Skip to main content

An Empirical Assessment of Functional Redundancy Semantic Metric

  • Conference paper
  • First Online:
  • 1074 Accesses

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 941))

Abstract

Software dependability is a generic concept that reflects the system’ trustworthiness by its users. It consists of different quality attributes like reliability and maintainability. To achieve dependable and reliable software systems, different dependability means are defined including fault tolerance. Most of fault tolerance techniques are based on the redundancy concept. To reflect the ability of a program to tolerate faults, the quantitative assessment of the program’ redundancy is required. Literature review shows that a set of semantic metrics whose objective is to assess the programs’ redundancy and to reflect their potential to tolerate faults is proposed. Despite the importance of the different metrics composing this suite, literature shows that they are manually computed for procedural programs, and only a theoretical basis of them is presented. Consequently, we aim in this paper to propose a way to automatically compute one of these metrics termed functional redundancy for different object oriented java programs. The automatic computing is necessary required for the different metrics to perform their empirical validation as software quality indicators.

This is a preview of subscription content, log in via an institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

References

  1. Randell, B., Laprie, J.C., Kopetz, H., Littlewood, B. (eds.): Predictably Dependable Computing Systems. Springer, Heidelberg (2013)

    MATH  Google Scholar 

  2. Asghari, S.A., Marvasti, M.B., Rahmani, A.M.: Enhancing transient fault tolerance in embedded systems through an OS task level redundancy approach. Future Gener. Comput. Syst. 87, 58–65 (2018)

    Article  Google Scholar 

  3. Mili, A., Jaoua, A., Frias, M., Helali, R.G.M.: Semantic metrics for software products. Innov. Syst. Softw. Eng. 10(3), 203–217 (2014)

    Article  Google Scholar 

  4. Randell, B.: System structure for software fault tolerance. IEEE Trans. Softw. Eng. 2, 220–232 (1975)

    Article  Google Scholar 

  5. Pullum, L.L.: Software Fault Tolerance Techniques and Implementation. Artech House, Norwood (2001)

    MATH  Google Scholar 

  6. Lyu, M.R.: Handbook of Software Reliability Engineering (1996)

    Google Scholar 

  7. Mili, A., Tchier, F.: Software Testing: Concepts and Operations. Wiley, New York (2015)

    Google Scholar 

  8. Amara, D., Fatnassi, E., Rabai, L.: An automated support tool to compute state redundancy semantic metric. In: International Conference on Intelligent Systems Design and Applications, pp. 262–272. Springer, Cham, December 2017

    Google Scholar 

  9. Avizienis, A., Laprie, J.C., Randell, B., Landwehr, C.: Basic concepts and taxonomy of dependable and secure computing. IEEE Trans. Dependable Secur. Comput. 1(1), 11–33 (2004)

    Article  Google Scholar 

  10. Laprie, J.C.: Dependability: basic concepts and terminology. In: Dependability: Basic Concepts and Terminology, pp. 3–245. Springer, Vienna (1992)

    Chapter  Google Scholar 

  11. Laprie, J.C.: Dependable computing and fault tolerance: concepts and terminology. In: Twenty-Fifth International Symposium on Fault-Tolerant Computing, 1995, p. 2. IEEE, June 1985

    Google Scholar 

  12. Isermann, R.: Fault-Diagnosis Systems: An Introduction from Fault Detection to Fault Tolerance. Springer, Heidelberg (2006)

    Book  Google Scholar 

  13. Dubrova, E.: Fault-Tolerant Design, pp. 55–65. Springer, New York (2013)

    Book  Google Scholar 

  14. Jaoua, A., Mili, A.: The use of executable assertions for error detection and damage assessment. J. Syst. Softw. 12(1), 15–37 (1990)

    Article  Google Scholar 

  15. Carzaniga, A., Mattavelli, A., Pezzè, M.: Measuring software redundancy. In: Proceedings of the 37th International Conference on Software Engineering, vol. 1. pp. 156–166. IEEE Press, May 2015

    Google Scholar 

  16. Fenton, N., Bieman, J.: Software Metrics: A Rigorous and Practical Approach. CRC Press, Boca Raton (2014)

    Book  Google Scholar 

  17. Hamming, R.W.: Error detecting and error correcting codes. Bell Syst. Tech. J. 29(2), 147–160 (1950)

    Article  MathSciNet  Google Scholar 

  18. Shannon, C.E.: A mathematical theory of communication. ACM SIGMOBILE Mob. Comput. Commun. Rev. 5(1), 3–55 (2001)

    Article  MathSciNet  Google Scholar 

  19. Lyu, M.R., Huang, Z., Sze, S.K., Cai, X.: An empirical study on testing and fault tolerance for software reliability engineering. In: 14th International Symposium on Software Reliability Engineering, 2003, ISSRE 2003, pp. 119–130. IEEE, November 2003

    Google Scholar 

  20. Jiang, L., Su, Z.: Automatic mining of functionally equivalent code fragments via random testing. In: Proceedings of the Eighteenth International Symposium on Software Testing and Analysis, pp. 81–92. ACM, July 2009. https://doi.org/10.1145/1572272.1572283

  21. Davis, J.S., LeBlanc, R.J.: A study of the applicability of complexity measures. IEEE Trans. Softw. Eng. 14(9), 1366 (1988)

    Article  Google Scholar 

  22. Yazici, B., Yolacan, S.: A comparison of various tests of normality. J. Stat. Comput. Simul. 77(2), 175–183 (2007). https://doi.org/10.1080/10629360600678310

    Article  MathSciNet  MATH  Google Scholar 

  23. Thadewald, T., Büning, H.: Jarque-Bera test and its competitors for testing normality–a power comparison. J. Appl. Stat. 34(1), 87–105 (2007). https://doi.org/10.1080/02664760600994539

    Article  MathSciNet  MATH  Google Scholar 

  24. Gall, C.S., Lukins, S., Etzkorn, L., Gholston, S., Farrington, P., Utley, D., Virani, S.: Semantic software metrics computed from natural language design specifications. IET Softw. 2(1), 17–26 (2008). https://doi.org/10.1049/iet-sen:20070109

    Article  Google Scholar 

  25. Olague, H.M., Etzkorn, L.H., Gholston, S., Quattlebaum, S.: Empirical validation of three software metrics suites to predict fault-proneness of object-oriented classes developed using highly iterative or agile software development processes. IEEE Trans. Softw. Eng. 33(6), 402–419 (2007). https://doi.org/10.1109/TSE.2007.1015

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Dalila Amara .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Amara, D., Fatnassi, E., Rabai, L. (2020). An Empirical Assessment of Functional Redundancy Semantic Metric. In: Abraham, A., Cherukuri, A., Melin, P., Gandhi, N. (eds) Intelligent Systems Design and Applications. ISDA 2018 2018. Advances in Intelligent Systems and Computing, vol 941. Springer, Cham. https://doi.org/10.1007/978-3-030-16660-1_25

Download citation

Publish with us

Policies and ethics