The world of test management is currently undergoing a remarkable transformation. In times of ever-increasing demands being placed on software quality and the smooth operation of applications, conventional test methods often reach their limits. This is countered by new, innovative methodological approaches to test management. In this blog post, we’ll be taking a look at these new methods and their potential to make the testing process more effective, flexible and accurate.
By Fatih Kilic
Shift-left testing, automation and agile methods
One promising approach is shift-left testing. This involves a strategy of integrating testing in the early stages of the development cycle. Instead of simply beginning testing at the end of the project, testers are integrated into the development process at an early stage. An essential design strategy that can be seamlessly integrated into this approach is known as “Test Driven Development” (TDD). In TDD, test cases are initially created that define the code’s expected behaviour, and then the code is developed to pass these tests. This cyclical approach aims to prevent errors from the outset during the development phase, and thus contributes to a more effective and cost-efficient testing strategy.
The continuous technical development in test automation opens up a multitude of new opportunities. Modern automation tools integrate artificial intelligence and machine learning, in order to automatically generate test cases, identify test data and detect anomalies. As a result, these test automation tools provide advanced analytics and reporting capabilities that facilitate deeper insight into test results and quality trends. Test automation will benefit even further from cloud services in the future, as they can dynamically provide the entire test infrastructure. Applications – with all their services and web front-ends – can be provided and tested on this infrastructure.
With Low-Code and No-Code test automation tools, even non-developers can create and execute test scripts. This promotes a spirit of cooperation between developers and testers, and speeds up the testing process. This allows checks to be carried out more frequently, leading to improved error detection. Automation offers greater scalability and enables efficient reuse of test cases. This allows testers to focus on more demanding and complex test tasks, while routine tests are executed automatically.
Agile methods – such as Scrum or Kanban – have established themselves as methodological approaches within test management. They are characterised by short development cycles, continuous testing and a close cooperation framework between developers and testers. The agile approach enables faster error detection and correction, as well as high adaptability to changing requirements. Close cooperation between the teams helps to shorten communication channels, which leads to more effective coordination. Agile methods in test management enable faster and more efficient software development, improved quality and better adaptability to changing requirements.
AI revolutionises test management
The integration of artificial intelligence (AI) into test management opens up many new opportunities to render the testing process more efficient and effective.
Corresponding algorithms can automatically create and execute test cases based on requirements, behaviour models or existing test data. This enables more comprehensive test coverage and saves valuable time in the manual creation and execution of test cases. AI can explore different combinations of inputs and scenarios to uncover potential sources of error.
In addition, AI analyses test results and error patterns to adjust the order of test execution and identify prioritised cases. This makes optimal use of resources and speeds up error detection. Intelligent test execution is particularly beneficial within agile development processes, as it delivers fast results and increases development efficiency.
Investment in new test management pays off
It should be noted that the new methodological approaches to test management described here offer tremendous potential for optimisation. Companies should not see it as just a passing trend, but as an opportunity to increase the efficiency of their software projects. By relying on Shift-Left Testing, Test Automation, Agile Testing Methods and AI, companies can achieve a higher quality of their software, detect and fix bugs faster and optimise their development processes. Investing in these new approaches is worthwhile, in order to meet the demands of an ever-changing digital world and ultimately gain more satisfied customers.