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Advanced Risk Based Test Results Reporting: Putting Residual Quality Risk Measurement in Motion

Girish Basidoni
Girish Basidoni
President and Chief Executive Officer, TestingCzars Software Solutions
Girish is currently employed at TestingCzars Software Solutions Private Limited in the position o... more>>
Analytical risk based testing offers a number of benefits to test teams and organizations that use this strategy. One of those benefits is the opportunity to make risk-aware release decisions. However, this benefit requires risk based test results reporting, which many organizations have found particularly challenging. This article describes the basics of risk based testing results reporting, then shows how Rex Black (of RBCS) and Nagata Atsushi (of Sony) developed and implemented new and ground-breaking ways to report test results based on risk.

Testing can be thought of as (one) way to reduce the risks to system quality prior to release. Quality risks typically include possible situations like slow system response to use input, incorrect calculations, corruption of customer data, and difficulty in understanding system interfaces. All testing strategies, competently executed, will reduce quality risks. However, analytical risk based testing, a strategy that allocates testing effort and sequences test execution based on risk, minimizes the level of residual quality risk for any given amount of testing effort.

There are various techniques for risk based testing, including highly formal techniques like Failure Mode and Effect Analysis (FMEA). Most organizations find this technique too difficult to implement, so RBCS typically recommends and helps clients to implement a technique called Pragmatic Risk Analysis and Management (PRAM). You can find a case study of PRAM implementation at another large company CA at:

http://www.rbcs-us.com/images/documents/A-Case-Study-in-Risk-Based-Testing.pdf


While this article describes the implementation of the technique for projects following a sequential life-cycle, a similar approach has been implemented by organizations using Agile and iterative life-cycle models.

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