You're faced with testing challenges. How do you choose between manual and automated approaches?

Automation testing is ideal for scenarios that are repetitive, have stable and consistent test data, and hold significant business value.

If you are facing testing challenges and time constraints as well, then going for the traditional test automation will not work. You will require time, effort, and cost to set up the test automation initially. On the other hand with manual testing you can get started right away, but miss on test coverage due to limitations of the human capacity and time constraints. So what is the solution? Solution is simple, go for intelligent AI-driven test automation tools that take away the programming pain away from the test script creation and maintenance. Advanced AI agents such as testRigor help you create/generate test cases in plain English. Your manual QA team can achieve great test coverage, quickly and efficiently through such tools.

Evaluate the skill set of your team. If the majority of your team members are experienced in manual testing, it might be prudent to continue with manual testing. Transitioning to automation testing would require hiring new resources, which may not be cost-effective for the company. If you decide to leverage the current team for automation testing, it will necessitate providing them with the required training, which might also involve significant costs.

L'idée sous-jacente de l'automatisation de test, est l'espoir d'un retour sur investissement rapide en ayant (idéalement) plus qu'à cliquer sur un bouton pour lancer, sans intervention humaine, un ensemble de test. Bien souvent ce calcul de ROI ne prend pas en compte le temps nécessaire à automatiser un test, et le temps nécessaire pour le maintenir. Une matrice de calcul permet d'estimer à partir de combien de lancement un test automatisé est moins couteux qu'un test manuel. Les arbitrages financiers doivent en référer.

For adoption of test automation or scaling-up the existing scripts, you need automation testers well versed with the programming language (if you are using Selenium or other Selenium based frameworks). If you are planning to increase the test coverage drastically then you might need to hire few more team members as well. However, there are better solutions available. With generative AI-powered testRigor you can turn your application specs into automation test cases directly. Such tools let the manual testers work as skilled test automation engineers, with almost no learning curve. Your tetsing team can utilize their testing expertise in creating robust test cases rather than learning a new programming language, & test script maintenance.

Test stability refers to the reliability and consistency of test results over time and under varying conditions. A stable test is one that consistently produces the same results for the same inputs or conditions, without unexpected failures or inconsistencies. Achieving test stability is crucial in software testing to ensure that defects are reliably identified and that the testing process itself does not introduce variability or false positives. Stable tests contribute to the overall reliability of the software by providing consistent feedback on its functionality, performance, and usability.