Skip to main content
SpringerLink
Log in

Tackling visual and conceptual complexity of problem-oriented modeling of requirements

  • Research
  • Published:
Software Quality Journal Aims and scope Submit manuscript

Abstract

In the contemporary age of cyber-physical systems (CPS), where software governs the control, coordination, and management of physical objects to tackle real-world problems, engineering requirements for such systems present considerable challenges. Consequently, it is not surprising that the requirements engineering (RE) community, encompassing both academia and industry, has turned to established RE methodologies and applied them within the context of CPS; notably, Jackson’s Problem Frames (PF) approach deploys problem diagrams for modeling CPS. However, problem diagrams of realistic CPS often present visual and conceptual complexities, which must be addressed before PF can be usefully applied in practice. In this paper, the above problem is addressed in two steps: firstly, preliminary findings are presented by deriving from the application of eye-tracking software in the assessment of a technique designed to mitigate the visual complexity inherent in the CARE (Computer-Aided Requirements Engineering) tool developed for PF. An auto-layout technique is developed for detecting and resolving overlaps, aimed at enhancing its usability from the perspectives of cognition, psychology, and user studies; secondly, the technique of a complexity matrix is applied for calculating and evaluating the conceptual complexity inherent in problem diagrams. Our eye-tracking results show the successful implementation of overlap detection and resolution. The case studies in the second step also demonstrate the applicability and effectiveness of the complexity matrix calculations.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11

Similar content being viewed by others

Data availability

The datasets generated during and/or analyzed during the current study are available from the corresponding author upon request.

References

  • Akiki, P. A., Bandara, A. K., & Yu, Y. (2016). Engineering adaptive model-driven user interfaces. IEEE Transactions on Software Engineering, 42(12), 1118–1147.

    Article  Google Scholar 

  • Al-alshuhai, A., & Siewe F. (2015). An extension of the use case diagram to model context-aware applications. In 2015 SAI Intelligent Systems Conference (IntelliSys). IEEE.

  • Aleryani, A. Y. (2016). Comparative study between data flow diagram and use case diagram. International Journal of Scientific and Research Publications, 6(3), 124–126.

    Google Scholar 

  • Calvary, G., et al. (2003). A unifying reference framework for multi-target user interfaces. Interacting with Computers, 15, 289–308.

    Article  Google Scholar 

  • Carter, B. T., & Luke, S. G. (2020). Best practices in eye tracking research. International Journal of Psychophysiology, 155, 49–62.

    Article  PubMed  Google Scholar 

  • Chen, C. L. T. (2010). Distributed collision detection and resolution.

  • Cheng, B.H., & Atlee J. M. (2007). Research directions in requirements engineering. Future of Software Engineering (FOSE'07) (pp. 285–303).

  • Cheng, S., et al. (2010). Adaptive user interface of product recommendation based on eye-tracking. In Proceedings of the 2010 workshop on Eye gaze in intelligent human machine interaction.

  • Cheng, S., & Liu, Y. (2012). Eye-tracking based adaptive user interface: Implicit human-computer interaction for preference indication. Journal on Multimodal User Interfaces, 5, 77–84.

    Article  Google Scholar 

  • Darwish, A., & Hassanien, A. E. (2018). Cyber physical systems design, methodology, and integration: The current status and future outlook. Journal of Ambient Intelligence and Humanized Computing, 9, 1541–1556.

    Article  Google Scholar 

  • Del Bianco, V., & Lavazza L. (2009). Applying the COSMIC functional size measurement method to problem frames. In 2009 14th IEEE International Conference on Engineering of Complex Computer Systems. IEEE.

  • Deng, Y., Li, Z., & Xiao, H. (2022). Trace4PF: A tool for automated decomposition of problem diagrams with traceability.

  • Esterle, L., & Grosu, R. (2016). Cyber-physical systems: Challenge of the 21st century. e & i Elektrotechnik und Informationstechnik.

  • Harris, P. (2017) What Is User Interface Design?. The Rosen Publishing Group, Inc.

  • Hoffmann, M. W., et al. (2021). Developing industrial cps: A multi-disciplinary challenge. Sensors, 21(6), 1991.

    Article  ADS  PubMed  PubMed Central  Google Scholar 

  • Jackson, M. (2001). Problem frames: Analysing and structuring software development problems. Addison-Wesley.

  • Junaid, W. (2021). Evaluating the effectiveness of problem frames for contextual modeling of cyber-physical systems: A tool suite with adaptive user interfaces, In Evaluation and Assessment in Software Engineering (pp. 284–287).

  • Lavazza, L., & Robiolo, G. (2010). Introducing the evaluation of complexity in functional size measurement: A UML-based approach. In Proceedings of the 2010 ACM-IEEE International Symposium on Empirical Software Engineering and Measurement.

  • Li, Z., Hall, J. G., & Rapanotti, L. (2014). On the systematic transformation of requirements to specifications. Requirements Engineering, 19, 397–419.

    Article  Google Scholar 

  • Liu, G., et al. (2015). CARE: A computer-aided requirements engineering tool for problem-oriented software development. International Journal of Software Engineering and Knowledge Engineering, 25(09n10), 1747–1752.

    Article  Google Scholar 

  • Liu, Z., et al. (2022). Nighthawk: Fully automated localizing UI display issues via visual understanding. IEEE Transactions on Software Engineering, 49(1), 403–418.

    Article  Google Scholar 

  • Longo, L. (2017). Subjective usability, mental workload assessments and their impact on objective human performance. In Human-Computer Interaction - INTERACT 2017. Cham: Springer International Publishing.

  • March, V., et al. (2005). Collision detection and resolution in hierarchical peer-to-peer systems. In The IEEE Conference on Local Computer Networks 30th Anniversary (LCN'05) l. IEEE.

  • McMurrey, D. (2019). Information Structures. Open Technical Communication, 36, 27.

  • Mehta, R. (2004). PFEdit: A graphical editor for problem frame diagrams. Citeseer.

    Google Scholar 

  • Ozkaya, I. (2006). Representing requirement relationships, in First International Workshop on Requirements Engineering. IEEE: Minneapolis, MN, USA.

    Google Scholar 

  • Pelczer, I., Singer, F. M., & Voica, C. (2013). Cognitive framing: A case in problem posing. Procedia-Social and Behavioral Sciences, 78, 195–199.

    Article  Google Scholar 

  • Pobaru, M., & Gokulapriya, R. (2023). Node overlapping detection for draggable node-based applications. In 2023 IEEE International Conference on Contemporary Computing and Communications (InC4). IEEE.

  • Quadri, I., et al. (2015). Modeling methodologies for cyber-physical systems: Research field study on inherent and future challenges. Ada User Journal, 36(4), 246–253.

    Google Scholar 

  • Sabharwal, S., Sibal, R., & Kaur, P. (2014). Deriving complexity metric based on use case diagram and its validation. In 2014 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT). IEEE.

  • Sabharwal, S., Singh, S. K., & Gupta, J. (2011). Deriving system complexity metric from events and its validation. International Journal of Software Engineering and Knowledge Engineering, 21(08), 1097–1121.

    Article  Google Scholar 

  • Silk, E. M., et al. (2021). Problem framing and cognitive style: Impacts on design ideation perceptions. Design Studies, 74, 101015.

    Article  Google Scholar 

  • Törngren, M., & Sellgren, U. (2018). Complexity challenges in development of cyber-physical systems. Principles of modeling: Essays dedicated to Edward A. Lee on the occasion of his 60th birthday (pp. 478–503).

  • Tversky, A., & Kahneman, D. (1981). The framing of decisions and the psychology of choice. Science, 211(4481), 453–458.

    Article  ADS  MathSciNet  CAS  PubMed  Google Scholar 

  • Wang, D. M. -H. (2006). Collision detection and resolution. COEN 396Interactive Multimedia and Game Programming.

  • Winkler, Á. (2007). A new auto-layout algorithm for GUI localization.

  • Yigitbas, E., et al. (2020). Integrated model-driven development of self-adaptive user interfaces. Software and Systems Modeling, 19(5), 1057–1081.

    Article  Google Scholar 

Download references

Funding

The funding is provided by the National Natural Science Foundation of China (62362006), “DuXiu Scholar” Fund, and the Guangxi “Bagui Scholar” Team for Innovation and Research. Zhi Li is with the Guangxi Key Lab of Multi-source Information Mining & Security, and the Key Laboratory of Education Blockchain and Intelligent Technology, Ministry of Education, Guangxi Normal University, Guilin 541004, China.

Author information

Authors and Affiliations

  1. School of Computer Science and Engineering, Guangxi Normal University, Guilin, Guangxi, 541004, People’s Republic of China

    Waqas Junaid & Zhi Li

Authors
  1. Waqas Junaid
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Zhi Li
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

Waqas Junaid made the conceptual design, performed the experiments, and wrote the manuscript. While Zhi Li is the corresponding author validating and verifying the experiments and manuscript. Waqas Junaid conceived of the presented idea, developed the theory, and performed the computations. Waqas Junaid and Zhi Li verified the analytical methods. Zhi Li encouraged Waqas Junaid to investigate the complexity and adaptive user interface and supervised the findings of this work. Waqas Junaid and Zhi Li conceived and planned the experiments and carried out the experiments and also planned and carried out the simulations. Waqas Junaid contributed to the sample preparation. Waqas Junaid and Zhi Li contributed to the interpretation of the results. Waqas Junaid took the lead in writing the manuscript. All authors provided critical feedback and helped shape the research, analysis, and manuscript.

Corresponding author

Correspondence to Zhi Li.

Ethics declarations

Conflict of interest

The author declares no competing interests.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Junaid, W., Li, Z. Tackling visual and conceptual complexity of problem-oriented modeling of requirements. Software Qual J (2024). https://doi.org/10.1007/s11219-024-09662-8

Download citation

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s11219-024-09662-8

Keywords

Search

Navigation