Analyzing And Quantifying Software Risks
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Analyzing And Quantifying Software Risks
There are some old and new risk analysis tools and techniques to use. The previously discussed tools for analyzing the identified risks are:
Brainstorming
1. Offer risks analysis ideas without judgment or evaluation
2. Build on ideas offered
3. Repeat until all ideas on risk analysis are exhausted.
Risk clustering
2. Build on ideas offered
3. Repeat until all ideas on risk analysis are exhausted.
Delphi method
1. Select a panel of experts (isolated from each other and unknown to one another)
2. Prepare and circulate a questionnaire about a risk
3. Solicit risk handling approaches and opinions
4. Share all responses and statistical feedback with entire group
5. Repeat until there is convergence on a consensus approaches
New analysis techniques that project managers and teams can use for risk analysis are:
2. Prepare and circulate a questionnaire about a risk
3. Solicit risk handling approaches and opinions
4. Share all responses and statistical feedback with entire group
5. Repeat until there is convergence on a consensus approaches
New analysis techniques that project managers and teams can use for risk analysis are:
Sensitivity analysis
1. Choose a few variable with big impact to the plan
2. Define a likely range of vaeration
3. Assess effect of changing them on project outcome
2. Define a likely range of vaeration
3. Assess effect of changing them on project outcome
Probability analysis
1. Similar to sensitivity analysis
2. Adds a probability distribution for each variable, usually skewed to eliminate optimism
2. Adds a probability distribution for each variable, usually skewed to eliminate optimism
Monte Carlo simulation
1. Similar to probability analysis
2. Assign randomly chosen values for each variable
3. Run simulation a number of times to get a probability distribution for the outcome
4. Produces a range of probabilities for the outcome
2. Assign randomly chosen values for each variable
3. Run simulation a number of times to get a probability distribution for the outcome
4. Produces a range of probabilities for the outcome
Utility theory
1. Comprehends decision maker’s attitude toward risk
2. Viewed as theoretical
2. Viewed as theoretical
Decision tree analysis
1. Graphical method
2. Forces probability considerations for each outcome
3. Usually applied to cost and time
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2. Forces probability considerations for each outcome
3. Usually applied to cost and time
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