Abstract
Formal scenarios have many uses in requirements engineering, validation, performance modeling, and test generation. Many tools and methodologies can handle scenarios when the number of steps (interleaved inputs and outputs of the target system) is reasonably small. However, scenario based techniques do not scale well with the number of steps, number of actors, and complexity of behaviors and system interactions to be specified in the scenario. First, it is impractically tedious and error-prone to specify thousands of input steps and corresponding expected outputs. Second, even if one can write down such large scale scenarios, confidence in their correctness is naturally low. Third, complex systems requiring large scale scenarios tend to require many such scenarios to adequately cover the behavior space. This paper describes the motivations for and problems of large scale scenarios, as well as the LSS method, which uses automated and semi-automated techniques in describing, maintaining, communicating, and using large scale scenarios in requirements engineering. The method is illustrated in two widely divergent application domains: military live training instrumentation and electronic mail servers. A case study demonstrates the practical and beneficial use of LSS in architectural modeling of a complex, real-world system design.
Similar content being viewed by others
Explore related subjects
Discover the latest articles and news from researchers in related subjects, suggested using machine learning.References
Hall, R.J.: Feature interactions in electronic mail. In: Feature Interactions in Telecommunications and Software Systems VI. IOS Press (2000)
Hall, R.J.: Specification, validation, and synthesis of email agent controllers: a case study in function rich reactive system design. Autom. Softw. Eng. 9 (2002)
Hall, R.J.: Combinatorial communications modeling of real-time tactical engagement adjudication architectures. In: Proc. 2005 IEEE Military Communications Conf. (2005a)
Hall, R.J.: Fundamental nonmodularity in electronic mail. Autom. Softw. Eng. 12(1) (2005b)
Hall, R.J., Zisman, A.: Validating personal requirements by assisted symbolic behavior browsing. In: Proc. of the 19th IEEE Conf. on Automated Software Engineering (2004)
Harel, D., Marelly, R.: Come, Let’s Play. Springer, Berlin (2003)
Heitmeyer, C., Kirby, J., Labaw, B., Bharadwaj, R.: Scr*: A toolset for specifying and analyzing software requirements. In: 10th Computer-Aided Verification Conf. (1998)
Holzmann, G.: Design and Validation of Computer Protocols. Prentice Hall, New York (1991)
Imielinski, T., Navas, J.: Geographic addressing, routing, and resource discovery with the global positioning system. Commun. ACM (1997)
ITU-T: Message sequence charts standard. www.itu.int/ITU-T/
Mauw, S., Reniers, M.A.: High-level message sequence charts. In: Proceedings of the Eighth SDL Forum (SDL’97), pp. 291–306 (1997)
Murthy, C.S.R., Manoj, B.S.: Ad Hoc Wireless Networks: Architectures and Protocols. Prentice Hall, New York (2004)
Musa, J.: Operational profiles in software-reliability engineering. IEEE Softw. 10(2), 14–32 (1993)
Reiter, M., Parson, J., Apticar, T.: The headquarters convoy model. In: Armor, pp. 26–33, January–February (2005)
Richardson, D., Aha, S., O’Malley, T.: Specification-based test oracles for reactive systems. In: Proceedings of the 14th International Conference on Software Engineering (1992)
Uchitel, S., Kramer, J., Magee, J.: Negative scenarios for implied scenario elicitation. In: Proceedings of the 10th Intl. Conf. on Foundations of Software Engineering (2002)
Uchitel, S., Kramer, J., Magee, J.: Incremental elaboration of scenario-based specifications and behavior models using implied scenarios. ACM Trans. Softw. Eng. Meth. 13(1), 37–85 (2004)
Author information
Authors and Affiliations
Corresponding author
Additional information
A two page extended abstract of this paper appeared in Proc. 21st ACM/IEEE Intl. Conf. on Software Engineering (ASE 2006).
Rights and permissions
About this article
Cite this article
Hall, R.J. A method and tools for large scale scenarios. Autom Softw Eng 15, 113–148 (2008). https://doi.org/10.1007/s10515-008-0026-8
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10515-008-0026-8