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Gashi, I.; Popov, P. T. (2006)
Languages: English
Types: Unknown
Subjects: QA76
We have reported previously (Gashi et al., 2004) results of a study with a sample of bug reports from four off-the-shelf SQL servers. We checked whether these bugs caused failures in more than one server. We found that very few bugs caused failures in two servers and none caused failures in more than two. This would suggest a fault-tolerant server built with diverse off-the-shelf servers would be a prudent choice for improving failure detection. To study other aspects of fault tolerance, namely failure diagnosis and state recovery, we have studied the "data diversity" mechanism and we defined a number of SQL rephrasing rules. These rules transform a client sent statement to an additional logically equivalent statement, leading to more results being returned to an adjudicator. These rules therefore help to increase the probability of a correct response being returned to a client and maintain a correct state in the database.
  • The results below are discovered through our pilot algorithms. Let us know how we are doing!

    • 1. Gashi, I., Popov, P., Strigini, L. Fault diversity among offthe-shelf SQL database servers in DSN'04, 2004, Florence, Italy, IEEE Computer Society Press p. 389-398.
    • 2. Popov, P., et al. Software Fault-Tolerance with Off-theShelf SQL Servers in ICCBSS'04, 2004, Redondo Beach, CA USA, Springer p. 117-126.
    • 3. Popov, P., et al. Protective Wrapping of OTS Components in 4th ICSE Workshop on Component-Based Software Engineering: Component Certification and System Prediction, 2001, Toronto
    • 4. Ammann, P.E. and J.C. Knight, Data Diversity: An Approach to Software Fault Tolerance, IEEE Transactions on Computers, 1988, C-37(4), p. 418-425.
    • 5. TPC, TPC Benchmark C, Standard Specification, Version 5.0. 2002 http://www.tpc.org/tpcc/.
    • 6. Patiño-Martinez, M., Jiménez-Peris, R., Kemme, B., and Alonso, G., MIDDLE-R: Consistent database replication at the middleware level, ACM Transactions on Computing Systems, 2005, 23(4), p. 375-423.
    • 7. Bernstein, P.A., V. Hadzilacos, and N. Goodman, Concurrency Control and Recovery in Database Systems. 1987, Reading, Mass.: Addison-Wesley. 370.
    • 8. Jimenez-Peris, R., M. Patino-Martinez, G. Alonso, and B. Kemme, Are Quorums an Alternative for Data Replication?, ACM Transactions on Database Systems, 2003, 28(3), p. 257-294.
    • 9. Gashi, I., Popov, P., Stankovic, V., Strigini, L., On Designing Dependable Services with Diverse Off-The-Shelf SQL Servers, in Architecting Dependable Systems II, R. de Lemos, C. Gacek, A. Romanovsky (Eds). 2004, SpringerVerlag. p. 191-214.
    • 10. EnterpriseDB, EnterpriseDB. 2006 http://www.enterprisedb.com/.
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    • 12. Gray, J. Why do computers stop and what can be done about it? in 6th International Conference on Reliability and Distributed Databases, 1987
    • 13. Tso, K.S. and A. and Avizienis. Community Error Recovery in N-Version Software: A Design Study with Experimentation in FTCS-17, Pittsburgh, Pennsylvania, July 6-8, 1987 p. 127-133.
    • 14. Sutter, H., SQL/Replication Scope and Requirements document, in ISO/IEC JTC 1/SC 32 Data Management and Interchange WG3 Database Languages. 2000. p. 7
    • 15. Gashi, I., Rephrasing Rules for SQL servers. 2006 http://www.csr.city.ac.uk/people/ilir.gashi/Bugs/.
    • 16. Gashi, I., Tables containing known bug scripts of Firebird 1.0 and PostgreSQL 7.2. 2005 http://www.csr.city.ac.uk/people/ilir.gashi/Bugs/.
    • 17. Gashi, I., Tables containing known bug scripts of Interbase, PostgreSQL, Oracle and MSSQL. 2003 http://www.csr.city.ac.uk/people/ilir.gashi/DSN/.
    • 18. Lin, Y., Kemme, B. et al., Middleware based Data Replication providing Snapshot Isolation in ACM SIGMOD Int. Conf. on Management of Data, 2005, Baltimore, Maryland, USA, ACM Press p. 419-430.
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