Architecture-level reliability prediction of concurrent systems

  • Authors:

  • Leslie Cheung;Ivo Krka;Leana Golubchik;Nenad Medvidovic

  • Affiliations:

  • NetApp, Sunnyvale, CA, USA;University of Southern California, Los Angeles, CA, USA;University of Southern California, Los Angeles, CA, USA;University of Southern California, Los Angeles, CA, USA

  • Venue:
  • ICPE '12 Proceedings of the 3rd ACM/SPEC International Conference on Performance Engineering
  • Year:
  • 2012

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Abstract

Stringent requirements on modern software systems dictate evaluation of dependability qualities, such as reliability, as early as possible in a system's life cycle. A primary shortcoming of the existing design-time reliability prediction approaches is their lack of support for modeling and analyzing concurrency in a scalable way. To address the scalability challenge, we propose SHARP, an architecture-level reliability prediction framework that analyzes a hierarchical scenario-based specification of system behavior. It achieves scalability by utilizing the scenario relations embodied in this hierarchy. SHARP first constructs and solves models of basic scenarios, and combines the obtained results based on the defined scenario dependencies; the dependencies we handle are sequential and parallel execution of multiple scenarios. This process iteratively continues through the scenario hierarchy until finally obtaining the system reliability estimate. Our evaluations performed on real-world specifications indicate that SHARP is (a) almost as accurate as a traditional non-hierarchical method, and (b) more scalable than other existing techniques.