Abstract
This paper introduces an ongoing PhD work that focuses on the design of a multi-agent system that would assess software maintainability in collaboration with human developers. Evaluation of the maintainability is difficult to implement on actual industrial projects as specific criteria cannot be easily adapted to the context of a project, and metrics are not always relevant to the architectural pattern in use. The metrics can be bypassed without improving the quality of the source code. We have the ambition to tackle this problem through a more modular, flexible and dynamic assessment system that will ultimately evolve through a dialogic interaction with the development team. Our approach will first lay the foundations of a shared vocabulary between the artificial agents and the human team. We will further develop a multi-agent system first by introducing feedback from the human team and second by moving towards a real dialogic interaction.
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References
Aniche, M.F., Oliva, G.A., Gerosa, M.A.: What do the asserts in a unit test tell us about code quality? A study on open source and industrial projects. In: Cleve, A., Ricca, F., Cerioli, M. (eds.) 17th European Conference on Software Maintenance and Reengineering, CSMR 2013, Genova, Italy, 5–8 March 2013, pp. 111–120. IEEE Computer Society (2013). https://doi.org/10.1109/CSMR.2013.21
Baggen, R., Correia, J.P., Schill, K., Visser, J.: Standardized code quality benchmarking for improving software maintainability. Softw. Qual. J. 20(2), 287–307 (2012). https://doi.org/10.1007/s11219-011-9144-9
Bakota, T., Hegedüs, P., Kortvelyesi, P., Ferenc, R., Gyimóthy, T.: A probabilistic software quality model. In: IEEE 27th International Conference on Software Maintenance, ICSM 2011, Williamsburg, VA, USA, 25–30 September 2011, pp. 243–252. IEEE Computer Society (2011). https://doi.org/10.1109/ICSM.2011.6080791
Boehm, B.W., Brown, J.R., Lipow, M.: Quantitative evaluation of software quality. In: Yeh, R.T., Ramamoorthy, C.V. (eds.) Proceedings of the 2nd International Conference on Software Engineering, San Francisco, California, USA, 13–15 October 1976, pp. 592–605. IEEE Computer Society (1976). http://dl.acm.org/citation.cfm?id=807736
Gilpin, L.H., Bau, D., Yuan, B.Z., Bajwa, A., Specter, M., Kagal, L.: Explaining explanations: an overview of interpretability of machine learning. http://arxiv.org/abs/1806.00069v3
Gordieiev, O., Kharchenko, V.S., Fominykh, N., Sklyar, V.V.: Evolution of software quality models in context of the standard ISO 25010. In: Zamojski, W., Mazurkiewicz, J., Sugier, J., Walkowiak, T., Kacprzyk, J. (eds.) Proceedings of the Ninth International Conference on Dependability and Complex Systems DepCoS-RELCOMEX, 30 June–4 July 2014, Brunów, Poland, Advances in Intelligent Systems and Computing, vol. 286, pp. 223–232. Springer (2014)
Guidotti, R., Monreale, A., Ruggieri, S., Turini, F., Pedreschi, D., Giannotti, F.: A survey of methods for explaining black box models. http://arxiv.org/abs/1802.01933
Kitchenham, B.A.: What’s up with software metrics? - A preliminary mapping study. J. Syst. Softw. 83(1), 37–51 (2010). https://doi.org/10.1016/j.jss.2009.06.041
Mäntylä, M., Lassenius, C.: Subjective evaluation of software evolvability using code smells: an empirical study. Empirical Softw. Eng. 11(3), 395–431 (2006). https://doi.org/10.1007/s10664-006-9002-8
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Bertrand, S., Favier, PA., André, JM. (2021). Pragmatic Software Maintainability Management Using a Multi-agent System Working in Collaboration with the Development Team. In: RodrÃguez González, S., et al. Distributed Computing and Artificial Intelligence, Special Sessions, 17th International Conference. DCAI 2020. Advances in Intelligent Systems and Computing, vol 1242. Springer, Cham. https://doi.org/10.1007/978-3-030-53829-3_21
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DOI: https://doi.org/10.1007/978-3-030-53829-3_21
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