information extraction for real-time embedded systems sebastian fischmeister university of waterloo...
TRANSCRIPT
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Information Extraction for Real-time Embedded Systems
Sebastian FischmeisterUniversity of Waterloo
esg.uwaterloo.ca
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Aim of the Talk
• Provide an overview of the research done within or associated with the project ORF-RE 03-045: “Certification of Safety-critical Software-intensive Systems”
• Create an opportunity for integrating of research results and collaborating
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Assumptions / Facts
• Software is where the innovation is happening!Features sell, apps everywhere
• Software size and complexity is thechallenge!
Illustrating one root cause:Bridge from Tokyo
to Vancouver
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Assumptions / Facts
• Computing systems are now beyond deep human comprehension.
• Evidence:– Software size is growing exponentially– Processor complexity is growing exponentially– 80% of the developer’s time is debugging
– We have software with 100M lines of code!
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100M LOC?
• Nuclear shutdown system: 40k lines of code
• F-22 Raptor (‘97): 1.7M lines of code• F-35 Joint Strike Fighter (‘06): 5.7M lines of code• Boeing 787 (‘09): 6.5M lines of code
• Current generation limousine: 100M LOC
Can we comprehend such software?
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Trying to Understand the Certification Problem
• Toronto: 2,503,281 • Ontario: 13,210,667• USA: 300M
You need to ensure that each person is doingthe right thing at the right time.
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PROJECT SAMPLER:REAL-TIME EMBEDDED SOFTWARE GROUP @ UNIVERSITY OF WATERLOO
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Vision: Information Extraction
Time awareinstrumentation
Coverage criterion [RTAS’09, TII]
ISA extension [TR]
Time-triggeredruntime verification
Crit. CFG & sampling [FM’11]
Mem vs. sampl. tradeoff [RV’11]
Time-triggeredexecution monitoring
Markers[LCTES’10]
bitvec+[LCTES’11]
Observabilityin software
Super-loop[LCTES’11]
Preemptive[OPODIS’11]
Debugging, tracing &monitoring
framework forRT embeddedapplications
Tagging
Basics [TR] Security [TR]
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Understanding Complex Programs• Problem: Can we efficiently trace information flow in a
software system? => Tagging
• Implemented in QNX at the kernel level• Applied to tracing, resource scheduling, and security• Applicable to testing, monitoring non-functional req.
Process
Network
Tag
Tag
Tag
Tag
X
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Understanding Complex Programs• Problem: Can we instrument programs without
changing the timing (thus the behaviour)? => time-aware instrumentation
• Applied to three case studies (OLPC, FS, SNU)• Software solution, hardware solution, code dup• Useful for tracing, testing, information extraction
Instrumented
Freq
uenc
y
Execution time
Original
Deadline
X
X X
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Monitoring Complex Programs• Problem: Can we engineer run-time monitoring
and checking of programs? => TTRVApplication
Program
Observer
Monitor
Steering
Report
Observe
Eval.properties
• Time-triggered monitoring & property evaluation
• Useful for system safety,security, steering, tuning, …
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Trying to Understand Complex Programs• Problem: How do people try to understand
software systems? => debugging study
• Useful to guide future tools• Useful to understand developers’ minds
Successfuldebuggers
Failingdebuggers
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Conclusions• Software systems are hard to understand• Software is growing in size and complexity
=> Developers need support to understand what is going on at run time!
• We research methods that help developers understand what the software is doing, especially tailored to (real-time) embedded systems.
• (We also work on benchmarking & real-time networking)• (We also host the CFI Real-time Embedded Software Lab)
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Acknowledgements
• This research was supported in part by industrial partners and the Canadian tax payer!
• In collaboration with Akramul Azim, Pansy Arafa, Akramul Azim, Shay Berkovich, Borzoo Bonakdarpour, Sina Gholamian, Hany Kashif, Patrick Lam, Samaneh Navabpour, Hiren Patel, Yassir Rizwan, Ahmad Rehman, Johnson Thomas, Mahesh Tripunithara, Augusto Oliveira, Wallace Wu.