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Exploring Software Project Effort versus Duration Trade-offs

Exploring Software Project Effort versus Duration Trade-offs. Prepared by : Hala As’ad - 7014651 Mariam Bastami - 6196298 submitted to Professor Shervin Shirmohammadi in partial fulfillment of the requirements for the course ELG 5100. Agenda. Introduction

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Exploring Software Project Effort versus Duration Trade-offs

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  1. Exploring Software Project Effort versus Duration Trade-offs Prepared by : HalaAs’ad - 7014651 Mariam Bastami - 6196298 submitted to Professor Shervin Shirmohammadi in partial fulfillment of the requirements for the course ELG 5100

  2. Agenda • Introduction • Effort-Duration Estimating Models • Symons’ process for effort -duration trade-off • Symons’ Reference Model • Symons’ Comparisons • Symons’ analysis procedure • Results • Conclusions and future work • References

  3. Introduction • At the beginning of the software project the estimator starts to predict some estimations for the expected : • Time • Effort • Cost …. etc . • These estimations are called central or optimal estimations.

  4. Introduction • In this project , we will study the effect of increasing or decreasing the size of the team on the duration of the project (schedule compression or expansion). • Other factors such as management pressure , requirements changes, or any environmental changes will be eliminated.

  5. Introduction • To measure the the effort versus duration trade-off , the estimators should be able to answer “what if “questions. • The answers of what if questions based on :

  6. Effort-Duration Estimating Models

  7. Putnam’s Software Life-Cycle Management (Slim) • Created by Lawrence Putnam in 1978 . • Used to estimate effort, time and cost that required to finish a software project according to its size. • This model works by collecting data , and used empirical analysis that based on the productivity level and the size of the project.

  8. Galorath’s Seer for Software (Seer-SEM) • Created by Galorath in the late 1980s • It is a tool that is programmed to allows the estimator to predict the project duration, effort and budget, and determine the probability of project completion on a certain date. • The Seer application has a variety of graphs, charts, and diagrams to illustrate the progress of the project http://www.galorath.com/DirectContent/SEERforSoftware2.pdf, (accessed on October 20𝑡ℎ ,2013)

  9. Symons’ process for effort-duration trade-off http://www.validest.com/img4.gif , (Accessed on November 25th ,2013)

  10. Symons’ Reference Model • Anther form of the equation : Rel. E: Relative effort. Rel. D: Relative duration.

  11. Symons’ Comparisons • Software Life Cycle Management (Slim) • N is 4 for both the compression and expansion sides. http://doi.ieeecomputersociety.org/ 10.1109/MS.2011.126 (Accessed on October 20th,2013)

  12. Symons’ Comparisons • Galorath’s Seer for Software (Seer.SEM) • N equal 2 In the compression side. • N equal -0.55 In the expansion side http://doi.ieeecomputersociety.org/ 10.1109/MS.2011.126 (Accessed on October 20th, 2013)

  13. Symons’ analysis procedure

  14. Step 1: Project acceptance and validation 1. Selecting the projects according to : • Completion dates. • Quality of the projects. • Consistency in the used measurement methods. • Ignoring the enhancement projects that has total enhancement size greater than 1,000 UFP 2.Checking average staffing level

  15. Step 2: Project grouping • why grouping ?

  16. Step 2: Project grouping • For small groups , Combining the groups that used primary programing languages from the same family . • Exclude groups with less than 12 projects. Result: 15 groups

  17. Step 3: Determining effort and the duration with respect to the size • Effort versus size and duration versus size were plotted for 15 groups. • Power curve fitting algorithm were used (norm curve). • Eliminating the outliers that give exponentially large size .

  18. Step 3: Determining effort and the duration with respect to the size • Observations: • Determination coefficient (R2) is higher for the effort data in comparison with the duration data. Why? • The average value for R2is higher for COSMIC enhancement projects in comparison with IFPUG enhancement projects. • No differences in R2 for new development projects. • Finally, Splitting some groups. • Result: 16 groups with 600 projects http://doi.ieeecomputersociety.org/ 10.1109/MS.2011.126 (Accessed on October 20th , 2013)

  19. Step 3: Determining effort and the duration with respect to the size

  20. Step 4: Plotting Relative Effort versus Duration • Determine the norm Effort and the norm Duration . • Calculate Relative Effort and Relative Duration by: Note : Assume NormEffort and Duration is the Central estimation in the reference equation.

  21. Step 4: Plotting Relative Effort versus Duration • Plot Relative Effort with Relative Duration • Sort the data based on the size . http://doi.ieeecomputersociety.org/ 10.1109/MS.2011.126 (Accessed on October 20th ,2013)

  22. Step 4: Plotting Relative Effort versus Duration - Calculate the Staffing Level (SL) - Divide the data according to SL into five bands.

  23. Step 4: Plotting Relative Effort versus Duration • http://doi.ieeecomputersociety.org/ 10.1109/MS.2011.126 (Accessed on October 20th ,2013)

  24. Step 5: Computing Exponent N SL is the driving factor • Plot Rel. E with SL and Rel. D with SL. • Use power curve fitting method to find the best fitted power curve for the data. • Calculate N(SL) using the reference equation. • http://doi.ieeecomputersociety.org/ 10.1109/MS.2011.126 (Accessed on October 20th ,2013)

  25. Step 5: Computing Exponent N

  26. Results

  27. Conclusions and Future works • Stuffing level (SL) is a crucial factor in the effort duration trade-off. • Symons’ process only accepts the projects of A and B qualities . Extend this process to test other projects with other qualities might be helpful to prove the robustness of this process. • Increase the number of the data in each group to be at least 30 projects instead of 12; this would validate the statistical analysis. • Many factors rather than the number of staff would cause compressing and expanding in the schedule . Therefore,considering these factors might extend the process to be more practical.

  28. References [1] Putnam, L. H. , "A General Empirical Solution to the Macro Software Sizing and Estimating Problem," Software Engineering, IEEE Transactions on SE-4(4), 345-361 (1978). [2]“SEER for Software: Estimating Software Projects,” product webpage, Galorath, 2011; http://www.validest.com/img4.gif, (accessed on October,202013) [3]Barry,E. , Mukhopadhyay,T. , Slaughter,S. , “Software Project Duration and Effort:An Empirical Study, “ Information Technology and Management on SE- 3, 113–136 (2002). [4] Symons, C. , "Exploring Software Project Effort versus Duration Trade-offs," Software, IEEE 29(4), 67-74 (2012) [5] Symons, C. , web extra accompanies the article "Exploring Software Project Effort versus Duration Trade-offs," Software, IEEE 29(4), 67-74 (2012); http://doi.ieeecomputersociety.org/10.1109/MS.2011.126 (accessed on October,20th ,2013) [6] Symons C., “The Performance of Business Application, Real-time and Component Software Projects: An Analysis of COSMIC-Measured Projects in the ISBSG Database,” Int’l Software Benchmarking Standards Group ( 2012 ).

  29. Thank you Questions

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