Manual testing vs Automation
Quality Assurance (or QA) is aimed at checking the quality of a product throughout its design and development cycle. QA ensures the smooth conduction of the processes in the application and all its components. It helps the development team to detect any failures in application systems and avoid them in the future. This significantly contributes to product quality and customers’ satisfaction, as well as brings benefits to the business.
The concept of QA thoroughly alters the approach to application testing. Today, the end-to-end model is of high priority when the testing is performed over the whole lifecycle of product development. This means that QA takes place on the levels of separate units, the application programmer interface, and the user interface. And all these various tests can be automated or run manually.
Even though many companies still employ a manual approach, QA automation has grown in popularity for the last few years, especially within teams using DevOps and Agile practices. Why is that so? Well, more than half of the companies that had introduced automated tests in application development pointed to its usefulness and the value it had added to their business. Those are just a few noteworthy strengths of automation in QA processes.
Benefits to businesses and their customers
QA automation has substantial advantages in comparison with traditional testing methods. One of the most important issues it solves is inefficient time use. QA organization helps companies to distribute employees’ working time and human resources more efficiently.
Previously, testers had to run the testing processes manually, registering all the deviations in the logbooks. That took valuable time from the experienced team and didn’t allow them to concentrate on more complex tasks. Now, with test automation, QA specialists can spend more time working on improvements of the existing automated tests or pay more attention to testing that requires human intervention.
Yet another beneficial effect of QA automation is higher product quality. Automated tests are performed throughout the entire design and development process, starting with its initial stages. Thus, the testers see the weak points of the systems while the code is still being written, not just at the end of production.
AI-based techniques deal with repeated inaccuracies, and this increases the quality level as well. In addition, automated tests can be reused in different projects and hence prove themselves to be somewhat cost-saving.
Manual testing vs QA automation
Followers of the manual testing approach claim that far from all processes can be automated. And these specialists are right. There are tests where the manual approach is indispensable, for example, exploratory testing.
Other cases when traditional solutions are preferable are those involving human logic. This refers to application usability and feedback on the user interface. For example, to know if a bank transaction is fast and securely done via a mobile app, a user should actually perform it.
QA automation, in its turn, successfully handles repetitive actions and routine tasks. This makes it convenient for large projects with lots of steps. That’s where automation testing can be effectively complemented by manual testing depending on the specific characteristics of every single stage. Such a combination allows companies to keep up with fast-paced production as the quality standards rise and the time for product development shortens.
Security testing as a compliance tool
Data protection has never been such a trending topic as now, in light of the advancement of digital technology. Online banking, telehealth, and other cutting-edge solutions involve exchanging huge amounts of data via the Internet. Therefore, it’s no wonder that multiple data protection policies are constantly arising. Automation testing reveals shortcomings in security even at the initial levels of application development. Such operations as identity verification or access control can be easily automated too. This eliminates human errors while carrying out seсurity tests and noticeably increases product quality.
Most common challenges in implementing QA automation
So what are the typical hardships the companies face when introducing QA automation into their workflow?
1. Rapid change of applications
Each year, companies launch dozens of various end-user programs. In the meantime, applications change. Automated tests are not always able to catch up with all these modifications. The solution to this problem would be to raise the experience level of QA specialists, to upgrade the existing automated test techniques, and to create more advanced ones.
2. AI-based technology mastering
AI-based solutions used in automation are still new for QA practices. When well-mastered though, AI algorithms are used successfully for risk assessment, reduction and simplification of a large amount of data, and distribution of tasks according to their relevancy.
The companies that seek to efficiently incorporate AI technology into their test activities should encourage the growth of AI skillfulness among their staff. The introduction of such job positions as AI-proficient QA testers, developers, and engineers can be a good solution.
3. Need for a better test environment and test data management.
Gaps in test data management can be filled by establishing a unified data repository. Thus, all the members of the development team will work together and have free access to constantly changing test data. Speaking about the test environment, companies should increase the number of working hours dedicated to testing. The checking process can also include a wide scope of scenarios, such as diverse devices and operating systems.
Each companies’ products are unique, and it means that their QA approaches are unique too. It’s up to each team to decide what testing methods to use depending on their size, product portfolio, and quality strategies. However, test automation undoubtedly becomes more and more popular, and its implementation brings businesses substantive benefits. QA outsourcing companies such as Andersen will be glad to consult with you on which individual solution suits you the best.
Interesting related article: “What is AI?“