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MICOSE4aPS: Industrially Applicable Maturity Metric to Improve Systematic Reuse of Control Software

Authors:

Birgit Vogel-Heuser,

Eva-Maria Neumann,

Juliane FischerAuthors Info & Claims

ACM Transactions on Software Engineering and Methodology (TOSEM), Volume 31, Issue 1

Article No.: 5, Pages 1 - 24

https://doi.org/10.1145/3467896

Published: 28 September 2021 Publication History

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Abstract

automated Production Systems (aPS) are highly complex, mechatronic systems that usually have to operate reliably for many decades. Standardization and reuse of control software modules is a core prerequisite to achieve the required system quality in increasingly shorter development cycles. However, industrial case studies in aPS show that many aPS companies still struggle with strategically reusing software. This paper proposes a metric-based approach to objectively measure the maturity of industrial IEC 61131-based control software in aPS (MICOSE4aPS) to identify potential weaknesses and quality issues hampering systematic reuse. Module developers in the machine and plant manufacturing industry can directly benefit as the metric calculation is integrated into the software engineering workflow. An in-depth industrial evaluation in a top-ranked machine manufacturing company in food packaging and an expert evaluation with different companies confirmed the benefit of efficiently managing the quality of control software.

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References

[1]

1061–1992 IEEE Standard for a Software Quality Metrics Methodology. IEEE /Institute of Electrical and Electronics Engineers Incorporated, s.l.

[2]

3S-Smart Software Solutions GmbH. 2019. Data Sheet CODESYS Static Analysis — Product Data Sheet V0.0.0.1.

[3]

Florian Angerer, Herbert Prähofer, Rudolf Ramler, and Friedrich Grillenberger. 2013. Points-to analysis of IEC 61131-3 programs: Implementation and application. In IEEE 18th Conference on Emerging Technologies & Factory Automation (ETFA). IEEE, 1–8.

[4]

Barry C. Arnold. 2015. Pareto distributions second edition (2nd ed.). Chapman & Hall /CRC Monographs on Statistics & Applied Probability. Taylor and Francis, Hoboken.

[5]

Elvira M. Arvanitou, Apostolos Ampatzoglou, Alexander Chatzigeorgiou, Matthias Galster, and Paris Avgeriou. 2017. A mapping study on design-time quality attributes and metrics. JSS 127, 52–77.

Digital Library

[6]

Nathaniel Ayewah, William Pugh, David Hovemeyer, J. D. Morgenthaler, and John Penix. 2008. Using static analysis to find bugs. IEEE Software 25, 5 (2008), 22–29.

Digital Library

[7]

Giacomo Barbieri, Nicola Battilani, and Cesare Fantuzzi. 2015. A PackML-based design pattern for modular PLC code. IFAC-PapersOnLine 48, 10 (2015), 178–183.

[8]

Beckhoff Automation GmbH & Co. KG. 2019. Manual TC3 PLC Static Analysis.

[9]

Iwan Binanto, Harco L. Hendric Spits Warnars, Bahtiar S. Abbas, and Nesti F. Sianipar. 2018. Automation processing Halstead metrics application's results. In Indonesian Association for Pattern Recognition International Conference (INAPR). IEEE, 1–4.

[10]

Dimitri Bohlender, Hendrik Simon, Nico Friedrich, Stefan Kowalewski, and Stefan Hauck-Stattelmann. 2016. Concolic test generation for PLC programs using coverage metrics. In IEEE 13th International Workshop on Discrete Event Systems (WODES), Piscataway, NJ, 432–437.

[11]

Safa Bougouffa, Sebastian Diehm, Michael Schwarz, and Birgit Vogel-Heuser. 2017. Scalable cloud based semantic code analysis to support continuous integration of industrial PLC code. In IEEE 15th International Conference on Industrial Informatics (INDIN), 621–627.

[12]

G. A. Campbell, Patroklos P. Papapetrou, and Olivier Gaudin. 2014. SonarQube in action. Manning, Shelter Island.

Digital Library

[13]

Lorena Capitán and Birgit Vogel-Heuser. 2017. Metrics for software quality in automated production systems as an indicator for technical debt. In IEEE 13th IEEE Conference on Automation Science and Engineering (CASE). IEEE, 709–716.

Digital Library

[14]

Wenbin W. Dai, Valeriy Vyatkin, and James H. Christensen. 2013. Essential elements for programming of distributed automation and control systems. In IEEE 18th Conference on Emerging Technologies & Factory Automation (ETFA), 1–8.

[15]

Tom DeMarco. 1986. Controlling software projects: Management, measurement, and estimates.

Digital Library

[16]

Rickard Elsen, Inggriani Liem, and Saiful Akbar. 2016. Software versioning quality parameters: Automated assessment tools based on the parameters. In International Conference on Data and Software Engineering (ICoDSE). IEEE, 1–6.

[17]

Sascha El-Sharkawy, Nozomi Yamagishi-Eichler, and Klaus Schmid. 2019. Metrics for analyzing variability and its implementation in software product lines: A systematic literature review. Information and Software Technology 106, 1–30.

Digital Library

[18]

Emelie Engström and Per Runeson. 2011. Decision support for test management and scope selection in a software product line context. In 2011 IEEE Fourth International Conference on Software Testing, Verification and Validation Workshops. IEEE, 262–265.

Digital Library

[19]

Alexander Fay, Birgit Vogel-Heuser, Timo Frank, Karin Eckert, Thomas Hadlich, and Christian Diedrich. 2015. Enhancing a model-based engineering approach for distributed manufacturing automation systems with characteristics and design patterns. JSS 101, 221–235.

Digital Library

[20]

Stefan Feldmann, Florian Hauer, Sebastian Ulewicz, and Birgit Vogel-Heuser. 2016. Analysis framework for evaluating PLC software: An application of semantic web technologies. In IEEE 25th International Symposium on Industrial Electronics (ISIE). IEEE, 1048–1054.

[21]

Juliane Fischer, Safa Bougouffa, Alexander Schlie, Ina Schaefer, and Birgit Vogel-Heuser. 2018. A qualitative study of variability management of control software for industrial automation systems. IEEE International Conference on Software Maintenance and Evolution (ICSME), 615–624.

[22]

M. Fischer, M. Pinzger, and H. Gall. 2003. Populating a release history database from version control and bug tracking systems. In IEEE International Conference on Software Maintenance (ICSM). IEEE Computer Society, 23–32.

Digital Library

[23]

H. Gall, M. Jazayeri, and J. Krajewski. 2003. CVS release history data for detecting logical couplings. In IEEE 6th International Workshop on Principles of Software Evolution. IEEE, 13–23.

Digital Library

[24]

Gui Gui and Paul D. Scott. 2007. Ranking reusability of software components using coupling metrics. JSS 80, 9 (2007), 1450–1459.

Digital Library

[25]

Maurice H. Halstead. 1977. Elements of software science (7th). Elsevier Computer Science Library: Operational Programming Systems Series. Elsevier, New York.

Digital Library

[26]

S. Henry and D. Kafura. 1981. Software structure metrics based on information flow. IIEEE Trans. Software Eng. SE-7, 5, 510–518.

Digital Library

[27]

Youssef A. Houaich and Mustapha Belaissaoui. 2015. Measuring the maturity of open source software. In 6th International Conference on Information Systems and Economic Intelligence (SIIE). IEEE, 133–140.

[28]

ANSI/ISA-88.00.01. 2010. Batch control - Part 1: Models and terminology.

[29]

ISO/IEC 25010:2011-03. 2011. Systems and software engineering --- Systems and software Quality Requirements and Evaluation (SQuaRE) --- System and software quality models.

[30]

Itris Automation Square. 2017. PLC Checker Data Sheet - Automatic analysis of PLC programs quality.

[31]

Karl H. John and Michael Tiegelkamp. 2010. IEC 61131-3: Programming industrial automation systems. Springer, Berlin.

Digital Library

[32]

Stephen C. Johnson, Ed. 1977. Lint, a C program checker. Bell Telephone Laboratories, Murray Hill.

[33]

Stamatis Karnouskos, Roopak Sinha, Paulo Leitao, Luis Ribeiro, and Thomas. I. Strasser. 2018. The Applicability of ISO/IEC 25023 measures to the integration of agents and automation systems. In 44th Annual Conference of the IEEE Industrial Electronics Society (IECON). IEEE, 2927–2934.

[34]

Krista M. Kcskemety, Zachary Dix, and Benjamin Kott. 2018. Examining software design projects in a first-year engineering course: The impact of the project type on programming complexity and programming. In IEEE Frontiers in Education Conference (FIE), 1–5.

Digital Library

[35]

Lov Kumar, Raoul Jetley, and Ashish Sureka. 2016. Source code metrics for programmable logic controller (PLC) ladder diagram (LD) visual programming language. In 7th International Workshop on Emerging Trends in Software Metrics (WETSoM). IEEE Computer Society, Conference Publishing Services; The Association for Computing Machinery, 15–21.

Digital Library

[36]

Lov Kumar and Ashish Sureka. 2017. Using structured text source code metrics and artificial neural networks to predict change proneness at code tab and program organization level. In 10th Innovations in Software Engineering Conference. ICPS: ACM International Conference Proceeding series. ACM, 172–180.

Digital Library

[37]

A. Lüder, A. Klostermeyer, J. Peschke, A. Bratoukhine, and T. Sauter. 2005. Distributed automation: PABADIS versus HMS. IEEE Trans. Ind. Inf 1, 1 (2005), 31–38.

[38]

Camelia R. Maga, Nasser Jazdi, and Peter Göhner. 2011. Reusable models in industrial automation: Experiences in defining appropriate levels of granularity. 18th World Congress - The International Federation of Automatic Control 44, 9145–9150.

[39]

T. J. McCabe. 1976. A complexity measure. IEEE Transactions on Software Engineering 4, 308–320.

Digital Library

[40]

Nachiappan Nagappan, Andreas Zeller, Thomas Zimmermann, Kim Herzig, and Brendan Murphy. 2010. Change bursts as defect predictors. In IEEE 21st International Symposium on Software Reliability Engineering (ISSRE). IEEE Computer Society, 309–318.

Digital Library

[41]

Anil Nair. 2012. Product metrics for IEC 61131-3 languages. In IEEE 17th Conference on Emerging Technologies & Factory Automation (ETFA). IEEE, 1–8.

[42]

Martin Obermeier, Steven Braun, and Birgit Vogel-Heuser. 2015. A model-driven approach on object-oriented PLC programming for manufacturing systems with regard to usability. IEEE Transactions on Industrial Informatics 11, 3 (2015), 790–800.

[43]

Marcio F. Oliveira, Ricardo M. Redin, Luigi Carro, Lu Lamb, and Fl Wagner. 042008. Software quality metrics and their impact on embedded software. In 2008 5th International Workshop on Model-based Methodologies for Pervasive and Embedded Software. IEEE, 68–77.

Digital Library

[44]

Herbert Prähofer, Florian Angerer, Rudolf Ramler, and Friedrich Grillenberger. 2017. Static code analysis of IEC 61131-3 programs: Comprehensive tool support and experiences from large-scale industrial application. IEEE TII 13, 1 (2017), 37–47.

[45]

Herbert Prähofer, Florian Angerer, Rudolf Ramler, Hermann Lacheiner, and Friedrich Grillenberger. 2012. Opportunities and challenges of static code analysis of IEC 61131-3 programs. In IEEE 17th Conference on Emerging Technologies & Factory Automation (ETFA). IEEE, 1–8.

[46]

Ralf Reussner, Michael Goedicke, Wilhelm Hasselbring, Birgit Vogel-Heuser, Jan Keim, and Lukas Märtin. 2019. Managed software evolution. Springer International Publishing, Cham.

[47]

J. Rosenberg. 1997. Some misconceptions about lines of code. In IEEE Fourth International Software Metrics Symposium. IEEE Comput. Soc, 137–142.

Digital Library

[48]

George Rzevski. 2003. On conceptual design of intelligent mechatronic systems. Mechatronics 13, 1029–1044.

[49]

Hendrik Simon and Stefan Kowalewski. 2016. Static analysis of sequential function charts using abstract interpretation. In IEEE 21st International Conference on Emerging Technologies & Factory Automation (ETFA). IEEE, 1–4.

Digital Library

[50]

Miroslaw Staron, Wilhelm Meding, Christoffer Hoglund, Peter Eriksson, Jimmy Nilsson, and Jorgen Hansson. 2013. Identifying implicit architectural dependencies using measures of source code change waves. In IEEE 39th EUROMICRO Conference on Software Engineering and Advanced Applications (SEAA). IEEE Computer Society, Conference Publishing Services, 325–332.

Digital Library

[51]

Kleanthis Thramboulidis. 2010. The 3+1 SysML view-model in model integrated mechatronics. JSEA 03, 02 (2010), 109–118.

[52]

Birgit Vogel-Heuser, Alexander Fay, Ina Schaefer, and Matthias Tichy. 2015. Evolution of software in automated production systems: Challenges and research directions. JSS 110 (2015), 54–84.

Digital Library

[53]

Birgit Vogel-Heuser, Juliane Fischer, Stefan Feldmann, Sebastian Ulewicz, and Susanne Rösch. 2017. Modularity and architecture of PLC-based software for automated production systems: An analysis in industrial companies. JSS 131, 35–62.

Digital Library

[54]

Birgit Vogel-Heuser, Juliane Fischer, Eva-Maria Neumann, and Sebastian Diehm. 2018. Key maturity indicators for module libraries for PLC-based control software in the domain of automated production systems. IFAC-PapersOnLine 51, 11 (2018), 1610–1617.

[55]

Birgit Vogel-Heuser, Juliane Fischer, Susanne Rösch, Stefan Feldmann, and Sebastian Ulewicz. 2015. Challenges for maintenance of PLC-software and its related hardware for automated production systems: Selected industrial case studies. In IEEE International Conference on Software Maintenance and Evolution (ICSME). IEEE, 362–371.

Digital Library

[56]

Birgit Vogel-Heuser and Felix Ocker. 2018. Maintainability and evolvability of control software in machine and plant manufacturing — An industrial survey. CEP 80, 157–173.

[57]

Birgit Vogel-Heuser, Susanne Rösch, Juliane Fischer, Thomas Simon, Sebastian Ulewicz, and Jens Folmer. 2016. Fault handling in PLC-based industry 4.0 automated production systems as a basis for restart and self-configuration and its evaluation. JSEA 09, 01 (2016), 1–43.

[58]

Sophia Voulgaropoulou, Georgios Spanos, and Lefteris Angelis. 2012. Analyzing measurements of the R statistical open source software. In IEEE 35th Annual Software Engineering Workshop (SEW). IEEE, 1–10.

Digital Library

[59]

Jan Wilch, Juliane Fischer, Eva-Maria Neumann, Sebastian Diehm, Michael Schwarz, Eric Lah, Matthias Wander, and Birgit Vogel-Heuser. 2019. Introduction and evaluation of complexity metrics for network-based, graphical IEC 61131-3 programming languages. In IEEE Annual Conference of the IEEE Industrial Electronics Society (IECON), 253–259.

Digital Library

[60]

Ian Wright and Albert Ziegler. 2019. The standard coder: A machine learning approach to measuring the effort required to produce source code change. In IEEE/ACM 7th International Workshop on Realizing Artificial Intelligence Synergies in Software Engineering (RAISE). IEEE, 1–7.

Digital Library

Cited By

Wang YVogel-Heuser BNeumann EGnadlinger MWen ZWilch JRupprecht B(2024)Change Categories Based on Mutable Artifacts in PLC Control Software Projects2024 IEEE 7th International Conference on Industrial Cyber-Physical Systems (ICPS)10.1109/ICPS59941.2024.10639988(1-7)Online publication date: 12-May-2024
https://doi.org/10.1109/ICPS59941.2024.10639988
Dong QVogel-Heuser BNeumann E(2023)Semi-automatic assessment of lack of control code documentation in automated production systemsat - Automatisierungstechnik10.1515/auto-2022-014671:8(670-689)Online publication date: 8-Aug-2023
https://doi.org/10.1515/auto-2022-0146
Vogel-Heuser BNeumann EFischer J(2022)Maturity Levels for Automation Software Engineering in automated Production Systems2022 IEEE 20th International Conference on Industrial Informatics (INDIN)10.1109/INDIN51773.2022.9976112(618-623)Online publication date: 25-Jul-2022
https://doi.org/10.1109/INDIN51773.2022.9976112
Show More Cited By

Index Terms

MICOSE4aPS: Industrially Applicable Maturity Metric to Improve Systematic Reuse of Control Software
1. Software and its engineering
  1. Software creation and management
    1. Software post-development issues
      1. Maintaining software
  2. Software organization and properties
    1. Extra-functional properties

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Published In

cover image ACM Transactions on Software Engineering and Methodology

ACM Transactions on Software Engineering and Methodology Volume 31, Issue 1

January 2022

665 pages

ISSN:1049-331X

EISSN:1557-7392

DOI:10.1145/3481711

Editor:
Mauro Pezzè
USI Università della Svizzera italiana and SIT Schaffhausen Institute of Technology

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Copyright © 2021 Association for Computing Machinery.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Publication History

Published: 28 September 2021

Accepted: 01 May 2021

Revised: 01 April 2021

Received: 01 July 2020

Published in TOSEM Volume 31, Issue 1

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Cited By

Wang YVogel-Heuser BNeumann EGnadlinger MWen ZWilch JRupprecht B(2024)Change Categories Based on Mutable Artifacts in PLC Control Software Projects2024 IEEE 7th International Conference on Industrial Cyber-Physical Systems (ICPS)10.1109/ICPS59941.2024.10639988(1-7)Online publication date: 12-May-2024
https://doi.org/10.1109/ICPS59941.2024.10639988
Dong QVogel-Heuser BNeumann E(2023)Semi-automatic assessment of lack of control code documentation in automated production systemsat - Automatisierungstechnik10.1515/auto-2022-014671:8(670-689)Online publication date: 8-Aug-2023
https://doi.org/10.1515/auto-2022-0146
Vogel-Heuser BNeumann EFischer J(2022)Maturity Levels for Automation Software Engineering in automated Production Systems2022 IEEE 20th International Conference on Industrial Informatics (INDIN)10.1109/INDIN51773.2022.9976112(618-623)Online publication date: 25-Jul-2022
https://doi.org/10.1109/INDIN51773.2022.9976112
Neumann EVogel-Heuser BGnadlinger MFischer JReimoser LDiehm SEnglert TSchwarz M(2022)Metric-based Identification of Target Conflicts in the Development of Industrial Automation Software Libraries2022 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)10.1109/IEEM55944.2022.9989691(1493-1499)Online publication date: 7-Dec-2022
https://doi.org/10.1109/IEEM55944.2022.9989691
Vogel-Heuser BNeumann EFischer JMarcos MEstevez EBarbieri GSonnleithner LRabiser R(2022)Automation Software Architecture in CPPS - Definition, Challenges and Research Potentials2022 IEEE 5th International Conference on Industrial Cyber-Physical Systems (ICPS)10.1109/ICPS51978.2022.9816893(01-08)Online publication date: 24-May-2022
https://doi.org/10.1109/ICPS51978.2022.9816893

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