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COCOMO II: Airborne Radar System Example

COCOMO II: Airborne Radar System Example. Ray Madachy madachy@usc.edu CSCI 510 September 14, 2005. Outline. Overview the Airborne Radar System (ARS) Demonstrate progressive usage of different COCOMO sub-models within an evolutionary spiral development process

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COCOMO II: Airborne Radar System Example

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  1. COCOMO II: Airborne Radar System Example Ray Madachy madachy@usc.edu CSCI 510 September 14, 2005 9/14/05

  2. Outline • Overview the Airborne Radar System (ARS) • Demonstrate progressive usage of different COCOMO sub-models within an evolutionary spiral development process • Cover estimation of reuse, modification, COTS, and automated translation • Show how an aggregate estimate is refined in greater detail 9/14/05

  3. ARS Estimation • Use Applications Composition, Early Design and Post-Architecture submodels • Two Post-Architecture estimates are demonstrated: top-level and detailed • scale drivers apply to overall system in both estimates • cost drivers are rated for the aggregate system in the top-level estimate (17 ratings) • cost drivers are refined for each individual software component in the detailed estimate (17*6 components=102 ratings) 9/14/05

  4. ARS System Overview 9/14/05

  5. Software Components • Radar Unit Control • controls radar hardware • Radar Item Processing • extracts information from returned radar to identify objects • Radar Database • maintains radar object tracking data • Display Manager • high level displays management • Display Console • user input device interface and primitive graphic processing • Built In Test • hardware monitoring and fault localization 9/14/05

  6. COCOMO Coverage in Evolutionary Lifecycle Process * both top-level and detailed estimates shown 9/14/05

  7. Prototype Size and Effort Productivity is “high” at 25 NAP/PM Effort = NAP/ Productivity = 136.3/25 = 5.45 PM (or 23.6 person-weeks) Personnel = 23.5 person-weeks/6 weeks ~ 4 full-time personnel 9/14/05

  8. Precedentedness (PREC) Development Flexibility (FLEX) Risk/Architecture Resolution (RESL) Team Cohesion (TEAM) Process Maturity (PMAT) Nominal Low High Nominal Nominal Scale Factors for Breadboard Factor Rating 9/14/05

  9. High Very High High High Nominal Nominal Nominal Product Reliability and Complexity (RCPX) Required Reuse (RUSE) Platform Difficulty (PDIF) Personnel Capability (PERS) Personnel Experience (PREX) Facilities (FCIL) Schedule (SCED) Early Design Cost Drivers for Breadboard Factor Rating 9/14/05

  10. Breadboard System Size Calculations 9/14/05

  11. Early Design Estimate for Breadboard 9/14/05

  12. ARS Full Development for IOC • Use Post-Architecture estimation model • same general techniques as the Early Design model for the Breadboard system, except for elaborated cost drivers • Two estimates are demonstrated: top-level and detailed • scale drivers apply to overall system in both estimates • cost drivers are rated for the aggregrate system in the top-level estimate (17 ratings) • cost drivers are refined for each individual software component in the detailed estimate (17*6 components=102 ratings) 9/14/05

  13. ARS Top-Level Size Calculations 9/14/05

  14. Post-Architecture Estimate for IOC (Top-level) 9/14/05

  15. Post-Architecture Estimate for IOC (Detailed) 9/14/05

  16. Sample Incremental Estimate 9/14/05

  17. Increment Phasing 9/14/05

  18. Increment Summary 9/14/05

  19. Summary and Conclusions • We provided an overview of the ARS example provided in Chapter 3 • We demonstrated using the COCOMO sub-models for differing lifecycle phases and levels of detail • the estimation model was matched to the known level of detail • We showed increasing the level of component detail in the Post-Architecture estimates • Incremental development was briefly covered 9/14/05

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