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Problem: Quality issues of software

Software Quality Assessment Process

Modelling, analysis, and refactoring.

graph LR
  1(Annotated Software Model)
  2(Model2Model transformation)
  3(quality-based model)
  4(model solutiion or simulation)
  5(quality metrics)
  6(results interpretation and feedback generation)
  1-->2
  2-->3
  3-->4
  4-->5
  5-->6
  6-->1

Objectives and Contents of the Lecture

Objectives

  • Understand foundation of stochastic process
  • Quatitative analysis of stochastic process

Contents

  • Stochastic process
  • Markov Chains
  • LAB on discrete time Markov Chains
  • Petri Nets
  • LAB on generalized stochastic Petri Nets

Stochastic Process

Stochastic process is a collection of random variables representing the evolution of a system.

Counterpart to deterministic.

In Computer Science, probabilities can be

  • Randomized algorithms
  • Unreliable or unpredictable system behaviors
  • System performance and dependability
  • Complex systems

Recap Some Basic Notions

Experiments, sample spaces, events, probability measures, random experiment, random variable

Cumulative distribution function (CDF) \(F(x)=\Pr\{X\leq x\}\).

Some Probability Distributions

  • Uniform distribution
  • Normal distribution: \(\mu,\sigma^2\)
  • Binomial distribution
  • Poisson distribution
  • Exponential distribution