University of Southern California Center for Systems and Software Engineering USC CSSE Research Overview Barry Boehm Sue Koolmanojwong Jo Ann Lane Nupul Kukreja 1

University of Southern California Center for Systems and Software Engineering Overview ICSM overview ICSM process guide overview and demo Early feasibility evidence Cost modeling for complex systems and systems of systems Requirements/solution space negotiating 2

University of Southern California Center for Systems and Software Engineering Incremental Commitment Spiral Model (ICSM) 3

University of Southern California Center for Systems and Software Engineering ICSM Principles Stakeholder value-based system definition and evolution Incremental commitment and accountability Concurrent system and software definition and development Evidence and risk-based decision-making 4

University of Southern California Center for Systems and Software Engineering The ICSM Electronic Process Guide (EPG) Tool: IBM® Rational® Method Composer® A process management platform with a content management system 5 The ICSM EPG is available at

University of Southern California Center for Systems and Software Engineering Status of the ICSM EPG Develop software development process guidelines describing roles, responsibilities, work products, delivery process, and etc. Currently support –Process guidelines for 4 process patterns Architected Agile, Use Single NDI, NDI-Intensive, Net-Centric Services –Small-project based –Fixed schedule Used and evolved across 38 distributed-team projects in 3 years 6

University of Southern California Center for Systems and Software Engineering ICSM EPG: Operational Concept Development Practice 7

University of Southern California Center for Systems and Software Engineering ICSM EPG Demo 8

University of Southern California Center for Systems and Software Engineering Types of Milestone Reviews Schedule-based reviews (contract-driven) –We’ll hold the PDR on April 1 whether we have a design or not –High probability of proceeding into a Death March Event-based reviews (artifact-driven) –The design will be done by June 1, so we’ll have the review then –Large “Death by PowerPoint and UML” event Hard to avoid proceeding with many unresolved risks and interfaces Evidence-based commitment reviews (risk-driven) –Evidence provided in Feasibility Evidence Description (FED) A first-class deliverable –Shortfalls in evidence are uncertainties and risks –Should be covered by risk mitigation plans –Stakeholders decide to commit based on risks of going forward 9

University of Southern California Center for Systems and Software Engineering Anchor Point Feasibility Evidence Descriptions Evidence provided by developer and validated by independent experts that: If the system is built to the specified architecture, it will –Satisfy the requirements: capability, interfaces, level of service, and evolution –Support the operational concept –Be buildable within the budgets and schedules in the plan –Generate a viable return on investment –Generate satisfactory outcomes for all of the success-critical stakeholders All major risks resolved or covered by risk management plans Serves as basis for stakeholders’ commitment to proceed Can be used to strengthen current schedule- or event-based reviews 10

University of Southern California Center for Systems and Software Engineering 11 Size Drivers Cost Drivers SE Effort Calibration Number of requirements Number of interfaces Number of algorithms Number of operational scenarios 8 Application factors 6 Team factors Schedule driver COSYSMO Single System Systems Engineering (SE) Cost Model* Prediction Accuracy Academic version –Single system cost model calibrated with data from multiple organizations: PRED(30)=75% Local calibration versions –Anecdotal evidence: PRED(30)=85% * COSYSMO [Valerdi, 2005] General Form of academicCOSYSMO Equation Effort (person months) = [38.55 * EM * (size) 1.06 ] / 152 where – and 1.06 are the academicCOSYSMO calibration factors – EM is computed from cost drivers

University of Southern California Center for Systems and Software Engineering May 2010 Complex Systems and SoS Challenges 12Copyright © USC-CSSE

University of Southern California Center for Systems and Software Engineering Complex System Effort Estimation Model 13 System Capabilities Sub 1 effort System-level effort Equivalent set of “sea-level” requirements Sub n effort Total SE Effort Applies reuse factors, different cost factors for each engineering organization at each system level, and diseconomy of scale for system-level and subsystem-level requirements implemented in the parallel….

University of Southern California Center for Systems and Software Engineering SoS Effort Estimation Model 14 System Capability CS 1 SoSE contribution effort SoSE effort Equivalent set of “sea-level” requirements CS n SoSE contribution effort SoSE Effort Applies reuse factors, different cost factors for each engineering organization at each system level, and diseconomy of scale for SoS and CS-level requirements implemented in the same upgrade cycle….

University of Southern California Center for Systems and Software Engineering Requirements/Solution Space Negotiating Tool Demo 15