Abstract
Successful system evolution is dependent on knowledge about the system itself, its past and its present, as well as the environment of the system. This chapter presents several approaches to automate the acquisition of knowledge about the system’s past, for example past evolution steps, and its present, for example models of its behaviour. Based on these results, further approaches support the validation and verification of evolution steps, as well as the recommendation of evolutions to the system, as well as similar systems. The approaches are illustrated using the joint automation production system case study, the Pick and Place Unit (PPU) and Extended Pick and Place Unit (xPPU).
Chapter PDF
Similar content being viewed by others
References
C. Aldrich and Lidia Auret.Unsupervised process monitoring and fault diagnosis with machine learning methods. Advances in computer vision and pattern recognition. London, New York: Springer, 2013.isbn: 1447151852.
Ayman Amin, A Colman, and Lars Grunske. “An Approach to Forecasting QoS Attributes of Web Services Based on ARIMA and GARCH Models”. In:Proceedings of the IEEE 19th International Conference on Web Services (ICWS 2012). IEEE, June 2012, pp. 74–81.https://doi.org/10.1109/ICWS.2012.37.
A. Amin, L. Grunske, and A. Colman. “An automated approach to forecasting QoS attributes based on linear and non-linear time series modeling”. In:Proceedings of the 27th IEEE/ACM International Conference on Automated Software Engineering (ASE 2012) IEEE, Sept. 2012, pp. 130–139.https://doi.org/10.1145/2351676.2351695.
Kerstin Altmanninger et al. “Why model versioning research is needed!? an experience report”. In:Proceedings of the MoDSE-MCCM 2009 Workshop@ MoDELS Vol. 9. 2009.
Thorsten Arendt et al. “Henshin: Advanced Concepts and Tools for In-Place EMF Model Transformations”. In:MoDELS 2010. 2010, pp. 121–135.https://doi.org/10.1007/978-3-642-16145-2_9.
L. V. Allen and D. M. Tilbury. “Anomaly Detection Using Model Generation for Event-Based Systems Without a Preexisting Formal Model”. In:Systems, Man and Cybernetics, Part A: Systems and Humans, IEEE Transactions on42.3 (2012), pp. 654–668.issn: 1083–4427.https://doi.org/10.1109/TSMCA.2011.2170418.
Luca Bassi et al. “A SysML-based methodology for manufacturing machinery modeling and design”. In:IEEE/ASME transactions on mechatronics16.6 (2011), pp. 1049–1062.
Lars Bendix and Pär Emanuelsson. “Diff and merge support for model based development”. In:Proceedings of the 2008 international workshop on Comparison and versioning of software models. ACM. 2008, pp. 31–34.
Marcel Bruch, Martin Monperrus, and Mira Mezini. “Learning from examples to improve code completion systems”. In:Proceedings of the the 7th joint meeting of the European software engineering conference and the ACM SIGSOFT symposium on The foundations of software engineering. ACM. 2009, pp. 213–222.
Monica Bellgran and Kristina Säfsten.Production development: Design and operation of production systems. London: Springer, 2010.isbn: 9781848824959.
Radu Calinescu et al. “Adaptive model learning for continual verification of nonfunctional properties”. In:ACM/SPEC Int. Conference on Performance Engineering. ACM, 2014, pp. 87–98.https://doi.org/10.1145/2568088.2568094.
Radu Calinescu, Kenneth Johnson, and Yasmin Rafiq. “Using observation ageing to improve markovian model learning in QoS engineering”. In:Second WOSP/SIPEW Int. Conference on Performance Engineering. ACM, 2011, pp. 505–510.https://doi.org/10.1145/1958746.1958823.
Ilenia Epifani, Carlo Ghezzi, and Giordano Tamburrelli. “Change-point detection for black-box services”. In:Proceedings of the 18th ACM SIGSOFT Int. Symposium on Foundations of Software Engineering. ACM, 2010, pp. 227–236.
Pär Emanuelsson. “There is a strong need for diff/merge tools on models”. In:Softwaretechnik-Trends 32.4 (2012), pp. 30–31.
Ilenia Epifani et al. “Model Evolution by Run-time Parameter Adaptation”. In: IEEE International Conference on Software Engineering. Washington, DC, USA: IEEE Computer Society, 2009, pp. 111–121.isbn: 978-1-4244-3453-4.url:http://dx.doi.org/10.1109/ICSE.2009.5070513.
G. Frey and L. Litz. “Formal methods in PLC programming”. In:IEEE International Conference on Systems, Man, and Cybernetics. 2000.https://doi.org/10.1109/ICSMC.2000.884356.
Sabrina Förtsch and Bernhard Westfechtel. “Differencing and merging of software diagrams state of the art and challenges”. In:Intl. Conf. Software and Data Technologies (ICSOFT). 2007.
J. Huselius and J. Andersson. “Model synthesis for real-time systems”. In:Ninth European Conference on Software Maintenance and Reengineering. 2005, pp. 52–60.
Robert Heinrich et al. “Architecture-based change impact analysis in cross-disciplinary automated production systems”. In:Journal of Systems and Software146 (2018), pp. 167–185.issn: 0164–1212.doi:https://doi.org/10.1016/j.jss.2018.08.058.
S. Hashtrudi Zad, R. H. Kwong, and W. M. Wonham. “Fault diagnosis in discreteevent systems: framework and model reduction”. In:IEEE Transactions on Automatic Control 48.7 (2003), pp. 1199–1212.https://doi.org/10.1109/TAC.2003.814099.
J. Huselius et al. “Automatic Generation and Validation of Models of Legacy Software”. In:IEEE International Conference on Embedded and Real-Time Computing Systems and Applications. 2006.https://doi.org/10.1109/RTCSA.2006.19.
Rolf Isermann.Fault-Diagnosis Systems: An Introduction from Fault Detection to Fault Tolerance. Berlin and Heidelberg: Springer-Verlag Berlin Heidelberg, 2006.isbn: 3540241124.url:http://dx.doi.org/10.1007/3-540-30368-5.
Timo Kehrer et al. “Understanding model evolution through semantically lifting model diffierences with SiLift”. In:28th IEEE International Conference on Software Maintenance (ICSM), Trento, Italy. IEEE. 2012, pp. 638–641.
Timo Kehrer et al. “Generating Edit Operations for Profiled UML Models”. In:Proceedings of the Workshop on Models and Evolution (ME) co-located with ACM/IEEE 16th International Conference on Model Driven Engineering Languages and Systems (MoDELS), Miami, FL, USA. Vol. 1090. CEURWorkshop Proceedings. 2013, pp. 30–39.
Timo Kehrer et al. “Automatically deriving the specification of model editing operations from meta-models”. In:International Conference on Theory and Practice of Model Transformations. Springer. 2016, pp. 173–188.
Timo Kehrer. “Calculation and propagation of model changes based on user-level edit operations”. In:A Foundation for Version and Variant Management in Modeldriven Engineering (Doctoral Dissertation, Universität Siegen). Siegen, Germany (2015).
Timo Kehrer, Udo Kelter, and Gabriele Taentzer. “Integrating the Specification and Recognition of Changes in Models”. In:Softwaretechnik-Trends 32.2 (2012), pp. 41–42.
Timo Kehrer, Udo Kelter, and Gabriele Taentzer. “Consistency-preserving edit scripts in model versioning”. In:2013 IEEE/ACM 28th International Conference on Automated Software Engineering (ASE). Nov. 2013, pp. 191–201.https://doi.org/10.1109/ASE.2013.6693079.
Sandro Koch. “Automatische Vorhersage von Änderungsausbreitungen am Beispiel von Automatisierungssystemen”. MA thesis. Karlsruhe Institute of Technology (KIT), 2017.
Jochen M Küster et al. “Detecting and resolving process model differences in the absence of a change log”. In:International Conference on Business Process Management. Springer. 2008, pp. 244–260.
J. Ladiges et al. “Learning Behaviour Models of Discrete Event Production Systems from Observing Input/Output Signals”. In:IFAC/IEEE/IFIP/IFORS Symposium on Information Control Problems in Manufacturing (INCOM). 2015.
Jan Ladiges et al. “Learning Material Flow Models for Manufacturing Plants from Data Traces”. In:IEEE International Conference on Industrial Informatics (INDIN). 2015.
D. Lefebvre and E. Leclercq. “Stochastic Petri Net Identification for the Fault Detection and Isolation of Discrete Event Systems”. In:IEEE Transactions on Systems, Man and Cybernetics, Part A: Systems and Humans41.2 (2011), pp. 213–225.https://doi.org/10.1109/TSMCA.2010.2058102.
Na Meng, Miryung Kim, and Kathryn S McKinley. “LASE: locating and applying systematic edits by learning from examples”. In: Proceedings of the 2013 International Conference on Software Engineering. IEEE Press. 2013, pp. 502–511.
Philip Morris, Marcelo Masera, and Marc Wilikens. “Requirements engineering and industrial uptake”. In:Requirements Engineering3.2 (1998), pp. 79–83.issn: 1432-010X.url:http://dx.doi.org/10.1007/BF02919966.
Kıvanç Muşlu et al. “Speculative analysis of integrated development environment recommendations”. In:ACM SIGPLAN Notices47.10 (2012), pp. 669–682.
Manuel Ohrndorf et al. “ReVision: A Tool for History-based Model Repair Recommendations”. In:IEEE International Conference on Software Engineering. ACM,2018.
Christopher Pietsch et al. “SiPL–A Delta-Based Modeling Framework for Software Product Line Engineering”.In: Automated Software Engineering (ASE), 2015 30th IEEE/ACM International Conference on. IEEE. 2015, pp. 852–857.
Christopher Pietsch et al. “A tool environment for quality assurance of deltaoriented model-based SPLs”. In:Proceedings of the Eleventh International Workshop on Variability Modelling of Software-intensive Systems. ACM. 2017, pp. 84–91.
Klaus Pohl and Chris Rupp.Requirements Engineering Fundamentals - A Study Guide for the Certified Professional for Requirements Engineering Exam: Foundation Level - IREB compliant. rockynook, 2011, pp. I–XVIII, 1–163.isbn: 978-1-933952-81-9.
M. Roth, J.-J Lesage, and L. Litz. “Black-box identification of discrete event systems with optimal partitioning of concurrent subsystems”. In:American Control Conference (ACC). 2010.
Kiana Rostami et al. “Architecture-based Assessment and Planning of Change Requests”. In:11th International ACM SIGSOFT Conference on Quality of Software Architectures (QoSA ’15). Montréal, QC, Canada: ACM, 2015, pp. 21–30.isbn: 9781450334709.https://doi.org/10.1145/2737182.2737198.url:http://dl.acm.org/citation.cfm?doid=2737182.2737198.
Thomas Ruhroth et al. “Versioning and Evolution Requirements for Model-Based System Development”. In:Softwaretechnik-Trends 34.2 (2014). ISSN 0720–8928.
Petri Selonen. “A review of UML model comparison approaches”. In:Nordic Workshop on Model Driven Engineering. Citeseer. 2007, p. 37.
Daniel Strüber et al. “Henshin: A Usability-Focused Framework for EMF Model Transformation Development”. In:Graph Transformation - 10th International Conference, ICGT 2017, Held as Part of STAF 2017, Marburg, Germany, July 18–19, 2017, Proceedings. Vol. 10373. Lecture Notes in Computer Science. Springer, 2017, pp. 196–208.
Wilhelm Schäfer and Heike Wehrheim. “Model-Driven Development with Mechatronic UML”. In:Graph Transformations and Model-Driven Engineering: Essays Dedicated to Manfred Nagl on the Occasion of his 65th Birthday. Ed. by Gregor Engels et al. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010, pp. 533–554.isbn: 978-3-642-17322-6.url:https://doi.org/10.1007/978-3-642-17322-6_23.
Gabriele Taentzer et al. “Change-Preserving Model Repair”. In:International Conference on Fundamental Approaches to Software Engineering. Springer. 2017, pp. 283–299.
Kleanthis Thramboulidis. “Overcoming mechatronic design challenges: the 3+ 1 SysML-view model”. In:Computing Science and Technology International Journal 1.1 (2013), pp. 6–14.
Birgit Vogel-Heuser et al. “Selected challenges of software evolution for automated production systems”. In:Industrial Informatics (INDIN), 2015 IEEE 13th International Conference on. IEEE. 2015, pp. 314–321.
Birgit Vogel-Heuser et al. “Maintenance effort estimation with KAMP4aPS for cross-disciplinary automated Production Systems - a collaborative approach”. In:20th IFAC World Congress. Toulouse, France, 2017.
Tao Zheng, C. Murray Woodside, and Marin Litoiu. “Performance Model Estimation and Tracking Using Optimal Filters”. In:IEEE Trans. Softw. Eng. 34.3 (2008), pp. 391–406.https://doi.org/10.1109/TSE.2008.30.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Open Access This chapter is licensed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
The images or other third party material in this chapter are included in the chapter's Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the chapter's Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.
Copyright information
© 2019 The Author(s)
About this chapter
Cite this chapter
Kögel, S. et al. (2019). Learning from Evolution for Evolution. In: Reussner, R., Goedicke, M., Hasselbring, W., Vogel-Heuser, B., Keim, J., Märtin, L. (eds) Managed Software Evolution. Springer, Cham. https://doi.org/10.1007/978-3-030-13499-0_10
Download citation
DOI: https://doi.org/10.1007/978-3-030-13499-0_10
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-13498-3
Online ISBN: 978-3-030-13499-0
eBook Packages: Computer ScienceComputer Science (R0)