Based on analyzing the effects of exception handling constructs on dependence analysis, this paper proposes a precise and efficient representation for C++ programs with exception handling constructs—improved control flow graph.

Based on Q-learning method, the paper presents a novel idea of program dynamic dependence analysis, and gives an algorithm which can make analysis for complex programs more concise, more intelligent and more efficient.

It is analyze the programming parallelism on Ada95 and implemented the principle with a series of algorithms based on control and data-dependence analysis, and made the auto-recognition possible in this thesis.

Integration framework of enterprise components based on dependency analysis;

UML Statechart Slicing Based on Dependency Analysis in the Regression Testing;

Through the dependency analysis,this paper generates the UML statechart diagram and dependency diagram.

The method uses the underlying principle of the bound and collapse method to estimate the joint probability of variable sets,and it adopts basic ideas of dependency analysis to learn Bayesian networks.

A new method of learning Bayesian network structure based on basic dependency relationship between variables,basic structure between nodes,d-separation criterion,the idea of dependency analysis and the strategy of mixture orienting is given.

Firstly, in this paper an over view of Bayesian network and its characteristics is presented,and how to learn a Bayesian network structure from given data is discussed,and then a model of the Bayesian network is constructed by the dependency analysis of Bayesian network learning algorithm for the period of Xiangshan Baycage culture with expert knowledge and the dataset.