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Deriving Successful Factors for Practical AI System Development Projects Using Assurance Case

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Knowledge-Based Software Engineering: 2018 (JCKBSE 2018)

Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 108))

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Abstract

In this research, we considered projects to develop systems that use AI technologies including machine learning techniques for office environment. In many AI system development projects, both developers and users need to be involved in order to reach a consensus on discussion items before starting a project. To facilitate this, we propose a method of assessing an AI system development project by using an assurance case based on quality sub-characteristics of functionality to derive project success factors.

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References

  1. Berntsson-Svensson, R., Aurum, A.: Successful software project and products: an empirical investigation. In: Proceedings of the 26th ACM/IEEE International Symposium on Empirical Software Engineering, pp. 144–153 (2006)

    Google Scholar 

  2. Quichiz, L.P., Oré, S.B.: It demand management in organizations: a review. In: Proceedings of the 18th International Conference on Computer Modeling and Simulation, pp. 95–99 (2017)

    Google Scholar 

  3. Chen, H.M., Kazman, R., Haziyev, S.: Strategic prototyping for developing big data systems. IEEE Softw. 33(2), 36–43 (2016)

    Article  Google Scholar 

  4. Kim, M., Zimmermann, T., DeLine, R., Begel, A.: The emerging role of data scientists on software development teams. In: Proceedings of the 38th International Conference on Software Engineering, pp. 96–107 (2016)

    Google Scholar 

  5. Song, I.Y., Zhu, Y.: Big data and data science: what should we teach? Expert Syst. 33(4), 364–373 (2016)

    Article  Google Scholar 

  6. Wang, X., Mylopoulos, J., Guizzardi, G.: How software changes the world: the role of assumptions. In: Proceedings of the 10th IEEE International Conference on Research Challenges in Information Science, pp. 1–12 (2016)

    Google Scholar 

  7. Kelly, T., McDermid, J.A.: Safety case construction and reuse using patterns. In: Proceedings of the 16th International Conference on Computer Safety, Reliability and Security, pp. 55–69 (1997)

    Google Scholar 

  8. Kelly, T., Weaver, R.: The goal structuring notation – a safety argument notation. In: Proceedings of Dependable Systems and Networks Workshop on Assurance Cases (2004)

    Google Scholar 

  9. Yamamoto, S., Matsuno, Y.: An evaluation of argument patterns to reduce pitfalls of applying assurance case. In: Proceedings of the 1st International Workshop on Assurance Cases for Software-Intensive Systems (ASSURE), pp. 12–17 (2013)

    Google Scholar 

  10. Doss, O., Kelly, T.: Addressing the 4+1 software safety assurance principles within scrum. In: Proceedings of the Scientific Workshop Proceedings of XP2016, pp. 17:1–17:5 (2016)

    Google Scholar 

  11. Bloomfield, R., Bishop, P., Butler, E., Netkachova, K.: Using an assurance case framework to develop security strategy and policies. In: Proceedings of the International Conference on Computer Safety, Reliability, and Security, pp. 27–38 (2017)

    Google Scholar 

  12. Sklyar, V., Kharchenko, V.: Challenges in assurance case application for industrial IoT. In: Proceedings of the 9th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems, pp. 736–739 (2017)

    Google Scholar 

  13. Boness, K., Finkelstein, A., Harrison, R.: A method for assessing confidence in requirements analysis. Inf. Softw. Technol. 53(10), 1084–1096 (2011)

    Article  Google Scholar 

  14. Kaneko, T., Yamamoto, S., Tanaka, H.: CC-case based on system development life-cycle process. In: Proceedings of the International Conference on Computer Security and Digital Investigation (COMSEC), pp. 29–35 (2014)

    Google Scholar 

  15. Varkoi, T., Nevalainen, R., Mäkinen, T.: Process assessment in a safety domain. In: Proceedings of the 10th International Conference on the Quality of Information and Communications Technolgy, pp. 52–58 (2016)

    Google Scholar 

  16. Sternberg, R.J.: Successful Intelligence: How Practical and Creative Intelligence Determines Success in Life. Simon & Schuster (1996)

    Google Scholar 

  17. ISO/IEC TR 9126: Software engineering - product quality (2000)

    Google Scholar 

  18. Djouab, R., Bari, M.: An ISO 9126 based quality model for the e-learning systems. Int. J. Inf. Educ. Technol. 6(5), 370–375 (2016)

    Google Scholar 

  19. Yamamoto, S.: A continuous approach to improve it management. In: Proceedings of the International Conference on Enterprise Information Systems (CENTERIS), pp. 27–35 (2017)

    Google Scholar 

  20. Yamamoto, S.: Assuring security through attribute GSN. In: Proceedings of the 5th International Conference on IT Convergence and Security (CIITCS), pp. 1–5 (2015)

    Google Scholar 

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Author information

Authors and Affiliations

  1. Musashi University, Tokyo, Japan

    Hironori Takeuchi

  2. IBM Japan, Ltd., Tokyo, Japan

    Shiki Akihara

  3. Nagoya University, Nagoya, Japan

    Shuichiro Yamamoto

Authors
  1. Hironori Takeuchi
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  2. Shiki Akihara
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  3. Shuichiro Yamamoto
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Corresponding author

Correspondence to Hironori Takeuchi .

Editor information

Editors and Affiliations

  1. Department of Informatics, University of Piraeus, Piraeus, Greece

    Maria Virvou

  2. Nippon Institute of Technology, Miyashiro, Japan

    Fumihiro Kumeno

  3. Department of Informatics, Ionian University, Corfu, Greece

    Konstantinos Oikonomou

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Takeuchi, H., Akihara, S., Yamamoto, S. (2019). Deriving Successful Factors for Practical AI System Development Projects Using Assurance Case. In: Virvou, M., Kumeno, F., Oikonomou, K. (eds) Knowledge-Based Software Engineering: 2018. JCKBSE 2018. Smart Innovation, Systems and Technologies, vol 108. Springer, Cham. https://doi.org/10.1007/978-3-319-97679-2_3

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