880
Views
3
CrossRef citations to date
0
Altmetric
Software Quality, Reliability and Security

Theoretical and empirical validation of software trustworthiness measure based on the decomposition of attributes

, &
Pages 1181-1200 | Received 30 Jan 2022, Accepted 29 Mar 2022, Published online: 07 Apr 2022

References

  • Briand, L. C., Emam, K. E., & Morasca, S. (1996). On the application of measurement theory in software engineering. Empirical Software Engineering, 1(1), 61–88. https://doi.org/10.1007/BF00125812
  • Briand, L. C., Morasca, S., & Basili, R. V. (1996). Property-based software engineering measurement. IEEE Transactions on Software Engineering, 22(1), 68–86. https://doi.org/10.1109/32.481535
  • Chen, Y. X., & Tao, H. W. (2019). Software trustworthiness measurement evaluation and enhancement specifications. Science Press.
  • Cho, J. H., Xu, S. H., Hurley, P. M., Mackay, M., Benjamin, T., & Beaumont, M. (2019). STRAM: Measuring the trustworthiness of computer-based systems. ACM Computing Surveys, 51(6), 1–47. https://doi.org/10.1145/3277666
  • Devi, D., Biswas, S. K., & Purkayastha, B. (2019). Learning in presence of class imbalance and class overlapping by using one-class SVM and undersampling technique. Connection Science, 31(2), 105–142. https://doi.org/10.1080/09540091.2018.1560394
  • Ding, S., Yang, S. L., & Fu, C. (2012). A novel evidential reasoning based method for software trustworthiness evaluation under the uncertain and unreliable environment. Expert Systems with Applications, 39(3), 2700–2709. https://doi.org/10.1016/j.eswa.2011.08.127
  • Falcone, R., & Castelfranchi, C. (2002). Issues of trust and control on agent autonomy. Connection Science, 14(4), 249–263. https://doi.org/10.1080/0954009021000068763
  • Fenton, N., & Bieman, J. (2015). Software metrics: A rigorous and practical approach (3rd ed.). CRC Press.
  • Gene, M. A., & Tyler, J. R. (2018, January 3–6). Trustworthiness perceptions of computer code a heuristic-systematic processing model. Proceedings of the 51st Hawaii International Conference on System Sciences, Hilton Waikoloa Village, Hawaii (pp. 5384–5393).
  • Gul, J., & Luo, P. (2019, August 5–8). A unified measurable software trustworthy model based on vulnerability loss speed index. Proceedings of 18th IEEE International Conference on Trust, Security and Privacy in Computing and Communications/13th IEEE International Conference on Big Data Science and Engineering, Rotorua, New Zealand (pp. 18–25).
  • Gupta, S., Aroraa, H. D., Naithania, A., & Chandrab, A. (2021). Reliability assessment of the planning and perception software competencies of self-driving cars. International Journal of Performability Engineering, 17(9), 779–786. https://doi.org/10.23940/ijpe.21.09.p4.779786
  • He, J. F., Shan, Z. G., Wang, J., Pu, G. G., Fang, Y. F., Liu, K., Zhao, R. Z., & Zhang, Z. T. (2018). Review of the achievements of major research plan of trustworthy software. Bulletin of National Natural Science Foundation of China, 32(3), 291–296. https://doi.org/10.16262/j.cnki.1000-8217.2018.03.009
  • Lemes, C. I., Naessens, V., & Vieira, M. (2019, October 28–31). Trustworthiness assessment of web applications: Approach and experimental study using input validation coding practices. Proceedings of IEEE 30th International Symposium on Software Reliability Engineering (ISSRE), Berlin, Germany (pp. 435–445).
  • Lian, S. X., & Tang, M. D. (2022). API recommendation for Mashup creation based on neural graph collaborative filtering. Connection Science, 34(1), 124–138. https://doi.org/10.1080/09540091.2021.1974819
  • Liu, H., Tao, H. W., & Chen, Y. X. (2021). An approach for trustworthy evidence of source code oriented aerospace software trustworthiness measurement. Aerospace Control and Application, 47(2), 32–41. https://doi.org/10.3969/j.issn.1674-1579
  • Maza, S., & Megouas, O. (2021). Framework for trustworthiness in software development. International Journal of Performability Engineering, 17(2), 241–252. https://doi.org/10.23940/ijpe.21.02.p8.241252
  • Medeiros, N., Ivaki, N., Costa, P., & Vieira, M. (2020). Vulnerable code detection using software metrics and machine learning. IEEE Access, 8, 219174–219198. https://doi.org/10.1109/Access.6287639
  • Meneely, A., Smith, B., & Williams, L. (2012). Validating software metrics: A spectrum of philosophies. ACM Transactions on Software Engineering and Methodology, 21(4), 1–28. https://doi.org/10.1145/2377656.2377661
  • Muhammad, D. M. S., Fairul, R. F., Loo, F. A., Nur, F. A., & Norzamzarini, B. (2018). Rating of software trustworthiness via scoring of system testing results. International Journal of Digital Enterprise Technology, 1(1/2), 121–134. https://doi.org/10.1504/IJDET.2018.092637
  • Shi, H. L., Ma, J., & Zou, F. Y. (2008, August 29–September 2). Software dependability evaluation model based on fuzzy theory. Proceedings of International Conference on Computer Science & Information Technology, Singapore (pp. 102–106).
  • Srinivasan, K. P., & Devi, T. (2014). Software metrics validation methodologies in software engineering. International Journal of Software Engineering & Applications, 5(6), 87–102. https://doi.org/10.5121/ijsea
  • Steffen, B., Wilhelm, H., Alexandra, P., Becker, S., Boskovic, M., Dhama, A., Hasselbring, W., Koziolek, H., Lipskoch, H., Meyer, R., Muhle, M., Paul, A., Ploski, J., Rohr, M., Swaminathan, M., Warns, T., & Winteler, D. (2006). Trustworthy software systems: A discussion of basic concepts and terminology. ACM SIGSOFT Software Engineering Notes, 31(6), 1–18.https://doi.org/10.1145/1218776.1218781
  • Tao, H. W., & Chen, Y. X. (2009, September 15–18). A metric model for trustworthiness of softwares. Proceedings of the 2009 IEEE/WIC/ACM International Conference on Web Intelligence and International Conference on Intelligent Agent Technology, Milan, Italy (pp. 69–72).
  • Tao, H. W., & Chen, Y. X. (2012). A new metric model for trustworthiness of softwares. Telecommunication Systems, 51(2-3), 95–105. https://doi.org/10.1007/s11235-011-9420-9
  • Tao, H. W., Chen, Y. X., & Pang, J. M. (2015, May 18). A software trustworthiness measure based on the decompositions of trustworthy attributes and its validation. Proceedings of Industrial Engineering, Management Science and Applications, Tokyo, Japan (pp. 981–990).
  • Tao, H. W., Chen, Y. X., & Wu, H. Y. (2020, December 11–12). Decomposition of attributes oriented software trustworthiness measure based on axiomatic approaches. Proceedings of the 20th IEEE International Conference on Software Quality, Reliability and Security Companion (QRS-C), Macau, China (pp. 308–315).
  • Tao, H. W., & Zhao, J. (2018). Source codes oriented software trustworthiness measure based on validation. Mathematical Problems in Engineering, 2018(3), 1–10.https://doi.org/10.1155/2018/6982821
  • Tian, J. F., & Guo, Y. H. (2020). Software trustworthiness evaluation model based on a behaviour trajectory matrix. Information and Software Technology, 119(1), 106233. https://doi.org/10.1016/j.infsof.2019.106233
  • Wang, B. H., Chen, Y. X., Zhang, S., & Wu, H. Y. (2019). Updating model of software component trustworthiness based on users feedback. IEEE Access, 7, 60199–60205. https://doi.org/10.1109/Access.6287639
  • Wang, H. M. (2018). Harnessing the crowd wisdom for software trustworthiness: Practices in China. Software Engineering Notes, 43(1), 6–11. https://doi.org/10.1145/3178315.3178328
  • Wang, J., Chen, Y. X., Gu, B., Guo, X. Y., Wang, B. H., Jin, S. Y., Xu, J., & Zhang, J. Y. (2015). An approach to measuring and grading software trust for spacecraft software. Scientia Sinica Techologica, 45(2), 221–228. https://doi.org/10.1360/N092014-00479
  • Wong, W. E, Debroy, V., Surampudi, A., Kim, H., & Siok, M. F. (2010, June 9–11). Recent catastrophic accidents: Investigating how software was responsible. Proceedings of the 4th IEEE International Conference on Secure Software Integration and Reliability Improvement (SSIRI), Singapore (pp. 14–22).
  • Wong, W. E, Li, X. L., & Laplante, P. A. (2017). Be more familiar with our enemies and pave the way forward: A review of the roles bugs played in software failures. Journal of Systems and Software, 133(2/3), 68–94. https://doi.org/10.1016/j.jss.2017.06.069
  • Xie, J., Tan, W. A., Yang, Z. B., Li, S. M., Xing, L. Q., & Huang, Z. Q. (2022). SysML-based compositional verification and safety analysis for safety-critical cyber-physical systems. Connection Science, 34(1), 911–941. https://doi.org/10.1080/09540091.2021.2017853
  • Xu, J. L., Xiao, L. J., Li, Y. H., Huang, M. W., Zhuang, Z. C., Weng, T. H., & Liang, W. (2021). NFMF: Neural fusion matrix factorisation for QoS prediction in service selection. Connection Science, 33(3), 753–768. https://doi.org/10.1080/09540091.2021.1889975
  • Yang, X., Jabeen, G., Luo, P., Zhu, X. L., & Liu, M. H. (2018). A unified measurement solution of software trustworthiness based on social-to-software framework. Journal of Computer Science and Technology, 33(3), 603–620. https://doi.org/10.1007/s11390-018-1843-2
  • Zuse, H., & Bollmann-Sdorra, P. (1991, May 5). Measurement theory and software measures. Proceedings of the BCS-FACS Workshop on Formal Aspects of Measurement, South Bank University, London (pp. 219–259).