Stop Testing! You Might Find Something Wrong

The pinnacle of Quality Engineering is not finding bugs but eliminating any possibilities for a bug. Quality issues kill customer experience instantly and eventually destroy the hard-earned brand equity. Resurrecting your business brand is quite costlier than fixing the technical issues. Hence every company should adopt matured quality engineering processes early in the software engineering lifecycle, so that the guaranteed business outcomes are delivered consistently throughout the customer journey.

Quality of your software engineering processes can very easily be judged from the quality of the issues you unearth throughout the software life cycle. If you find anything during testing, then there are opportunities for improvement. ?Predicting and avoiding issues should be the ultimate objective than finding and fixing issues.

The field of Quality Engineering has advanced lot more than you can imagine. When you apply technology to test technology, there are world of possibilities. Today Machine Learning and Artificial Intelligence have paved ways for all kinds of prediction techniques, so that engineers can avoid potential quality issues as they develop software.

Emerging methodologies have increased release velocity of customer applications. Businesses worry about cost, quality, speed, and customer experience in every one of these releases. Matured automation is key for continuous deployment. When the power of technology and deep domain knowledge come together in testing, effectiveness of quality goes up. Consistently measuring the test effectiveness will give us confidence in certifying the product 100% error free so that there is no necessity for end of the lifecycle testing.

Such a “Zero Testing” environment is the ultimate nirvana that the future of software engineering can achieve. But all of us know, zero-testing is the result of early and more frequent testing in the software development lifecycle. It is also a status that we achieve over a period after multiple iterations of release cycles.

Foundation for Zero Testing is built on the following principles:

1. Agile maturity of the organization: ?As every company is modernizing their IT, unlocking the value of these emerging technologies requires a fundamental shift in mindset and the adoption of an agile approach across the organization.?The model should enforce early inclusion of customers in the process so that the consumer persona can be assessed early in the lifecycle to avoid potential usability issues in the future. Studies prove that more than 85% of the issues can be avoided by conducting group tests before the product rollout.
2. Effectiveness of enterprise architecture: How we design the application seriously matter for the QE efficiency. A microservices architecture will help design a more sophisticated Quality Engineering model than a monolithic design. When automation goes more modular, coverage and leverage can be better administered.
3. Advanced QE discipline – Automation and Simulation are the quality-twins that help us guarantee product quality. Automation preserves application knowledge reusable. Simulating potential users, data, devices, servers, and usability scenarios using virtualization technologies helps test the application on possible scenarios. That’s the only way to check out the possibilities of all kinds of quality issues that could arise now during the development and later during the usage.
4. Quality of “feedback” to the system: It is important to learn early on issues that (potentially may) go wrong. Each of the learnings should be fed back through the system so that testing becomes more and more efficient. Application of our current knowledge and the ones we continue to learn should be automatic. Manual dependencies aren’t going to help. We should align the learning and automation leverage so that every iteration of development and testing gets better and better.
5. Self-Testing & Self-Healing: Continuous quality can only be achieved through continuous testing. Embedding robotic components with the applications to digitize the quality gates to monitor, learn, self-test and self-heal, will help certify the quality for the life of the product. This requires investment in Machine Learning /Artificial Intelligence in test.

As a QE enthusiast, I would never advise you NOT to test. But testing more and testing early, can help you guarantee quality for the life of the product, so no one needs to test it again.