Robustness Hinting

    Carnegie Mellon University

    [ People | Publications | Related Work | Affiliates | Sponsors ]

    Robustness Hinting will provide analysis of error handling to an underlying subsystem. This will determine when it is necessary to take additional and perhaps costly, in terms of system resources, measures to overcome failure conditions. Additional measures should only be taken when there is no application code to handle the failure condition.

    Robustness Hinting requires two types of solutions. The first is an analysis of the application to direct the automatic insertion of hints. We are pursuing this using both static and dynamic program analysis techniques. The second need is the intelligent usage of the robustness hint in order to improve overall performance.

    Dynamic Program Analysis examines the ability of applications to handle error conditions. We use callee-generated software fault generation to determine an applicatin's ability to handle error conditions. Does the application handle the errors generated by the subsystem or called module. If an error is generated by the code that you call, how does your software behave?

    Static Program Analysis is a mechanism for providing a robustness metric of an application. The identification of general robustness problems can be used to provide feedback to the programmer to direct the manual insertion of  error checks into  the application code at the most appropriate location.

    Direct comments and questions to: bigrigg @ ices . cmu . edu

    People

    • Michael Bigrigg
      Project Scientist, Institute for Complex Engineered Systems, Carnegie Mellon University
    • Student Research Programmers, Carnegie Mellon University
      Madhur Joshi, Jeff Knupp, Morgan Linton
    • Student Research Programmers, University of Pittsburgh
      Michael Finnerty, Alexander Poulis, Joe Slember, Julie Sperow, Jacob Vos, Christy Wilson
    • Student Research Programmers, University of North Carolina
      Amit Mathew


    Publications

    • Robustness Hinting for Improving End-to-End Dependability. Michael W. Bigrigg. Second Workshop on Evaluating and Architecting System Dependability (EASY). In conjunction with ASPLOS-X, San Jose, CA, USA, October 2002.
      Abstract / PDF
    • The Set-Check-Use Methodology for Detecting Error Propagation Failures in I/O Routines. Michael W. Bigrigg, Jacob J. Vos. Workshop on Dependability Benchmarking in conjunction with The International Conference on Dependable Systems and Networks, DSN-2002. Washington DC, June 2002.
      Abstract / PDF
    • Testing the Portability of Desktop Applications to a Networked Embedded System. Michael W. Bigrigg and Joseph G. Slember. Workshop on Reliable Embedded Systems, in conjunction with the 20th IEEE Symposium on Reliable Distributed Systems, October 28, 2001, New Orleans, LA.
      Abstract / PDF

    Related Projects

    Static Program Analysis for Robustness Checking

    • LcLint, University of Virginia
    • Software Productivity Tools, Microsoft Research
    • Meta-level Compilation, Stanford
    • Open Source Quality, Berkeley
    • CodeWizard, Parasoft
    • Extended Static Checking, Compaq Research

    Dynamic Program Analysis for Robustness Checking

    • Ballista, Carnegie Mellon University
    • Fuzz, University of Wisconsin
    • CrashMe

    Associated Departments, Institutes and Labs at CMU

    • Institute for Complex Engineered Systems
    • Department of Electrical and Computer Engineering
    • Embedded and Reliable Information Systems Laboratory
    • Parallel Data Laboratory

    Sponsors

    • Pennsylvania Infrastructure Technology Alliance
    • Defense Advanced Research Projects Agency


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    Last updated 11 November, 2004