Integrated Modeling in the Quality Assessment of Flight Management Software Systems
Abstract
Ensuring the high quality of Flight Management Systems (FMS) software is a critical task given the increasing, demands for accuracy, reliability, and safety in aviation transportation. Modern FMS quality assessment methods often fail to account for the complexity of dynamic changes and interactions between system components. Objective – to develop an integrated quality assessment model for FMS that incorporates a comprehensive approach to analyzing system characteristics, including functionality, reliability, performance, security, and process transparency. Methodology – the study is based on the use of integrated modeling, which enables the combination of various evaluation criteria and their adaptation to real-world
operational conditions. The proposed Integrated Quality Model (IQM) is based on a multi-criteria aggregation function that combines key quality dimensions—functionality, reliability, performance, security, and transparency – in accordance with ISO/IEC 25010 and DO-178C. The IQM framework enables quantitative
benchmarking, yielding a total quality score of 0.871 for the Jeppesen Crew Management (JCM) system, which exceeds the average for comparable FMS solutions such as Sabre Airline Solutions and ARINC Direct. The assessment highlighted the system’s strengths in performance, transparency, and security,
while also identifying areas for improvement, particularly in user interface interactivity and adaptation mechanisms. Conclusions confirm the effectiveness of integrated modeling for FMS quality assessment. Future research may focus on enhancing adaptive algorithms and implementing predictive analytics methods
to optimize flight management. Compared with traditional checklists and static MCDM scorecards, IQM explicitly models cross-dimension interactions and supports context-adaptive weighting, clarifying its novelty and practical advantage.
Full Text:
PDFReferences
Alsheikh, R. S., Fadel, E. A., & Akkari, N. T. (2024). Distributed software-defined networking management. Aro-the Scientific Journal of Koya University, 12(2), 157–166.
[https://doi.org/10.14500/aro.11468]
Arrighini, M., Zecchi, L., & Volta, M. (2023). Integrated modelling assessment of low carbon and air quality plan synergies. IFAC-PapersOnLine, 56(2), 8308–8313. [https://doi.org/10.1016/j.ifacol.2023.10.1019]
Blaschinskaya, O., & Patrushev, K. (2023). Integrated environmental quality assessment. Bulletin of the Angarsk State Technical University, 1(17), 174–177. [https://doi.org/10.36629/2686-777x-2023-1-17-174-177]
Bonchev, M. (2024). Educational methodology in software systems. Innovative STEM Education, 6(1), 281–309. https://doi.org/10.55630/stem.2024.0630
Di Ruscio, D., Iovino, L., & Pierantonio, A. (2023). AMINO: A quality assessment framework for modeling ecosystems. Journal of Software: Evolution and Process. [https://doi.org/10.1002/smr.2603]
Fang, Y., Li, Z., Yan, J., Sui, X., & Liu, H. (2023). Study of spatio-temporal modeling in video quality assessment. IEEE Transactions on Image Processing, 1. [https://doi.org/10.1109/tip.2023.3272480]
Haber, А. А., Haber, V. S., & Mazur, E. О. (2024). Software quality management. Key title: Zbìrnik naukovih pracʹ Odesʹkoï deržavnoï akademìï tehnìčnogo regulûvannâ ta âkostì, (1(24)), 13–17. [https://doi.org/10.32684/2412-5288-2024-1-24-13-17]
Koi-Akrofi, G. Y., Tanye, H., Quist, S. C., Koi- Akrofi, J., Gaisie, E., Agangiba, M., & Yeboah, D. (2024). Towards a software quality factor assessment model for learning management systems (LMS). Indian Journal of Science and Technology, 17(23), 2463–2468. [https://doi.org/10.17485/ijst/v17i23.1006]
Mahmood, W., Çalıklı, G., Strüber, D., Lämmel, R., Mukelabai, M., & Berger, T. (2024). Virtual platform: Effective and seamless variability management for software systems. IEEE Transactions on Software Engineering, 1–31. [https://doi.org/10.1109/tse.2024.3406224]
Masood, M. U., Rashid, M., Haider, S., Naz, I., Pande, C. B., Heddam, S., Alshehri, F., Elkhrachy, I., Ahsan, A., & Sammen, S. S. (2023). Exploring groundwater quality assessment: A geostatistical and integrated water quality indices perspective. Water, 16(1), 138. [https://doi.org/10.3390/w16010138]
Mock, M. (2023). The quality assessment of integrated reporting: A structured literature review. Journal of Business Management, 21, 22–47. [https://doi.org/10.32025/jbm23001
Naumann, P., & Sands, T. (2024). Micro-Satellite systems design, integration, and flight. Micromachines, 15(4), 455. [https://doi.org/10.3390/mi15040455]
Tanasa, I., Cazacu, M., & Sluser, B. (2023). Air quality integrated assessment: Environmental impacts, risks and human health hazards. Applied Sciences, 13(2), 1222. [https://doi.org/10.3390/app13021222]
Verani, A., Rienzo, R. D., Nicodemo, N., Baronti, F., Roncella, R., & Saletti, R. (2024). Open hardware/software modular battery emulator for battery management systems development and functional testing. IEEE Access, 1. [https://doi.org/10.1109/access.2024.3413187]
Zajdel, A., Welcer, M., & Szczepanski, C. J. (2024). Initial flight test verification of software and hardware in the loop simulations of the flight stabilization system. Aircraft Engineering and Aerospace Technology. [https://doi.org/10.1108/aeat-04-2023-0115]
DOI: https://doi.org/10.31449/inf.v49i31.11012
This work is licensed under a Creative Commons Attribution 3.0 License.