Reliability Tools

Reliability Tools

The basis of all reliability tools is statistical analysis - any tools with the ability to analyze data sets and basic statistical techniques. Each of the software reliability approaches has an appropriate tool set:

Fault forecasting - reliability models, historic data analysis, failure data collection, functional profiling, operational environment profiling;

Fault prevention - formal methods, software reuse, construction tools;

Fault removal - formal inspections, verification and validation;

Fault tolerance - monitoring techniques, decision verification, redundancy, exception conditions.

The goal of this section is not to be a tool guide to reliability engineering. Michael Lyu's 1996 book, Handbook of Software Reliability Engineering, is the definitive guide to this field. The goal here is to specify the skills required on a project team in order to successfully use the tools available. A project manager needs to either have these statistical skills or have an experienced team member available before attempting to use commercially available reliability models and statistical methods:

1. Notations

● Discrete random variables
● Continuous random variables
● Conditional probabilities
● Conditional probability density functions
● Stochastic processes

2. Reliability theory

● Time-to-failure relationships
● Failure rate
● Mean-time-to-failure
● Failure intensity

3. Analytical methods

● Combinatorial models
● Markov models
● Markov reward analysis
● Birth-death process
● Poisson processes

4. Statistical techniques

● Parameter estimation
● Point estimation
● Interval estimation
● Distribution characterization
● Empirical distribution
● Distribution function fitting
● Chi-square test
● Kolmogorov-Smirnov test
● Multivariate analysis
● Correlation analysis
● Factor analysis
● Cluster analysis


statistical analysis, construction tools, decision verification, redundancy
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