Aditya Akundi

Basis Path Analysis for Testing Complex System of Systems

Abstract In Systems of Systems (SoS), a major challenge is to determine how to design a test suite that will check that the complete SoS mission and objectives are achieved. Combinatorial strategies that test for every interface in the SoS are not always optimal due to their exponential nature, and given the mission of the SoS, not all the constituent systems might have to actually interact with each other. To overcome these problems, this paper proposes the use of Basis Path Testing, which is a white-box software testing technique that makes use of Graph Theory to analyse the complexity of a structured system by creating a control flow graph from each of the programs functions to design an optimal test suite. This test suite is a set of paths that traverse through the functions, which are assumed linearly independent and that can be used to create a test strategy that will exercise all of the programs functions at least once to verify and validate their functionality. By applying Basis Path Testing analysis to the constituent systems in a SoS, the tester can develop an optimal test suite that will guarantee that all possible independent paths, all possible logical decisions, and all their interfaces are executed at least once. This paper presents a SoS sample architecture and show how to generate a test suite using Basis Path Testing analysis.

UML Profile and Extensions for Complex Approval Systems with Complementary Levels of Abstraction

Abstract Extending the Unified Modelling Language (UML) version 2.0 with a profile and stereotypes that allow the modelling of an approval system with multiple levels, each with inherently dualistic complementarity, allows the high-fidelity characterization of the stacked levels of a real world approval hierarchy. The objective was to extend UML to model the complex, emergent and multi-level decision making which occurs within modern multi- disciplinary projects. At any level of abstraction, the logical and concrete processes of that level allow a consideration of local factors and decisions, generating and establishing a qualitative conclusion as the result. The high degree of certainly in the result creates the absoluteness of the qualitative conclusion, which can then be fed up or down one level of abstraction in order to take part in the local decision making at that level. The profile was applied to ground-breaking and ongoing engineering investigation concerning the expansion of a student busing system as it is proposed to be integrated into a city-wide busing system, where the student busing system can be considered to be a sub-system to the city-wide busing system, but in reality it is a self-standing, independent and complete system in its own right.

Information entropy applied to software based control flow graphs

Information theory, introduced by Shannon in the context of information transfer in communication channels, is used as a foundation for research in many diverse fields. The concept Entropy in terms of information theory is seen as the average amount of information or the rate of information produced when forming a message, element by element. Entropy has found broad application in many research fields and can also be applied in software engineering for quantifying the uncertainty associated with a software code. In this paper, information entropy and its application towards measuring software complexity are explored, along with the formulation of an information entropy based complexity measure that considers logical decision-making, processes, and software statement interaction patterns in control flow graphs mapped from actual software code. To broaden the application of the proposed metric, the execution times of nodes in the control flow graphs are also incorporated. Further, the metric is evaluated against eight different axioms that a software complexity measure should satisfy.