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A New Fuzzy Analytic Hierarchy Process Method for Software Trustworthiness Measurement

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1657))

Abstract

Software trustworthiness measurement becomes a focus in software companies. In software trustworthiness measurement, traditional Analytic Hierarchy Process (shortly, AHP) is usually utilized to estimate software attributes’ weights. However, the traditional AHP method only supports using definite numerical values and cannot quantify well decision makers’ opinions on software attributes. By using interval-valued intuitionistic fuzzy set, a new method is proposed in this study based on the traditional AHP for software trustworthiness measurement. In the proposed method, an equation for calculating correlation coefficients between interval-valued intuitionistic fuzzy matrices is designed in order to characterize similarities among decision makers’ opinions, and a parameter of threshold is introduced to select correlation coefficients for decision makers’ weights calculation. Besides, an equation for calculating attribute weights is designed based on harmonic mean in order to stand out levels of attribute importance. The proposed method is experimented in a task of evaluating the resilience of an operating system, and it is compared to the other two classical methods. Our experimental results show that the proposed method produces attribute weights with great differences, and its ability is stronger in the aspect of describing decision makers’ opinions.

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Notes

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References

  1. Wong, W.E., Li, X., Laplante, P.A.: Be more familiar with our enemies and pave the way forward: a review of the roles bugs played in software failures. J. Syst. Softw. 133, 68–94 (2017)

    Article  Google Scholar 

  2. He, J., et al.: Review of the achievements of major research plan of trustworthy software. Sci. Found. China 32(3), 291–296 (2018)

    Google Scholar 

  3. Maza, S., Megouas, O.: Framework for trustworthiness in software development. Int. J. Perform. Eng. 17(2), 241–252 (2021)

    Article  Google Scholar 

  4. Saaty, T.L.: A scaling method for priorities in hierarchical structures. J. Math. Psychol. 15(3), 234–281 (1977)

    Article  MathSciNet  MATH  Google Scholar 

  5. Di Angelo, L., Di Stefano, P., Fratocchi, L., Marzola, A.: An AHP-based method for choosing the best 3D scanner for cultural heritage applications. J. Cult. Herit. 34, 109–115 (2018)

    Article  Google Scholar 

  6. Ishizaka, A., Pearman, C., Nemery, P.: AHPSort: an AHP-based method for sorting problems. Int. J. Prod. Res. 50(17), 4767–4784 (2012)

    Article  Google Scholar 

  7. Tao, H.: Research on the measurement models of software trustworthiness based on attributes. Doctor, East China Normal University, Shanghai, China, April 2011

    Google Scholar 

  8. Wang, B.: Research on trustworthiness measurement models based on software component. Doctor, East China Normal University, Shanghai, China, October 2019

    Google Scholar 

  9. Kahraman, C., Cebeci, U., Ulukan, Z.: Multi-criteria supplier selection using fuzzy AHP. Logist. Inf. Manag. 16(6), 382–394 (2003)

    Article  Google Scholar 

  10. Wang, T.C., Chen, Y.H.: Applying consistent fuzzy preference relations to partnership selection. Omega 35(4), 384–388 (2007)

    Article  Google Scholar 

  11. Deng, H.: Multicriteria analysis with fuzzy pairwise comparison. Int. J. Approx. Reason. 21(3), 215–231 (1999)

    Article  Google Scholar 

  12. van Laarhoven, P., Pedrycz, W.: A fuzzy extension of Saaty’s priority theory. Fuzzy Sets Syst. 11(1–3), 229–241 (1983)

    Article  MathSciNet  MATH  Google Scholar 

  13. Chang, D.Y.: Applications of the extent analysis method on fuzzy AHP. Eur. J. Oper. Res. 95(3), 649–655 (1996)

    Article  MATH  Google Scholar 

  14. Peng, G., Han, L., Liu, Z., Guo, Y., Yan, J., Jia, X.: An application of fuzzy analytic hierarchy process in risk evaluation model. Front. Psychol. 12, 715003 (2021)

    Article  Google Scholar 

  15. Tan, R., Aviso, K., Huelgas, A., Promentilla, M.: Fuzzy AHP approach to selection problems in process engineering involving quantitative and qualitative aspects. Process Saf. Environ. Prot. 92(5), 467–475 (2014)

    Article  Google Scholar 

  16. Atanassov, K.T.: Intuitionistic fuzzy sets. Fuzzy Sets Syst. 20(1), 87–96 (1986)

    Article  MATH  Google Scholar 

  17. Atanassov, K., Gargov, G.: Interval valued intuitionistic fuzzy sets. Fuzzy Sets Syst. 31(3), 343–349 (1989). https://doi.org/10.1007/978-3-7908-1870-3_2

    Article  MathSciNet  MATH  Google Scholar 

  18. Atanassov, K.T.: Operators over interval valued intuitionistic fuzzy sets. Fuzzy Sets Syst. 64(2), 159–174 (1994)

    Article  MathSciNet  MATH  Google Scholar 

  19. Hong, D.H.: A note on correlation of interval-valued intuitionistic fuzzy sets. Fuzzy Sets Syst. 95(1), 113–117 (1998)

    Article  MathSciNet  MATH  Google Scholar 

  20. Xu, Z.S., Chen, J.: An overview of distance and similarity measures of intuitionistic fuzzy sets. Int. J. Uncertain. Fuzziness Knowl.-Based Syst. 16(04), 529–555 (2008)

    Article  MathSciNet  MATH  Google Scholar 

  21. Xu, Z.: Methods for aggregating interval-valued intuitionistic fuzzy information and their application to decision making. Control Decis. 22(2), 215–219 (2007)

    Google Scholar 

  22. Abdullah, L., Najib, L.: A new preference scale MCDM method based on interval-valued intuitionistic fuzzy sets and the analytic hierarchy process. Soft. Comput. 20(2), 511–523 (2016). https://doi.org/10.1007/s00500-014-1519-y

    Article  Google Scholar 

  23. Büyüközkan, G., Göçer, F.: An extension of ARAS methodology under interval valued intuitionistic fuzzy environment for digital supply chain. Appl. Soft Comput. 69, 634–654 (2018)

    Article  Google Scholar 

  24. Jia, Z., Zhang, Y.: Interval-valued intuitionistic fuzzy multiple attribute group decision making with uncertain weights. Math. Probl. Eng. 2019, 1–9 (2019)

    MathSciNet  MATH  Google Scholar 

  25. Zadeh, L.: Fuzzy sets. Inf. Control 8(3), 338–353 (1965)

    Article  MATH  Google Scholar 

  26. Gorzałczany, M.B.: A method of inference in approximate reasoning based on interval-valued fuzzy sets. Fuzzy Sets Syst. 21(1), 1–17 (1987)

    Article  MathSciNet  MATH  Google Scholar 

  27. Park, D.G., Kwun, Y.C., Park, J.H., Park, I.Y.: Correlation coefficient of interval-valued intuitionistic fuzzy sets and its application to multiple attribute group decision making problems. Math. Comput. Model. 50(9–10), 1279–1293 (2009)

    Article  MathSciNet  MATH  Google Scholar 

  28. Saaty, T.L.: The Analytic Hierarchy Process: Planning, Priority Setting, Resource Allocation. McGraw-Hill International Book Co, New York (1980)

    MATH  Google Scholar 

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Acknowledgement

This work is supported by the East China Normal University - Huawei Trustworthiness Innovation Center and the Shanghai Trusted Industry Internet Software Collaborative Innovation Center.

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Correspondence to Yixiang Chen .

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Yue, Z., Yao, X., Chen, Y. (2022). A New Fuzzy Analytic Hierarchy Process Method for Software Trustworthiness Measurement. In: Chen, Y., Zhang, S. (eds) Artificial Intelligence Logic and Applications. AILA 2022 2022. Communications in Computer and Information Science, vol 1657. Springer, Singapore. https://doi.org/10.1007/978-981-19-7510-3_18

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  • DOI: https://doi.org/10.1007/978-981-19-7510-3_18

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-19-7509-7

  • Online ISBN: 978-981-19-7510-3

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