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Distributed Architecture for an Integrated Development Environment, Large Trace Analysis, and Visualization.

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This study introduces a novel modular client-server architecture for integrating tracing and trace visualization tools into modern Integrated Development Environments (IDEs). This approach enhances software performance analysis, especially for Internet of Things (IoT) devices.

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Area of Science:

  • Computer Science
  • Software Engineering

Background:

  • Integrated Development Environments (IDEs) offer essential software development tools but struggle with integrating advanced debugging and performance analysis features.
  • Traditional IDE plugins for language support are often not reusable across different IDEs, increasing development and maintenance overhead.
  • Existing tracing and visualization tools operate independently, failing to leverage the benefits of modular IDEs.

Purpose of the Study:

  • To propose an efficient, modular client-server architecture for integrating trace analysis and visualization into modern IDEs.
  • To address the challenge of incorporating tracing tools, which have unique data structures and use cases, into modular IDE frameworks.
  • To facilitate performance analysis for large, multithreaded systems and resource-constrained devices like those in the Internet of Things (IoT).

Main Methods:

  • Development of a modular client-server architecture for trace analysis and visualization.
  • Designing the architecture for efficient data handling of potentially massive execution traces.
  • Focusing on reusability and interoperability with existing modular IDE frameworks.

Main Results:

  • The proposed architecture enables seamless integration of tracing tools within modular IDEs.
  • Experimental evaluation confirmed the solution's scalability and flexibility.
  • The architecture demonstrated a small, acceptable performance overhead compared to standalone tracing tools.

Conclusions:

  • The developed client-server architecture effectively solves the challenge of integrating tracing tools into modular IDEs.
  • The solution is well-suited for performance analysis on resource-limited IoT devices.
  • The proposed architecture offers a reusable, scalable, and efficient approach to software performance analysis.