This work was supported by NASA under contract NNL13AC67T. Any opinions, findings, conclusions, or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of NASA or the U.S. Government. Several individuals contributed to the study described in this report. Siddhartha Bhattacharyya of Rockwell Collins provided general oversight, outline of the sections and characterization. Darren Cofer of Rockwell Collins developed sections on certification challenges and also on the general oversight. Dave Musliner, Joseph Mueller and Eric Engstrom provided insight into intelligent and adaptive control algorithms. Kelly J. Hayhurst from NASA Langley Research Center provided valuable input regarding adaptive systems and certification. Many researchers from academia, industry and government agencies provided insight into adaptive systems.The use of trademarks or names of manufacturers in this report is for accurate reporting and does not constitute an official endorsement, either expressed or implied, of such products or manufacturers by the National Aeronautics and Space Administration.
This paper describes an experiment to use the Spin model checking system to support automated verification of time partitioning in the Honeywell DEOS real-time scheduling kernel. The goal of the experiment was to investigate whether model checking with minimal abstraction could be used to find a subtle implementation error that was originally discovered and fixed during the standard formal review process. The experiment involved translating a core slice of the DEOS scheduling kernel from C++ into Promela, constructing an abstract "test-driver" environment and carefully introducing several abstractions into the system to support verification. Attempted verification of several properties related to time-partitioning led to the rediscovery of the known error in the implementation. The case study indicated several limitations in existing tools to support model checking of software. The most difficult task in the original DEOS experiment was constructing an adequate environment to close the system for verification. The fidelity of the environment was of crucial importance for achieving meaningful results during model checking. In this paper, we describe the initial environment modeling effort and a follow-on experiment with using semi-automated environment generation methods. Program abstraction techniques were also critical for enabling verification of DEOS. We describe an implementation scheme for predicate abstraction, an approach based on abstract interpretation, which was developed to support DEOS verification.
This paper describes an experiment to use the Spin model checking system to support automated verification of time partitioning in the Honeywell DEOS real-time scheduling kernel. The goal of the experiment was to investigate whether model checking could be used to find a subtle implementation error that was originally discovered and fixed during the standard formal review process. To conduct the experiment, a core slice of the DEOS scheduling kernel was first translated without abstraction from C++ into Promela (the input language for Spin). We constructed an abstract "test-driver" environment and carefully introduced several abstractions into the system to support verification. Several experiments were run to attempt to verify that the system implementation adhered to the critical time partitioning requirements. During these experiments, the known error was rediscovered in the time partitioning implementation. We believe this case study provides several insights into how to develop cost-effective methods and tools to support the software design and implementation review process.
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