Scenario Based Test Case Generation Using Activity Diagram and Action Semantics

Scenario is an account of description of user interaction with the system, presented in a sequence. They can be represented using unified modeling language (UML) diagrams such as use case diagram, state charts, activity diagrams etc. Scenario-based testing can be performed at higher abstraction level using the design diagrams. In this work activity diagrams are used which are annotated with action semantics to test scenario dependencies. The action semantics make activity diagram executable and the dependencies between multiple scenarios can be seen at execution level. The authors intend to propose an approach for scenario dependency testing. Dependency graphs will be then generated against all the dependencies present on activity diagram under test. The test paths extracted from these dependency graphs help in testing.

Situational model of technological operations for secondary metallurgy

Purpose: The aim of this study was development of a computer situational model of heat and power processes and transport operations for secondary steelmaking (SSM) to evaluate the effectiveness of the proposed SSM energy regimes and minimization the consumption of energy resources. Design/methodology/approach: For the solution of the tasks were used next methods: analytical and statistical methods of mathematical modeling; method of dynamic programming for the development of technological recommendations for energy modes on LF; Harel state charts to evaluate the effectiveness of the applied models. Findings: In order to provide rational energy regimes for SSM, it is necessary to introduce a new controlled parameter - the optimum time to start heating the melt at the ladle furnace unit (LF), which is determined by solving the dynamic programming task. The melt heating start time must be selected in such a way as to ensure that all the necessary technological operations are performed during metal processing in the LF, taking into account schedule constraints, and that the heating of the metal must be carried out with the maximum energy efficiency. Research limitations/implications: The main objective of the present study was to apply the mathematical modeling methods to ensure rational energy regimes of SSM. Practical implications: The developed situational model of technological operations for SSM will allow finding reserves to increase the productivity and quality of the process, and to evaluate the effectiveness of new technological solutions. Originality/value: To ensure an energy-efficient treatment of steel in LF, it is necessary: the time for starting the heating of the metal is chosen such that the energy efficiency of the LF, which depends on the thickness of the slag layer, is maximum at each stage; increase the power that is supplied to the heating of the melt by switching the voltage taps of the transformer as the thickness of the slag cover increases.

Statecharts and State Chart XML as a Modeling Technique in Web Engineering

Domain-driven design is a methodology that attempts to improve software development by focusing on domain terminology and functionality. It encourages collaboration between technical and domain experts by making an explicit technology-independent model that is iteratively refined. Many modeling languages exist. This paper examines the use of statecharts and their XML encoding, State Charts XML (SCXML), as a language for modeling the behavioral aspects of a reactive system. The use case presented in this paper is GameX, an interactive browser-based game where players operate on a map of towns and fields. We demonstrate that SCXML-encoded statecharts can be used to describe complex models during the software development process. Not only can these models be used to drive new development, but modeling already deployed systems in this way can provide a deeper understanding of their behavior.

A Symbolic Approach to the Analysis of Multi-Formalism Markov Reward Models

When modelling large systems, modularity is an important concept, as it aids modellers to master the complexity of their model. Moreover, employing different modelling formalisms within the same modelling project has the potential to ease the description of various parts or aspects of the overall system. In the area of performability modelling, formalisms such as stochastic reward nets, stochastic process algebras, stochastic automata, or stochastic UML state charts are often used, and several of these may be employed within one modelling project. This chapter presents an approach for efficiently constructing a symbolic representation in the form of a zero-suppressed Binary Decision Diagram (BDD), which represents the Markov Reward Model underlying a multi-formalism high-level model. In this approach, the interaction between the submodels may be established either by the sharing of state variables or by the synchronisation of common activities. It is shown that the Decision Diagram data structure and the associated algorithms enable highly efficient state space generation and different forms of analysis of the underlying Markov Reward Model (e.g. calculation of reward measures or asserting non-functional system properties by means of model checking techniques).