computer science

Risk-based testing

Risk-based testing is a computer science topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Risk-based testing rather than just read about it. In short: Risk-based testing (RBT) is a type of software testing that functions as an organizational principle used to prioritize the tests of features and functions in software, based on the risk of failure, the function of their importance and likelihood or impact of failure. In theory, there are an infinite number of possible tests.

Key takeaways

Risk-based testing belongs to computer science; place it in that map before memorising details.
Learn the definition first, then one example that makes the definition concrete.
Connect Risk-based testing to a quantity you can measure, compute or draw — that is where exam questions come from.
Reproduce the core statement of Risk-based testing from memory before moving on to harder problems.

Reference excerpt

Risk-based testing (RBT) is a type of software testing that functions as an organizational principle used to prioritize the tests of features and functions in software, based on the risk of failure, the function of their importance and likelihood or impact of failure. In theory, there are an infinite number of possible tests. Risk-based testing uses risk (re-)assessments to steer all phases of the test process, i.e., test planning, test design, test implementation, test execution and test evaluation. This includes for instance, ranking of tests, and subtests, for functionality; test techniques such as boundary-value analysis, all-pairs testing and state transition tables aim to find the areas most likely to be defective.

Types of risk assessment

Light-weight risk assessment Lightweight risk-based testing methods mainly concentrate on two important factors: likelihood and impact. Likelihood means how likely it is for a risk to happen, while impact measures how serious the consequences could be if the risk actually occurs. Instead of using complicated math, these techniques rely on simple judgments and scales. For instance, a team might rate the chance of risk as high, medium, or low and its impact as severe, moderate, or minor. These ratings help prioritize where testing efforts should be focused.

Heavy-weight risk assessment Heavy-weighted risk-based testing is a method used to test software by focusing on the areas where problems are most likely to happen. The testing team looks for the most important parts of the software that might fail and concentrates on testing those parts more thoroughly. There are four main types of heavy-weight risk-based testing methods:

Cost of Exposure: This looks at how much money a problem in the software might cause. It figures this out by thinking about how likely a problem is and how much it might cost. Failure Mode and Effect Analysis (FMEA): This technique finds out what parts of the software might fail, why they might fail, and what might happen if they do. It helps find the important areas that need attention. Quality Functional Deployment (QFD): This method helps connect what the users need with what the software does. It looks at risks that might come from not understanding what the users really want. Fault Tree Analysis (FTA): This technique is used to figure out why something went wrong by looking at different reasons in a step-by-step way.

Types of risk Risk can be identified as the probability that an undetected software bug may have a negative impact on the user of a system. The methods assess risks along a variety of dimensions:

Business or operational High use of a subsystem, function or feature Criticality of a subsystem, function or feature, including the cost of failure

Technical Geographic distribution of development team Complexity of a subsystem or function

External Sponsor or executive preference Regulatory requirements

E-business failure-mode related Static content defects Web page integration defects Functional behavior-related failure Service (Availability and Performance) related failure Usability and Accessibility-related failure Security vulnerability Large scale integration failure

References

Worked examples

Example 1 — a first encounter with Risk-based testing

Start with the simplest possible case. Write down what Risk-based testing claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In computer science, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Risk-based testing before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Risk-based testing ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Risk-based testing

In research: Risk-based testing appears in computer science research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry: Engineering practice reuses Risk-based testing in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom: Risk-based testing is common in secondary-school and first-year university syllabi. It links to neighbouring topics Software engineering stubs, Software testing, so understanding it makes those chapters shorter.
In everyday life: Look for Risk-based testing outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.

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How to study Risk-based testing in 20 minutes

Read the reference excerpt below once, without taking notes.
Close the page and write down what Risk-based testing means in your own words.
Compare your version with the excerpt and mark what you missed.
Work through the three examples above with pen and paper.
Explain Risk-based testing out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Risk-based testing in simple terms?

Why does Risk-based testing matter?

Because it connects several computer science ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Risk-based testing?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Risk-based testing.