Abstract
Mechatronic on-site technicians are responsible for maintenance and thus adequate testing of automated production systems. Hence, they must derive test cases from the IEC 61131-3 control code, which requires systematic testing skills. But despite the industry’s high demand for such skills, testing is not established in mechatronic apprentices’ educational curriculum. For the design of a teaching strategy for mechatronic apprentices on testing, this paper investigates the impact of the IEC 61131-3 language on test case design and evaluation. Comparing Sequential Function Chart (SFC) and Function Block Diagram, a trend towards SFC in apprentices’ self-perceived and real competence is shown.
Kurzzusammenfassung
Mechatroniker sind für die Wartung und den Test automatisierter Produktionssysteme zuständig. Dafür müssen sie adäquate Testfälle aus dem IEC 61131-3 Steuerungscode ableiten, was ein systematisches Vorgehen erfordert. Die dafür dringend notwendige Testkompetenz ist in den Lehrplänen für Mechatroniker jedoch nicht verankert. Dieser Beitrag untersucht für die Entwicklung einer Testen-Lehrstrategie für Mechatronik-Auszubildende den Einfluss der IEC 61131-3-Sprache auf Testfallentwurf und – evaluierung. Die von den Auszubildenen wahrgenommene als auch tatsächliche Testkompetenz ist beim Vergleich von Ablaufsprache (SFC) und Funktionsbausteinsprache (FBD) im Fall von SFC besser.
About the authors
Kathrin Land received an M.Sc. in Electrical Engineering from the University of Stuttgart in 2017. She is pursuing a Ph.D. at the Institute of Automation and Information Systems at TUM. Her main research interests include model-based testing of automated production systems, test case management, and test education.
Univ.-Prof. Dr.-Ing. Birgit Vogel-Heuser received a Diploma degree in Electrical Engineering and a Ph.D. in Mechanical Engineering from RWTH Aachen. Since 2009, she has been full professor and director of the Insititute of Automation and Information Systems at the Technical University of Munich (TUM). Her current research focuses on systems and software engineering. She is a member of the acatech (German National Academy of Science and Engineering), editor of IEEE T-ASE, and IEEE Fellow and member of the science board of MIRMI at TUM.
-
Research ethics: Not applicable.
-
Author contributions: The authors have accepted responsibility for the entire content of this manuscript and approved its submission.
-
Competing interests: The authors state no conflict of interest.
-
Research funding: None declared.
-
Data availability: The raw data can be obtained on request from the corresponding author.
References
[1] V. Vyatkin, “Software engineering in industrial automation: state-of-the-art review,” IEEE Trans. Ind. Inf., vol. 9, no. 3, pp. 1234–1249, 2013. https://doi.org/10.1109/tii.2013.2258165.Search in Google Scholar
[2] B. Vogel-Heuser, A. Fay, I. Schaefer, and M. Tichy, “Evolution of software in automated production systems: challenges and research directions,” J. Syst. Software, vol. 110, pp. 54–84, 2015, https://doi.org/10.1016/j.jss.2015.08.026.Search in Google Scholar
[3] V. Garousi, M. Felderer, C. M. Karapıçak, and U. Yılmaz, “Testing embedded software: a survey of the literature,” Inf. Software Technol., vol. 104, pp. 14–45, 2018, https://doi.org/10.1016/j.infsof.2018.06.016.Search in Google Scholar
[4] D. Bohlender, H. Simon, N. Friedrich, S. Kowalewski, and S. Hauck-Stattelmann, “Concolic test generation for PLC programs using coverage metrics,” in IFAC WODES, 2016, pp. 432–437.10.1109/WODES.2016.7497884Search in Google Scholar
[5] E. Enoiu, A. Čaušević, T. Ostrand, E. Weyuker, D. Sundmark, and P. Pettersson, “Automated test generation using model checking: an industrial evaluation,” Int. J. Software Tool. Technol. Tran., vol. 18, pp. 335–353, 2016, https://doi.org/10.1007/s10009-014-0355-9.Search in Google Scholar
[6] S. Ulewicz and B. Vogel-Heuser, “Increasing system test coverage in production automation systems,” Control Eng. Pract., vol. 73, no. 1, pp. 171–185, 2018. https://doi.org/10.1016/j.conengprac.2018.01.010.Search in Google Scholar
[7] E. Jee, S. Kim, S. Cha, and I. Lee, “Automated test coverage measurement for reactor protection system software implemented in function block diagram,” Lect. Notes Comput. Sci., vol. 6351, pp. 223–236, 2010.10.1007/978-3-642-15651-9_17Search in Google Scholar
[8] B. Vogel-Heuser, M. Obermeier, S. Braun, K. Sommer, F. Jobst, and K. Schweizer, “Evaluation of a UML-based versus an IEC 61131-3-based software engineering approach for teaching PLC programming,” IEEE Trans. Educ., vol. 56, no. 3, pp. 329–335, 2012. https://doi.org/10.1109/te.2012.2226035.Search in Google Scholar
[9] A. Bandura, “Guide for constructing self-efficacy scales,” in Self-Efficacy Beliefs of Adolescents, F. M. Pajares and T. Urdan, Eds., Greenwich, Information Age Publishing, 2006, pp. 307–337.Search in Google Scholar
[10] L. Baartman and L. Ruijs, “Comparing students’ perceived and actual competence in higher vocational education,” Assess Eval. High Educ., vol. 36, no. 4, pp. 385–398, 2011. https://doi.org/10.1080/02602938.2011.553274.Search in Google Scholar
[11] S. Eldh, “On technical debt in software testing – observations from industry,” Lect. Notes Comput. Sci., vol. 13702, pp. 301–323, 2022.10.1007/978-3-031-19756-7_17Search in Google Scholar
[12] M. Aniche, F. Hermans, and A. van Deursen, “Pragmatic software testing education,” in ACM SIGCSE’19, 2019, pp. 414–420.10.1145/3287324.3287461Search in Google Scholar
[13] M. Mladenović, S. Mladenovic, and Ž. Žanko, “Impact of used programming language for K-12 students’ understanding of the loop concept,” Int. J. Technol. Enhanc. Learn., vol. 12, no. 1, pp. 79–98, 2019. https://doi.org/10.1504/ijtel.2020.103817.Search in Google Scholar
[14] Y. Tashtoush, Z. Odat, I. Alsmadi, and M. Yatim, “Impact of programming features on code readability,” Int. J. Software Eng. Appl., vol. 7, no. 6, pp. 441–458, 2013. https://doi.org/10.14257/ijseia.2013.7.6.38.Search in Google Scholar
[15] F. Fronchetti, et al.., “Language impact on productivity for industrial end users: a case study from programmable logic controllers,” J. Comput. Lang., vol. 69, pp. 2590–1184, 2022, https://doi.org/10.1016/j.cola.2021.101087.Search in Google Scholar
[16] H. Zhu, P. Hall, and J. May, “Software unit test coverage and adequacy,” ACM Comput. Surv., vol. 29, no. 4, pp. 366–427, 1997. https://doi.org/10.1145/267580.267590.Search in Google Scholar
[17] M. Aniche, C. Treude, and A. Zaidman, “How developers engineer test cases: an observational study,” IEEE Trans. Software Eng., vol. 48, no. 12, p. 1, 2021. https://doi.org/10.1109/tse.2021.3129889.Search in Google Scholar
[18] IEC, “IEC 61131-3 programmable controllers – part 3: programming languages,” in IEC Std, 2013.Search in Google Scholar
[19] L. Hao, J. Shi, T. Su, and Y. Huang, “Automated test generation for IEC 61131-3 ST programs via dynamic symbolic execution,” in 2019 International Symposium on Theoretical Aspects of Software Engineering (TASE), 2019, pp. 200–207. https://doi.org/10.1109/TASE.2019.00004.10.1109/TASE.2019.00004Search in Google Scholar
[20] K. Doganay, M. Bohlin, and O. Sellin, “Search-based testing of embedded systems implemented in IEC 61131-3: an industrial case study,” in IEEE ICST, 2013, pp. 425–432.10.1109/ICSTW.2013.78Search in Google Scholar
[21] I. Buzhinsky, V. Ulyantsev, J. Veijalainen, and V. Vyatkin, “Evolutionary approach to coverage testing of IEC 61499 function block applications,” in IEEE INDIN, 2015, pp. 1213–1218.10.1109/INDIN.2015.7281908Search in Google Scholar
[22] J. Lawrence, S. Clarke, M. Burnett, and G. Rothermel, “How well do professional developers test with code coverage visualizations? An empirical study,” in IEEE VL/HCC’05, 2005, pp. 53–60.Search in Google Scholar
[23] S. Berner, R. Weber, and R. K. Keller, “Enhancing software testing by judicious use of code coverage information,” in IEEE ICSE, 2007, pp. 612–620.10.1109/ICSE.2007.34Search in Google Scholar
[24] A. Rahmani, J. L. Min, and A. Maspupah, “An evaluation of code coverage adequacy in automatic testing using control flow graph visualization,” in IEEE ISCAIE, 2020, pp. 239–244.10.1109/ISCAIE47305.2020.9108838Search in Google Scholar
[25] D. Ribeiro, R. Lima, C. Franca, A. Souza, I. Silva, and G. Pinto, “Understanding self-efficacy in software engineering industry: an interview study,” in ACM EASE, 2023.10.1145/3593434.3593467Search in Google Scholar
[26] J. Carver and N. Kraft, “Evaluating the testing ability of senior-level computer science students,” in IEEE CSEE&T, 2011, pp. 169–178.10.1109/CSEET.2011.5876084Search in Google Scholar
[27] S. Edwards and Z. Shams, “Comparing test quality measures for assessing student-written tests,” in ACM ICSE, 2014, pp. 354–363.10.1145/2591062.2591164Search in Google Scholar
[28] W. Sheikh, “Teaching C++ programming using automated unit testing and test-driven development—design and efficacy study,” Comput. Appl. Eng. Educ., vol. 30, no. 3, pp. 821–851, 2022. https://doi.org/10.1002/cae.22488.Search in Google Scholar
© 2024 Walter de Gruyter GmbH, Berlin/Boston
