University of Southern California Center for Software Engineering CSE USC SCRover Increment 3 and JPL’s DDP Tool USC-CSE Annual Research Review March 16, 2004 Barry Boehm, Ray Madachy, Jesal Bhuta, Eric Gradman, LiGuo Huang, Alex Lam, Steve Meyers, Gustavo Perez, Vincent Rosso

University of Southern California Center for Software Engineering CSE USC ©USC-CSE 2 HDC Project Background Continuing USC research on the NASA/CMU High Dependability Computing (HDC) Program –Research on dependability-enhancing technologies (e.g. formal methods, model checking, architecture analysis, human factors, code analysis, testing, etc.) –Empirical technology evaluation Testbeds are used to exercise new technologies under relevant mission conditions –Provide an organized archive of empirical data

University of Southern California Center for Software Engineering CSE USC ©USC-CSE 3 SCRover Overview SCRover is an ITAR-safe testbed that uses JPL’s Mission Data Systems (MDS) technology –MDS is a systems engineering methodology and software toolset Goal: Make SCRover representative of Mars Science Lab (MSL) mission to evaluate dependability strategies –Reference mission is post-earthquake campus safety monitoring Model SCRover on DDP risk tool to match MSL –Bridge the gap between results on technologies’ defect reduction capabilities and assessments of their impact on dependability attributes

University of Southern California Center for Software Engineering CSE USC ©USC-CSE 4 SCRover

University of Southern California Center for Software Engineering CSE USC ©USC-CSE 5 Increment 3 Plan Complete requirements this spring –Obstacle avoidance Use camera images and laser range finder to detect and maneuver around –Target sensing and data processing Visit points of interest along path to target –Multi-user goal-conflict resolution Find best path to maximize points of interest within power constraints Deliver in Q4 Developers: Eric Gradman, Alex Lam and Vincent Rosso –Currently working on camera, power adapter, and goal- conflict resolution algorithms

University of Southern California Center for Software Engineering CSE USC ©USC-CSE 6 DDP Background Defect Detection and Prevention (DDP) is a risk management framework –A systematic, continuous, top-down approach to risk management –Embodied in a software tool Widely used in JPL, not including the software domain –USC collaboration for HDC is the first extensive application for software risks –Results will be used by JPL for downstream mission planning –Win-Win for all

University of Southern California Center for Software Engineering CSE USC ©USC-CSE 7 DDP Concepts Three linked tree structures for requirements (mission objectives), risks and mitigations –Risks related to requirements Indication of how much each risk impacts each requirement –Mitigations related to risks The effect of each mitigation on each risk A set of mitigations achieves benefits and incurs costs Facilitates the selection of a set of mitigations to attain requirements in a cost-effective manner

University of Southern California Center for Software Engineering CSE USC ©USC-CSE 8 SCRover Risk Model Portions effectiveness matrix showing defect reduction percentage

University of Southern California Center for Software Engineering CSE USC ©USC-CSE 9 SCRover Sample DDP Output Green indicates risk reduction from selected mitigations

University of Southern California Center for Software Engineering CSE USC ©USC-CSE 10 DDP Acknowledgements and Demonstration JPL personnel collaborating on DDP include Steve Cornford, Martin Feather, Al Nikora, Leila Meshkat Demos presented here by Steve Meyers