Abstract
This paper introduces Malwa, a web-based tool implementing our new method of learnability by design that is designed to significantly reduce the main entry hurdle, the design of learning alphabets, for lifelong learning of web applications. Technically, Malwa is based on iHTML, a domain-specific extension of HTML, tailored to instrument the web services’ code in a fashion that releases the quality assurance team from defining any learning alphabet. In fact, deterministic, instrumented, purely client-side web applications can be learned out of the box. Learnability by design is a typical ‘left-shift-technology’: The effort of learning alphabet design is shifted to the GUI-developer. This makes sense for two reasons: She (1) knows the intended interactions points and the way to implement them and (2) has the required technological background. The paper illustrates the impact of learnability by design via a Malwa-based case study. Malwa will be made open source-available for replication, experimentation, and extension.
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References
Aarts, F., Heidarian, F., Vaandrager, F.: A theory of history dependent abstractions for learning interface automata. In: Koutny, M., Ulidowski, I. (eds.) CONCUR 2012. LNCS, vol. 7454, pp. 240–255. Springer, Heidelberg (2012). https://doi.org/10.1007/978-3-642-32940-1_18
Aarts, F., et al.: Generating models of infinite-state communication protocols using regular inference with abstraction. Form. Methods Syst. Des. 46(1), 1–41 (2015). ISSN: 0925-9856, https://doi.org/10.1007/s10703-014-0216-x
Hartig, P., Osmani, A., Sorhus, S., Sawchuk, S.: TodoMVC (2024). http://web.archive.org/web/20080207010024/http://www.808multimedia.com/winnt/kernel.htm. Visited 22 Jan 2024
Bainczyk, A.: Simplicity-oriented lifelong learning of web applications. Dissertation. Technische Universität Dortmund, January 2024. https://doi.org/10.17877/DE290R-24274
Bainczyk, A., Steffen, B., Howar, F.: Lifelong learning of reactive systems in practice. In: Ahrendt, W. et al. (eds.) The Logic of Software. A Tasting Menu of Formal Methods - Essays Dedicated to Reiner Hähnle on the Occasion of His 60th Birthday. LNCS, vol. 13360, pp. 38–53. Springer, Cham (2022). https://doi.org/10.1007/978-3-031-08166-8_3
Bainczyk, A., et al.: ALEX: mixed-mode learning of web applications at ease. In: Margaria, T., Steffen, B. (eds.) Leveraging Applications of Formal Methods, Verification and Validation: Discussion, Dissemination, Applications - 7th International Symposium, ISoLA 2016, Imperial, Corfu, Greece, 10–14 October 2016, Proceedings, Part II, pp. 655–671. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-47169-3_51
Bainczyk, A., et al.: Model-based testing without models: the TodoMVC case study. In: Katoen, J.-P., Langerak, R., Rensink, A. (eds.) ModelEd, TestEd, TrustEd: Essays Dedicated to Ed Brinksma on the Occasion of His 60th Birthday, pp. 125–144. Springer, Cham (2017). ISBN: 978-3-319-68270-9, https://doi.org/10.1007/978-3-319-68270-9_7
Banerjee, S.: A survey on Software as a service (SaaS) using quality model in cloud computing, May 2014
Bollig, B., et al.: Learning communicating automata from MSCs. IEEE Trans. Softw. Eng. 36(3), 390–408 (2010). https://doi.org/10.1109/TSE.2009.89
Bollig, B., et al.: libalf: the automata learning framework. English. In: Touili, T., Cook, B., Jackson, P. (eds.) Computer Aided Verification. LNCS, vol. 6174, pp. 360–364. Springer, Cham (2010). ISBN: 978-3-642-14294-9, https://doi.org/10.1007/978-3-642-14295-6_32
Bollig, B., et al.: Replaying play in and play out: synthesis of design models from scenarios by learning, pp. 435–450, March 2007. ISBN: 978-3-540-71208-4, https://doi.org/10.1007/978-3-540-71209-1_33
Bollig, B., et al.: SMA—the Smyle Modeling Approach. In: Huzar, Z., et al. (eds.) Software Engineering Techniques, pp. 103–117. Springer, Heidelberg (2011). ISBN: 978-3-642-22386-0
Bollig, B., et al.: Smyle: a tool for synthesizing distributed models from scenarios by learning. In: van Breugel, F., Chechik, M. (eds.) CONCUR 2008 - Concurrency Theory, pp. 162–166. Springer, Heidelberg (2008). ISBN: 978-3-540-85361-9, https://doi.org/10.1007/978-3-540-85361-9_15
Cassel, S., et al.: Active learning for extended finite state machines. Formal Aspects Comput. 28(2), 233–263 (2016). https://doi.org/10.1007/s00165-016-0355-5
Dinca, I., Ipate, F., Stefanescu, A.: Model learning and test generation for Event-B decomposition. In: Margaria, T., Steffen, B. (eds.) Proceedings of the 5th International Conference on Leveraging Applications of Formal Methods, Verification and Validation: Technologies for Mastering Change - Volume Part I, ISoLA 2012, Heraklion, Crete, Greece. Springer, Cham (2012). ISBN: 978-3-642-34025-3, https://doi.org/10.1007/978-3-642-34026-0_40
Drews, S., D’Antoni, L.: Learning symbolic automata. In: Legay, A., Margaria, T. (eds.) Tools and Algorithms for the Construction and Analysis of Systems - 23rd International Conference, TACAS 2017, Held as Part of the European Joint Conferences on Theory and Practice of Software, ETAPS 2017, Uppsala, Sweden, 22–29 April 2017, Proceedings, Part I. LNCS, vol. 10205, pp. 173–189. Springer, Cham (2017). https://doi.org/10.1007/978-3-662-54577-5_10
Ferreira, T., et al.: Prognosis: closed-box analysis of network protocol implementations. In: SIGCOMM, pp. 762–774. ACM (2021)
Fiterau-Brostean, P., Janssen, R., Vaandrager, F.W.: Combining model learning and model checking to analyze TCP implementations. In: Chaudhuri, S., Farzan, A. (eds.) Computer Aided Verification - 28th International Conference, CAV 2016, Toronto, ON, Canada, 17–23 July 2016, Proceedings, Part II, pp. 454–471. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-41540-6_25
Fiterau-Brostean, P., et al.: Analysis of DTLS implementations using protocol state fuzzing. In: USENIX Security Symposium, pp. 2523–2540. USENIX Association (2020)
Fiterau-Brostean, P., et al.: Model learning and model checking of SSH implementations. In: Erdogmus, H., Havelund, K. (eds.) Proceedings of the 24th ACM SIGSOFT International SPIN Symposium on Model Checking of Software, Santa Barbara, CA, USA, 10–14 July 2017, pp. 142–151. ACM (2017). https://doi.org/10.1145/3092282.3092289
Frohme, M., Steffen, B.: Compositional learning of mutually recursive procedural systems. Int. J. Softw. Tools Technol. Transf. 23, 521–543 (2021). https://doi.org/10.1007/s10009-021-00634-y
Howar, F., Steffen, B.: Active automata learning as black-box search and lazy partition refinement. In: Jansen, N., Stoelinga, M., van den Bos, P. (eds.) A Journey from Process Algebra via Timed Automata to Model Learning. LNCS, vol. 13560, pp. 321–338. Springer, Cham (2022). https://doi.org/10.1007/978-3-031-15629-8_17
Isberner, M., Howar, F., Steffen, B.: Inferring automata with state-local alphabet abstractions. In: Brat, G., Rungta, N., Venet, A. (eds.) NASA Formal Methods, pp. 124–138. Springer, Heidelberg (2013). ISBN: 978-3-642-38088-4, https://doi.org/10.1007/978-3-642-38088-4_9
Isberner, M., Howar, F., Steffen, B.: The open-source LearnLib. In: Kroening, D., Păsăreanu, C.S. (eds.) Computer Aided Verification, pp. 487–495. Springer, Cham (2015). ISBN 978-3-319-21690-4, https://doi.org/10.1007/978-3-319-21690-4_32
Isberner, M., Howar, F., Steffen, B.: The TTT algorithm: a redundancy-free approach to active automata learning. In: Bonakdarpour, B., Smolka, S.A. (eds.) RV 2014. LNCS, vol. 8734, pp. 307–322. Springer, Cham (2014). https://doi.org/10.1007/978-3-319-11164-3_26
Khmelnitsky, I., et al.: Analysis of recurrent neural networks via property-directed verification of surrogate models. Int. J. Softw. Tools Technol. Transf. 25(3), 341–354 (2023). ISSN: 1433-2787, https://doi.org/10.1007/s10009-022-00684-w
Maler, O., Mens, I.-E.: A generic algorithm for learning symbolic automata from membership queries. In: Aceto, L., Bacci, G., Bacci, G., Ingólfsdóttir, A., Legay, A., Mardare, R. (eds.) Models, Algorithms, Logics and Tools. LNCS, vol. 10460, pp. 146–169. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-63121-9_8
Meinke, K.: Active machine learning to test autonomous driving. In: ICST Workshops, p. 286. IEEE (2021)
Neubauer, J., et al.: Automated continuous quality assurance. In: FormSERA 2012 at ICSE 2012, pp. 37–43. IEEE (2012). https://doi.org/10.1109/FormSERA.2012.6229787
Grinchtein, O., Jonsson, B., Leucker, M.: Inference of timed transition systems. Electron. Notes Theor. Comput. Sci. 138(3), 87–99 (2005)
Pferscher, A., Aichernig, B.K.: Fingerprinting and analysis of Bluetooth devices with automata learning. Formal Methods Syst. Des. 61(1), 35–62 (2022)
Pietrantuono, R., et al.: Towards continuous software reliability testing in DevOps. In: 2019 IEEE/ACM 14th International Workshop on Automation of Software Test (AST), pp. 21–27 (2019). https://doi.org/10.1109/AST.2019.00009
Raffelt, H., Steffen, B.: LearnLib: a library for automata learning and experimentation. In: Baresi, L., Heckel, R. (eds.) Fundamental Approaches to Software Engineering, FASE 2006, pp. 377–380. Springer, Cham (2006). ISBN: 978-3-540-33094-3, https://doi.org/10.1007/11693017_28
Raffelt, H., et al.: LearnLib: a framework for extrapolating behavioral models. Int. J. Softw. Tools Technol. Transf. 11(5), 393–407 (2009). ISSN: 1433-2779, https://doi.org/10.1007/s10009-009-0111-8
Shahbaz, M., Groz, R.: Analysis and testing of blackbox component-based systems by inferring partial models. Softw. Test. Verif. Reliab. 24(4), 253–288 (2014). ISSN: 0960-0833, https://doi.org/10.1002/stvr.1491
Sun, J., et al.: TLV: abstraction through testing, learning, and validation. In: Proceedings of the 2015 10th Joint Meeting on Foundations of Software Engineering, ESEC/FSE 2015, Bergamo, Italy, pp. 698–709. ACM (2015). ISBN: 978-1-4503-3675-8, https://doi.org/10.1145/2786805.2786817
Vaandrager, F.W.: On the relationship between process algebra and input/output automata. In: [1991] Proceedings Sixth Annual IEEE Symposium on Logic in Computer Science, pp. 387–398, July 1991. https://doi.org/10.1109/LICS.1991.151662
Vaandrager, F.: Active learning of extended finite state machines. In: Nielsen, B., Weise, C. (eds.) ICTSS 2012. LNCS, vol. 7641, pp. 5–7. Springer, Heidelberg (2012). https://doi.org/10.1007/978-3-642-34691-0_2
Vaandrager, F.W.: Model learning. Commun. ACM 60(2), 86–95 (2017). https://doi.org/10.1145/2967606
Vaandrager, F.W., Bloem, R., Ebrahimi, M.: Learning Mealy machines with one timer. In: Leporati, A. et al. (eds.) Language and Automata Theory and Applications - 15th International Conference, LATA 2021, Milan, Italy, 1–5 March 2021, Proceedings. LNCS, vol. 12638, pp. 157–170. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-68195-1_13
Vaandrager, F.W., et al.: A new approach for active automata learning based on apartness. In: Fisman, D., Rosu, G. (eds.) Tools and Algorithms for the Construction and Analysis of Systems - 28th International Conference, TACAS 2022, Held as Part of the European Joint Conferences on Theory and Practice of Software, ETAPS 2022, Munich, Germany, 2–7 April 2022, Proceedings, Part I. LNCS, vol. 13243, pp. 223–243. Springer, Cham (2022). https://doi.org/10.1007/978-3-030-99524-9_12
Waja, G., Shah, J., Nanavati, P.: Agile software development. Int. J. Eng. Appl. Sci. Technol. 5, 73–78 (2021). https://doi.org/10.33564/IJEAST.2021.v05i12.011
Xu, R., An, J., Zhan, B.: Active learning of one-clock timed automata using constraint solving. In: Bouajjani, A., Holík, L., Wu, Z. (eds.) Automated Technology for Verification and Analysis, ATVA 2022. LNCS, vol. 13505, pp. 249–265. Springer, Cham (2022). https://doi.org/10.1007/978-3-031-19992-9_16
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Krumrey, M., Bainczyk, A., Howar, F., Steffen, B. (2025). Malwa: Learnability by Design. In: Jansen, N., et al. Principles of Verification: Cycling the Probabilistic Landscape . Lecture Notes in Computer Science, vol 15262. Springer, Cham. https://doi.org/10.1007/978-3-031-75778-5_4
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