Interaction Analyzer

Overview

Ubiquitous and pervasive computing systems are examples of complex systems where components are designed to work and interact with each other as a whole. Managing the behavior of applications in these systems is an important task in order to fully understand, develop and debug robust applications. When building applications in such a complex environment, the developers want the applications to behave correctly. If the application's behavior is unintended or reflects bugs, it is important to localize the original ...
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Overview

Ubiquitous and pervasive computing systems are examples of complex systems where components are designed to work and interact with each other as a whole. Managing the behavior of applications in these systems is an important task in order to fully understand, develop and debug robust applications. When building applications in such a complex environment, the developers want the applications to behave correctly. If the application's behavior is unintended or reflects bugs, it is important to localize the original root cause. However, due to the complexity of the application, it is often not trivial to analyze and localize the root cause of unexpected behavior easily. The developers can be easily overwhelmed due to the large number of different components. Additionally, these components can be driven by different complex protocols that span multiple protocol layers. Moreover, the communications or interactions between these components can occur in a distributed nature with different associated context information. In this dissertation I will describe an approach that enables developers to debug distributed and complex ubiquitous systems in a less costly and more effective manner via a scalable and interactive validation process using a system's specification and runtime information. The approach is demonstrated by the Interaction Analyzer, a working implementation. The Interaction Analyzer was evaluated with real applications and real bugs to show the functionality and applicability of the approach. Simulation results and mathematical models also prove its scalability for large-scale systems with different characteristics.
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Product Details

  • ISBN-13: 9781243672124
  • Publisher: BiblioLabsII
  • Publication date: 9/7/2011
  • Pages: 272
  • Product dimensions: 7.44 (w) x 9.69 (h) x 0.57 (d)

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