Applying Model-Driven Distributed Continuous Quality Assurance Processes to Enhance Persistent Software Attributes

Arvind S. Krishna, Cemal Yilmaz, Atif Memon, Adam Porter,
Douglas C. Schmidt, Aniruddha Gokhale, Balachandran Natarajan,
Dept. of Computer Science, University of Maryland, College Park, MD 20742
Dept. of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, TN 37203

Abstract:

• Introduction
  • Emerging trends and challenges.
  • Addressing PSA challenges with distributed continuous quality assurance and model-driven techniques.
  • Related work.
• Applying Model-driven DCQA Techniques to Address PSA Challenges
  • Managing PSA Challenges with Model-driven Skoll
  • An Example Model-driven DCQA Process
    • Step 1: Define the application scenario.
    • Step 2: Create benchmarks using the model-driven BGML tool.
    • Step 3: Register and download clients.
    • Step 4: Execute DCQA Process.
• Evaluating Correctness and Performance of QoS-Intensive Software
  • Evaluating Functional Correctness Across Large Configuration Spaces
    • Scenario 1: Clean Compilation
    • Scenario 2: Testing with Default Run-Time Options
    • Scenario 3: Regression Testing with Configurable Run-Time Options
  • Identifying Performance Degradation Across Large Configuration Spaces
    • Step 1: Define the application scenario.
    • Step 2: Create benchmarks using the model-driven BGML tool.
    • Step 3: Apply the main effects screening process.
    • Step 4: Compare to exhaustive and random testing.
• Concluding Remarks
• References
• About this document ...