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Every software project starts with a vision. Everything later is built upon that. Testing, when integrated from the initial stage, ensures that the vision gets transformed into the actual product in the right way. Contrary to the popular perspective, testing spans right from the beginning to the end. Every stage has different aspects of testing involved.
In the initial stage, where there is nothing tangible developed, testing is mostly about having a critical mindset. Validating the logical implications of the requirements and their feasibility is also a form of testing. A project initiation may start with the client, but as more critical minds get involved, testing shapes itself.
Then, as more tangible outcomes are produced, like mobile app development and design, testing becomes more visible and doable with test cases and scenarios. And finally, it ends before launching the product. This article dwells upon understanding different types of testing in the overall software development and their contribution to enhancing the quality.
Testing begins small at an early stage. Developers build standalone programs or functions that fulfill just one objective. Unit testing validates their functionality as a solo entity. Any dependency on another program can be simulated through hard-coded values just to check if the functionality works.
Once all the single units have been tested, their integration testing is performed. This kind of testing checks how the whole system works when its different parts are integrated. A standalone program tested successfully earlier must be checked along with its subsidiary programs. They may have worked well independently, but break when tested as a whole. Integration testing ensures that different parts of the system communicate and interact with each other successfully, producing the final desired output.
While integration testing was mostly about checking if the separate programs co-exist harmoniously, system testing checks how the complete structure works. While unit and integration testing were performed at a developer’s level, system testing is performed at an architectural level. It is mostly about validating the architecture design when the tangible solution has been built according to it. Any flaws found in system testing require fixing at the architectural level.
User acceptance testing comes after system testing is passed. This testing bridges the gap between engineering and experience. All the testing stages before this had technical testers or developers involved in the testing. They may only test the solution from a technical perspective, as they applied while building it. But user acceptance testing takes it to the customer’s level. A fresh perspective is applied to the product, which is almost equivalent to a real-time user. Testing at this level requires all the possible scenarios a real-time user may encounter while using the product.
Performance testing is all about checking the performance of the product beyond its regular functionalities. It may include negative testing, edge testing, or stress testing. When a product is tested against adverse scenarios, its robustness can be measured. Stress testing ensures the product can handle high-volume processing that may come from peak traffic or heavy data processing. Any lag in the process or delay in loading the pages can be found during performance testing. These are the kind of defects that are not directly related to functionality but product quality at a much subtler level.
Security testing, as the term suggests, takes care of all the security aspects of the product. The privacy of data, secured connections, and API requests are checked to ensure there’s no loophole in them. Simulated attacks are made to test if the system can handle them and yet ensure the safety of the product and customer data.
While all the above kinds of testing are essential, when it comes to the approach of testing, there are two options: manual and automated. Most of the companies are migrating their testing process from manual to automated these days, and even to AI. Automation and AI testing are almost similar except for AI’s capabilities to even generate test cases automatically. Whereas in automation testing, the test cases must be coded in a programming language.
AI testing can be integrated right from the initial stages of unit testing to system and integration finally to user acceptance testing. Test cases can be generated on a tool that can be executed any number of times. testRigor, as an automation testing tool, is one such product that performs AI and automation testing exceptionally well. It can generate test cases through natural language commands and execute them in the tool itself. All you need to do is to integrate the tool with the application that needs to be tested.
Automation and AI approaches are especially useful for regression testing. Software often goes through frequent updates, and with each of them, the existing functionality must also be tested. Running these same tests again and again manually is a pain. An automated testing approach allows you to create test cases just once and run them as many times as needed with a simple click.
While there’s a certain sequence of testing that is followed from unit to integration, system to user acceptance testing, other kinds of testing may fall outside it. Performance testing can be done either in the middle or at the end, depending on the aspect being tested. Automation and AI testing span throughout the testing process and may act as an abstraction layer above all the stages of testing. With so many different kinds of testing, it may become challenging to orchestrate them all together. Hence, a proper strategy is needed to introduce each kind of testing at the right time in the SDLC.
While understanding the different types of software testing is important, their implementation should be done by a senior executive. That may be a QA director or a leader. It’s because they hold a holistic view of the overall testing process that ensures the product has gone through rigorous testing at all stages.
