- 18. Effort Equation :Basic • (Effort) = A * (Size) ^ (Exponent) • A is a constant which depends on the mode of development – Organic: 2.4, Semidetached: 3.0, Embedded: 3.6 • (Exponent) is also a constant which depends on the mode of development – Organic: 1.05, Semidetached: 1.12, Embedded: 1.20 • Size should be in KSLOC (1000 SLOC)
- 19. Schedule Equation :Basic • Minimum time to develop (MTDEV) • (MTDEV) = 2.5 * (Effort) ^ (Exponent) • Exponent is a constant which depends on the mode – Organic: 0.38, Semidetached: 0.35, Embedded: 0.32 • 2.5 is constant for all modes • MTDEV is independent from the number of people assigned
- 20. Effort Equation :Intermediate • (Effort) = (EAF) * A * (Size) ^ (Exponent) • A is a constant which depends on the mode of development – Organic: 3.2, Semidetached: 3.0, Embedded: 2.8 • (Exponent) is also a constant which depends on the mode of development – Organic: 1.05, Semidetached: 1.12, Embedded: 1.20 • Size should be in KSLOC (1000 SLOC)
- 21. EAF (Effort AdjustmentFactor) • EAF = Product of effort multipliers
- 22. Schedule Equation :Intermediate • Minimum time to develop (MTDEV) • (MTDEV) = 2.5 * (Effort) ^ (Exponent) • Exponent is a constant which depends on the mode – Organic: 0.38, Semidetached: 0.35, Embedded: 0.32 • 2.5 is constant for all modes • MTDEV is independent from the number of people assigned
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