1. Applying COCOMO II Effort Multipliers to Simulation Models 16th International Forum on COCOMO and Software Cost Modeling Jongmoon Baik and Nancy Eickelmann Software and System Engineering Research Laboratory Motorola Labs Oct 25, 2001

2. Outline Problems What is Model & Simulation? Simulation Model Comparison Why COCOMO II Parameters? Example –System Test Process –DSD (Distributed Software Development) Future Work

3. Problems Most Critical Decision  Early in the lifecycle –Little information available to assess the proposed process changes and technology insertions Difficult to understand problems in the current complex processes

4. Model and Simulation Model “ An abstraction or simplified representation of a real or conceptual complex system. It is designed to display significant features and characteristics of the system under study.” Simulation “Computerized model that possesses the characteristics described above and that represents some dynamic system or phenomenon.”

5. Primary Benefits of Simulation Process Characterization Quantitative Analysis for Proposed Process Changes and Technology Insertions –Support Decision Making and Risk Assessment Support to achieve Higher CMM levels –Quantitative process Management and software Quality Management (CMM-Level 4) –Process/Technology Change Management and Continuous Process Improvement (CMM_Level 5) Project Planning including Effort/Schedule/Cost Estimation

6. Change Process Comparison Proposed Plan for Process Changes and Technology Insertions Process Manager, Team, or Cost Estimators Implementation of Process Changes and Technology Insertions Refin e Feed Back Analysis Proposed Plan for Process Changes and Technology Insertions Simulation Model Implementation of Process Changes and Technology Insertions Process Manager, Team, or Cost Estimators Feed Forward RefineQuantitative ControlFeed Back

7. Simulation Model Comparison Continuous ModelDiscrete Event Model Advantages -Continuous changes of process & product attributes -Captures stable or unstable feedback loops -Predict the unanticipated side effects from changes of process and product attributes -Easy to represent queues -Delay b/w activities based on available resources -Unique attributes for each entity -Capture the effects of variation in the entities for each activity -Capture inter-dependencies b/w activities Disadvantages -Difficult to describe process steps (Explicit mechanism for controlling the discrete activity sequence) -No individual entity and attributes -Same rate for each model run -Variable changes only at the event times -Difficult to represent simultaneous activities Common Use Economics, System Dynamics, Scientific (biology, Chemistry, Physic) processes, Electronics, Control Systems Business Process Reengineering, Networks, Systems Engineering, Manufacturing

8. Why COCOMO II Parameters? Widely accepted public cost model –Calibrated with 161 actual project data Objective impact analysis for each factor - If There is no data available for the parameter Can be calibrated from the organization’s historical data Dynamic effect can be added into simulation model –Different rating values over time (COCOMO81 Detailed COCOMO)

9. COCOMO II EMs to Simulation Product: RELY, DATA, DOCU,CPLX, RUSE Platform: TIME, STOR, PVOL Personnel: ACAP, APEX, PCAP, PLEX, LTEX, PCON Project: TOOL, SITE, SCED

10. System Test Process Simulation Baseline a current System Test Process Predict impact of process change and technology insertion on schedule, quality, effort System Requirements System Architecture Requirements System Detailed Design Box Rqmts Box Design System Functional Requirements Box (auto)Coding Box Unit Test Box System Test System Early SDL Integration testing System Early Integration testing System Integration Test System System Test Subsystem Integration Test Subsystem System Test (host/target) Box Integration Test System Beta Test Text Text eMSC SL + SDL Text eMSC SDL(process), C Box Validation Activities System Validation Activities eMSC Extended Message Sequence Charts SDL Specification and Design Language SL “SL”, data language eMSC, SDL(blocs) SDL (blocs)

11. Example: LTEX Used to assess the impact of SDL/MSC insertion into a system test process Map SDL Ranks (1-5) to LTEX ratings (VL to VH) SDL

12. Schedule Saving by LTEX Total Savings –Nominal (N to VH)  10.05 Days –Maximum (VL to VH)  24.51 Days

13. DSD [Distributed Software Development] Communication Breakdown Coordination Breakdown Geographical Dispersion Loss of Team Cohesiveness Cultural Differences Source: IEEE Software March/April 2001, Robert D. Battin et. al. “Leveraging Resources in Global Software Development” SITE PMAT TEAM PREC TOOL

14. Future Work More Application of Effort Multipliers to Simulation of Process Segments Refine the simulation model Through the calibration of applied COCOMO II parameters Expand simulation model to find out the dynamic impacts of the parameters