Leveraging Grid Computing Framework for Program Analysis

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Leveraging Grid Computing Framework for Program
Analysis

• CS 6230 Term Project
• Spring 05
• Gaurav Sharma

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Introduction

• Dynamic Analysis of software involves studying
  the program based on its behavior at run time.
• Some of the analysis techniques include examining
  the path of execution, branch spectra,
  definition-use spectra, data spectra etc.
• Dynamic Analysis is useful for understanding the
  behavior of the software.
• It can be used for Software Classification, Fault
  Localization etc.

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Introduction (Contd)

• Im using data spectra aspect of Dynamic
  Analysis for Software Classification
• Programs are first instrumented and then executed
  to generate traces. These traces represent the
  flow of execution of the program.
• The traces are analyzed to create data models
  which represent the data spectra.

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Using Grid Framework

• I plan to use the Grid Computing framework to
  create a distributed application.
• I will be using the CoG kits from Globus to
  develop an application to generate program traces
  and create data models in a distributed manner.
• The individual data models will be pieced
  together to give a model representing one
  execution of the software.

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Related Work

• Theres a lot of work being done in the field of
  Dynamic Analysis for determining software
  behavior. However, not much work has been done
  from the perspective of high-performance
  computing.
• Checking inside the black box Regression
  testing based on value spectra differences' by
  Tao Xie and David Notkin.
• Finding latent code errors via machine learning
  over program executions' by Yuriy Brun and
  Michael D. Ernst.