national aeronautics and space administration sas08_classify_defects_nikora1 software reliability...
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National Aeronautics and Space Administration
SAS08_Classify_Defects_Nikora 1
Software Reliability Techniques Applied to Constellation
Allen P. Nikora, JPL/Caltech
This research was carried out at the Jet Propulsion Laboratory, California Institute of Technology under a contract with the National Aeronautics and Space Administration. The work was sponsored by the NASA Office of Safety and Mission Assurance under the Software Assurance Research Program led by the NASA Software IV&V Facility. This activity is managed locally at JPL through the Assurance and Technology Program Office
Executive Briefing
NASA OSMA Software Assurance Symposium September 9-11, 2008
09/09/2008
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Agenda• Problem/Approach
• Relevance to NASA
• Accomplishments and/or Tech Transfer Potential
• Next Steps
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Problem/Approach
• Software-related failures responsible for more than half of NASA major space mission losses or malfunctions between 1996 and 2007– Large majority due to system conditions not been
anticipated or fully understood in the system / software specification and design process
– As NASA space missions are increasingly controlled by software, probability of mission failure due to software may increase if no action is taken
– Minimizing loss of crew/loss of mission requires appropriate techniques to evaluate reliability of on-board and ground-based support software during all development phases.
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Problem/Approach (cont’d)• Modeling of a software system in its anticipated
operational context is an important aspect of assuring software reliability.– Recognized in concept of “operational profile”, software reliability
model assumptions– Many techniques for modeling software reliability treat software
in isolation from the hardware on which it runs and which it controls.
• Goals:– Demonstrate feasibility of applying
Context-based Software Risk Modeling (CSRM) technique to CxP applications/scenarios
• Focus on mission-critical applications such as GN&C, Safety and Health Monitoring, Launch Abort
– Develop guidelines for use of context-based techniques– Infuse context-based SW reliability modeling techniques to other
NASA SW development efforts
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Relevance to NASA• Reliability of software component depends on
operating environment. CSRM explicitly includes context in system/software models.
• Unlike traditional software reliability modeling techniques, CSRM helps guide software testing
• CSRM can be used to evaluate risk of software failure during specification and design phases as well as during implementation and test.– Identify risk-prone areas earlier in development
reduced number of defects passed through to test and operations
– Earlier identification of risk-prone areas more effective management of development resources
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Accomplishments and/or Tech Transfer Potential
• Selected PA-1 as initial scenario to be modeled
• Acquired relevant artifacts from Windchill, JSC contacts
• Analysis of PA-1 software specifications/design in progress
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Next steps• Complete development of PA-1
model(s)• Analyze models; evaluate software
failure risk• Review models, results• Refine models• Select further applications to model
National Aeronautics and Space Administration
Backup Information
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CSRM HighlightsFrom “Risk-Informed Software Assurance for NASA Space
Missions”, Sergio Guarro, ASCA Inc., November, 2007
Approach
• PRA-style development of mission and risk scenario models• Uses traditional event-tree / fault-tree logic models at top
modeling level to capture the basic aspects of mission scenarios
• Uses Dynamic Flowgraph Methodology (DFM) models to capture dynamic and logically complex aspects of system/software interactions– DFM analytical and quantitative results are fully compatible and can
be integrated with PRA tool binary models and results (SAPHIRE, CAFTA)
• Modeling and quantification framework is also compatible with / can incorporate risk and assurance info from other tools and sources– Traditional test results– SW-process-quality based information– SW defect / reliability model output