1. In The Name Of God Software Development Management Presentors: Mostafa Abdollahi Ehsan Khodarahmi Fall-2010

2. Mazandaran University of Science & Technology SDM-Software Cost Estimation Introduction Inputs and Outputs Methods of Estimation COCOMO Conclusion 2 Outline

3. Mazandaran University of Science & Technology SDM-Software Cost Estimation 55% of projects over budget 24 companies that developed large distributed systems 53% of projects cost 189% more than initial estimates Based on 8,380 projects(1994) 3 Why Cost Estimation?

4. Mazandaran University of Science & Technology SDM-Software Cost Estimation Hardware and software costs Travel and training costs Effort costs (the dominant factor in most projects) Salaries of engineers involved in the project Social and insurance costs Effort costs must take overheads into account costs of building, heating, lighting costs of networking and communications costs of shared facilities (e.g library, staff restaurant, etc.) 4 Software cost components

5. Mazandaran University of Science & Technology SDM-Software Cost Estimation Estimates are made to discover the cost, to the developer, of producing a software system There is not a simple relationship between the development cost and the price charged to the customer Broader organisational, economic, political and business considerations influence the price charged 5 Costing and pricing

6. Mazandaran University of Science & Technology SDM-Software Cost Estimation Someone responsible for the implementation Can compare previous projects in organization to current project Usually experienced Someone from outside of organization Can provide unbiased estimate Tend to use empirical methods of estimation 6 Who is Estimator?

7. Mazandaran University of Science & Technology SDM-Software Cost Estimation Establish Plan What data should we gather Why are we gathering this data What do we hope to accomplish Do cost estimation for initial requirement Decomposition Use several Methods There is no perfect technique If get wide variances in methods, then should reevaluate the information used to make estimates 7 General Steps

8. Mazandaran University of Science & Technology SDM-Software Cost Estimation Do re-estimates during life cycle Make any require changes to development Do a final assessment of cost estimation at the end of the project 8 General Steps(cont.)

9. Mazandaran University of Science & Technology SDM-Software Cost Estimation Definition A set of techniques and procedures that is used to derive the cost estimate Set of inputs to the process and then process will use these inputs to generate the output 9 Software Cost Estimation Process Classical view of software estimation process

10. Mazandaran University of Science & Technology SDM-Software Cost Estimation To determine how well a cost estimation model predicts Assessing model performance Absolute Error = (E pred – E act ) Percentage Error = (E pred – E act ) / E act 10 Cost Estimation Accuracy

11. Mazandaran University of Science & Technology SDM-Software Cost Estimation 11 Cost Estimation Methods Methods Algorithmic (Parametric) Algorithmic (Parametric) Expert Judgment Top-Down Estimation by Analogy Bottom-Up Price to Win Estimation

12. Mazandaran University of Science & Technology SDM-Software Cost Estimation Use of mathematical equations to perform software estimation Equations are based on theory or historical data Use input such as SLOC, number of functions to perform and other cost drivers 12 Algorithmic (Parametric) Model

13. Mazandaran University of Science & Technology SDM-Software Cost Estimation Advantages Generate repeatable estimations Easy to modify input data Easy to refine and customize formulas Disadvantages Unable to deal with exceptional conditions Some experience and factors can not be quantified Sometimes algorithms may be proprietary 13 Algorithmic (Parametric) Model (Cont.)

14. Mazandaran University of Science & Technology SDM-Software Cost Estimation Capture the knowledge and experience of the practitioners and providing estimates based upon all the projects to which the expert participated. Examples Delphi Developed by Rand Corporation in 1940 where participants are involved in two assessment rounds. Work Breakdown Structure (WBS) A way of organizing project element into a hierarchy that simplifies the task of budget estimation and control 14 Expert Judgment

15. Mazandaran University of Science & Technology SDM-Software Cost Estimation Advantages Useful in the absence of quantified, empirical data. Can factor in differences between past project experiences and requirements of the proposed project Can factor in impacts caused by new technologies, applications and languages. Disadvantages Estimate is only as good expert’s opinion Hard to document the factors used by the experts 15 Expert Judgment (Cont.)

16. Mazandaran University of Science & Technology SDM-Software Cost Estimation Also called Macro Model Derived from the global properties of the product and then partitioned into various low level components 16 Top - Down

17. Mazandaran University of Science & Technology SDM-Software Cost Estimation Advantages – Requires minimal project detail – Usually faster and easier to implement – Focus on system level activities Disadvantages – Tend to overlook low level components – No detailed basis 17 Top – Down (Cont.)

18. Mazandaran University of Science & Technology SDM-Software Cost Estimation Cost of each software components is estimated and then combine the results to arrive the total cost for the project The goal is to construct the estimate of the system from the knowledge accumulated about the small software components and their interactions 18 Bottom - Up

19. Mazandaran University of Science & Technology SDM-Software Cost Estimation Advantages More stable More detailed Allow each software group to hand an estimate Disadvantages May overlook system level costs More time consuming 19 Bottom – Up (Cont.)

20. Mazandaran University of Science & Technology SDM-Software Cost Estimation Comparing the proposed project to previously completed similar project in the same application domain Actual data from the completed projects are extrapolated Can be used either at system or component level 20 Estimation by Analogy

21. Mazandaran University of Science & Technology SDM-Software Cost Estimation Advantages Based on actual project data Disadvantages Impossible if no comparable project had been tackled in the past. How well does the previous project represent this one 21 Estimation by Analogy (Cont.)

22. Mazandaran University of Science & Technology SDM-Software Cost Estimation Price believed necessary to win the contract Advantages Often rewarded with the contract Disadvantages Time and money run out before the job is done 22 Price to Win Estimation

23. Mazandaran University of Science & Technology SDM-Software Cost Estimation COCOMO stands for COnstructive COst MOdel It is an open system First published by Dr Barry Bohem in 1981 Worked quite well for projects in the 80’s and early 90’s Could estimate results within ~20% of the actual values 68% of the time 23 COCOMO 81

24. Mazandaran University of Science & Technology SDM-Software Cost Estimation COCOMO has three different models (each one increasing with detail and accuracy): Basic, applied early in a project Intermediate, applied after requirements are specified. Advanced, applied after design is complete COCOMO has three different modes: Organic – relatively small software teams develop software in a highly familiar, in-house environment Embedded – operate within tight constraints, product is strongly tied to complex of hardware, software, regulations, and operational procedures Semi-detached – intermediate stage somewhere between organic and embedded. 24 COCOMO 81

25. Mazandaran University of Science & Technology SDM-Software Cost Estimation MM = a * (KLOC) b *EAF TDEV = c * (MM) d People required = MM / TDEV MM is Effort Applied (in man-months) TDEV is Time Duration Estimated Value (in months) EAF is the Effort Adjustment Factor derived from the Cost Drivers, EAF for the basic model is 1 The values for a, b, c, and d differ depending on which mode you are using 25 COCOMO Equations Modeabcd Organic2.41.052.50.38 Semi Detached3.01.122.50.35 Embedded3.61.202.50.32

26. Mazandaran University of Science & Technology SDM-Software Cost Estimation 26 COCOMO Scaling Factors

27. Mazandaran University of Science & Technology SDM-Software Cost Estimation A simple example: Project is a flight control system (mission critical) with 310 KLOC in embedded mode Reliability must be very high (RELY=1.40). So we can calculate: MM = a * (KLOC) b *EAF – Effort = 1.40*3.6*(310) 1.20 = 4921 MM TDEV = c * (MM) d – Schedule = 2.5*(4921) 0.32 = 37.96 months People required = MM / TDEV – Average Staffing = 4921 MM/37.96 months = 130 27 An Example

28. Mazandaran University of Science & Technology SDM-Software Cost Estimation The exponent value b in the effort equation is replaced with a variable value based on five scale factors rather then constants Size of project can be listed as object points, function points or source lines of code (SLOC). EAF is calculated from seventeen cost drivers better suited for today's methods, COCOMO81 has fifteen 28 COCOMO II Differences

29. Mazandaran University of Science & Technology SDM-Software Cost Estimation COCOMO is the most popular method however for any software cost estimation you should really use more then one method Best to use another method that differs significantly from COCOMO so your project is examined from more then one angle Even companies that sell COCOMO based products recommend using more then one method. 29 Is COCOMO the Best?

30. Mazandaran University of Science & Technology SDM-Software Cost Estimation Project costs are being poorly estimated The accuracy of cost estimation has to be improved Use several methods of estimation 30 Conclusions

31. Mazandaran University of Science & Technology SDM-Software Cost Estimation Boehm B., Clark B., Horowitz E., Madachy R., Shelby R., Westland C. (1995). Cost Models for Future Software Life Cycle Processes: COCOMO 2.0, Annals of Software Engineering. http://sunset.usc.edu/research/COCOMOII/Docs/stc.pdf. http://sunset.usc.edu/research/COCOMOII/Docs/stc.pdf Boehm B., Clark B., Horowitz E., Madachy R., Shelby R., Westland C. (1995). An Overview of the COCOMO 2.0 Software Cost Model. http://sunset.usc.edu/research/COCOMOII/Docs/stc.pdf. http://sunset.usc.edu/research/COCOMOII/Docs/stc.pdf Boehm B., Chulani S., Clark B. (1997). Calibration Results of COCOMO II.1997. http://sunset.usc.edu/publications/TECHRPTS/1998/usccse98- 502/CalPostArch.pdf.http://sunset.usc.edu/publications/TECHRPTS/1998/usccse98- 502/CalPostArch.pdf Boehm B., Chulani S., Clark B. (1997). Calibrating the COCOMO II Post Architecture Model. http://sunset.usc.edu/Research_Group/Sunita/down/calpap.pdf. http://sunset.usc.edu/Research_Group/Sunita/down/calpap.pdf Boehm B., Chulani S., Reifer D., The Rosetta Stone: Making COCOMO 81 Files Work With COCOMO II. http://sunset.usc.edu/publications/TECHRPTS/1998/usccse98- 516/usccse98-516.pdf. http://sunset.usc.edu/publications/TECHRPTS/1998/usccse98- 516/usccse98-516.pdf Chulani, S. (1998). Software Development Cost Estimation Approaches – A Survey. IBM Research. Humphrey, W.S. (1990). Managing the Software Process. Addison- Wesley Publishing Company, New York, NY. 31 References

32. Mazandaran University of Science & Technology SDM-Software Cost Estimation Questions and Discussion 32