Stakeholders are always pushing searching for faster solutions. Project managers are rushing products to the delivery table. And there is isn't necessarily anything wrong with doing it this way.

But it can be challenging for QA testing teams who have to embrace this super quick timetable, and then convince the developer team to get onboard.

Software teams know how badly test management teams want to reach deadlines when they are coping with constant shifts and changes.

In this scenario, all blame falls on the test team, who might quickly become a convenient target when production bugs are shipped. And any delays regarding specifications and implementation in the upstream software development lifecycle (SDLC) phase will make matters worse.

Beyond that, the demands of the stakeholders who want the product available ASAP add fuel to the fire. All of this puts the testing team under immense pressure.

A QA team must have a rational and empirical response to this challenge. The answer to this problem lies in risk-based testing (RBT) which can help the testing team deliver on their deadlines.

Your test team can save a ton of effort with the RBT strategy, and it produces great savings while delivering the project on time.

What is Risk-Based Testing? RBT Basics

In risk-based test management, you find the greatest market threats (that would have a detrimental effect on the enterprise as defined by the consumer) early in the development cycle and then you can counter them by taking preventive steps.

These market threats may include increased costs, consumer disappointment, poor user interface, and lost customers. And RBT can help you mitigate them by conducting testing in such a way that, even if a customer gets an error, they can go on using the application (and the organization isn't greatly affected).

RBT involves testing that's performed on the basis of product risks. It's useful in helping you discover how likely a specific feature or capability is to fail in final output/production. It'll also help you determine this failure's effect on the company in terms of cost and other damages, well ahead of time. And it does this by using a prioritization strategy for test cases.

So Risk-Based evaluation works by prioritizing the testing of a product or software's functionality, components, and features. This prioritization is based on the risk of the possibility of failure in the development of the feature or functionality and its effect on clients.

How to Assess Risk with RBT

RBT includes risk management and test prioritization depending on the risk factor of each test. The risk factor is the result of the likelihood and possible effect of future risk.

But how are we able to come up with those values? To allocate a risk factor to a specific risk, here are three requirements to consider.

Code Complexity

Cyclomatic Complexity

The more ambiguous code is, the more likely flaws will be discovered. Simply put, it is more likely that more complicated code contains glitches. The reverse is also true: the cleaner and simpler the code, the less likely it is to contain errors.

The problem then is how you should calculate code complexity. One measure is cyclomatic complexity which refers to the number of potential paths. The minimal number of test cases you require to thoroughly test a feature is determined by that number. In fact, code with high cyclomatic complexity, which may expand the number of errors, can be more difficult to read.

Churn or number of modifications to the code

Churn here implies the number of modifications that a specified file or module experiences. An application area that developers alter more frequently is more likely to have bugs than one which they hardly ever touch.

A great example of this is an application for e-commerce that has been in development for many years. The software team is likely to make frequent adjustments to the offers, introduce new features, and try experiments to boost purchases. The affected sections of the code shift regularly and are thus more likely to produce errors.

When churn is significant, extensive testing should be proposed for risk-based planning: more UI tests, more unit tests, more integration tests, and so on.


Criticality involves the calculation of a software defect's influence on your application. Criticality is not spread equally through a codebase. Many systems are expected to have a high-critical code core on which the remainder of the application relies.

If the code does not perform properly, several parts of the software could be compromised and it would probably create defects. If it applies to safety-related software, a critical flaw may cause data loss, sensitive data disclosure, and maybe even endanger lives.

When measuring the effect portion of the risk factor, criticality may be useful.

If a bug arises in the application's most important environment, the effects could be much more extreme than if it existed in some area that included utility code only.

We rely on our algorithms in our test management frameworks to classify site components. If web components can not be detected by the algorithm and related core code, the UI checks if our customers will make mistakes or fail, creating frustration, reworks, service calls, and a lack of faith in our solution.

Worse still, if false positives are generated by our application, it will interrupt the CI/CD process and impede the implementation of a legitimate application.

Smart Testing Is the Solution

Software development companies need a better strategy when it comes to software testing than "just test everything." Not all code is equal, not all threats are credible, and not all bugs trigger equal harm.

In order to make informed decisions about how to distribute capital and test them more effectively, tech companies must take these RBT considerations into account.

If you want to remain on top of your Risk-Based Software Testing, you can check out Kualitee – we're a software testing and information security company.