Software Component Replication for Improved Fault-Tolerance: Can Multicore Processors Make It Work?

  • João Soares
  • João Lourenço
  • Nuno Preguiça
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7869)


Programs increasingly rely on the use of complex component libraries, such as in-memory databases. As any other software, these libraries have bugs that may lead to the application failure. In this work we revisit the idea of software component replication for masking software bugs in the context of multi-core systems. We propose a new abstraction: a Macro-Component. A Macro-Component is a software component that includes several internal replicas with diverse implementations to detect and mask bugs. By relying on modern multicores processing capacity it is possible to execute the same operation in multiple replicas concurrently, thus incurring in minimal overhead. Also, by exploring the multiple existent implementations of well-known interfaces, it is possible to use the idea without incurring in additional development cost.


Multicore Processor Memory Overhead Current Prototype Fault Tolerance Technique Multiple Replica 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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  1. 1.
    Avizienis, A.: The n-version approach to fault-tolerant software. IEEE Trans. Softw. Eng. 11(12), 1491–1501 (1985)CrossRefGoogle Scholar
  2. 2.
    Bessani, A., Correia, M., Quaresma, B., André, F., Sousa, P.: Depsky: dependable and secure storage in a cloud-of-clouds. In: EuroSys 2011, pp. 31–46 (2011)Google Scholar
  3. 3.
    Chen, L., Avizienis, A.: N-version programming: A fault-tolerance approach to reliability of software operation. In: Proc. FTCS-8, pp. 3–9 (1978)Google Scholar
  4. 4.
    Fonseca, P., Li, C., Singhal, V., Rodrigues, R.: A study of the internal and external effects of concurrency bugs. In: DSN 2010, pp. 221–230 (2010)Google Scholar
  5. 5.
    Fonseca, P., Li, C., Rodrigues, R.: Finding complex concurrency bugs in large multi-threaded applications. In: EuroSys 2011 (2011)Google Scholar
  6. 6.
    Gashi, I., Popov, P., Stankovic, V., Strigini, L.: On designing dependable services with diverse off-the-shelf SQL servers. In: de Lemos, R., Gacek, C., Romanovsky, A. (eds.) Architecting Dependable Systems II. LNCS, vol. 3069, pp. 191–214. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  7. 7.
    Gashi, I., Stankovic, V., Leita, C., Thonnard, O.: An experimental study of diversity with off-the-shelf antivirus engines. In: NCA 2009, pp. 4–11 (2009)Google Scholar
  8. 8.
    Ghosh, S., Kelly, J.L.: Bytecode fault injection for java software. Journal of Systems and Software 81(11), 2034–2043 (2008)CrossRefGoogle Scholar
  9. 9.
    Helal, A.A., Bhargava, B.K., Heddaya, A.A.: Replication techniques in distributed systems. Kluwer Academic Publishers (1996)Google Scholar
  10. 10.
    Jula, H., Tralamazza, D., Zamfir, C., Candea, G.: Deadlock immunity: Enabling systems to defend against deadlocks. In: OSDI 2008 (2008)Google Scholar
  11. 11.
    Kapritsos, M., Wang, Y., Quema, V., Clement, A., Alvisi, L., Dahlin, M.: All about eve: execute-verify replication for multi-core servers. In: OSDI 2012, pp. 237–250 (2012)Google Scholar
  12. 12.
    Lamport, L., Shostak, R., Pease, M.: The byzantine generals problem. ACM Trans. Program. Lang. Syst. 4(3), 382–401 (1982)MATHCrossRefGoogle Scholar
  13. 13.
    Li, Z., Tan, L., Wang, X., Lu, S., Zhou, Y., Zhai, C.: Have things changed now?: an empirical study of bug characteristics in modern open source software. In: Proc. ASID 2006, pp. 25–33 (2006)Google Scholar
  14. 14.
    Lu, S., Park, S., Hu, C., Ma, X., Jiang, W., Li, Z., Popa, R.A., Zhou, Y.: Muvi: automatically inferring multi-variable access correlations and detecting related semantic and concurrency bugs. In: SOSP 2007, pp. 103–116 (2007)Google Scholar
  15. 15.
    Mariano, P., Soares, J., Preguiça, N.: Replicated software components for improved performance. In: InForum 2010, pp. 95–98 (2010)Google Scholar
  16. 16.
    Musuvathi, M., Qadeer, S., Ball, T., Basler, G., Nainar, P.A., Neamtiu, I.: Finding and reproducing heisenbugs in concurrent programs. In: OSDI 2008, pp. 267–280 (2008)Google Scholar
  17. 17.
    Pullum, L.L.: Software fault tolerance techniques and implementation. Artech House, Inc., USA (2001)MATHGoogle Scholar
  18. 18.
    Purtilo, J.M., Jalote, P.: An environment for developing fault-tolerant software. IEEE Trans. Softw. Eng. 17, 153–159 (1991)CrossRefGoogle Scholar
  19. 19.
    Qin, F., Tucek, J., Sundaresan, J., Zhou, Y.: Rx: treating bugs as allergies—a safe method to survive software failures. In: SOSP 2005, pp. 235–248 (2005)Google Scholar
  20. 20.
    Rodrigues, R., Castro, M., Liskov, B.: Base: using abstraction to improve fault tolerance. In: SOSP 2001, pp. 15–28 (2001)Google Scholar
  21. 21.
    Romanovsky, A.: Class diversity support in object-oriented languages. Journal of Systems and Software 48(1), 43–57 (1999)CrossRefGoogle Scholar
  22. 22.
    Sidiroglou, S., Ioannidis, S., Keromytis, A.D.: Band-aid patching. In: HotDep 2007 (2007)Google Scholar
  23. 23.
    Veeraraghavan, K., Chen, P., Flinn, J., Narayanasamy, S.: Detecting and surviving data races using complementary schedules. In: SOSP 2011, pp. 369–384 (2011)Google Scholar
  24. 24.
    Xu, J., Randell, B., Rubira-Calsavara, C., Stroud, R.J.: Toward an object-oriented approach to software fault tolerance. In: Proc. FTPDS 1994, pp. 226–233 (1994)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • João Soares
    • 1
  • João Lourenço
    • 1
  • Nuno Preguiça
    • 1
  1. 1.CITI/DI-FCT-Univ. Nova de LisboaPortugal

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