Which technologies are used by software testers?
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Software testing is a critical step in software development, and no software application must ever be released without the proper testing schedule mandatory for each project. In an earlier article, we described the duties of a software engineer in detail, and now we proceed to examine the different tools and technologies; these are evergreen tools and would always play a pivotal role in securing the quality of the software.
Software testing is an important focus to be taken care of as it would help you make the necessary changes and improvements in each software application. It would also help successfully meet the multiple challenges faced by software developers all over the world.
Given below are the top technologies in software development, some of these have been developed a while ago, but are still in vogue, and ever popular. Let’s check the top tools and technologies now:
The tools and technologies popularly used
1. Agile and DevOps
Software developers vouch for the usability of Agile technologies in software development because it is the perfect answer to the changing requirements in the software development world. DevOps, which is a set of practices that combines IT operations and software development aims to shorten software development cycles and release software with the highest quality.
Adopting both these technologies can definitely help in faster-to-market software applications, and release completed projects without a hitch. Through team collaboration, incremental delivery, continual planning, software development has gone to a whole new level, thanks to the technologies in software testing.
QAOps is the next thing to do after DevOps. It is an emerging practice that integrates Quality Assurance into the software delivery pipelines. QAOps approach places Quality Assurance at the centre of the delivery value chain. The QA team works directly with the development team and the operations team, and they work together by integrating the QA procedures, automation and a QA reporting dashboard. There are two main principles in QA:
- It must be incorporated into the CI (Continuous Integration) and CD (Continuous Deployment)
- Software engineers work closely with the team while building CI and CD.
3. Test Automation
Test Automation is an integral element in implementing DevOps practices. With this, you can replace manual testing with automated testing wherever possible. In most cases, test automation is under-utilised because while it can automate the tests and you can use the results to improve software quality, there are some areas where it is not properly utilised. The following are the different stages in test automation – unit testing, integration testing, end-to-end testing and exploratory testing. Test automation covers all the ‘testing’ processed in a quick and cost-effective manner with better results. Earlier, the tests were done manually and they were usually error-prone and time-consuming.
To make the best use of the test automation suites, the QA team will align with DevOps practices, and make sure the tests are automated with 100% code coverage.
The automation tools used presently are much more efficient than the previous ones. This was because the different teams followed their own test automation frameworks, and when new members came in, they had a hard time crossing the steep learning curve.
Today’s applications run on multiple devices with different moving parts so there must be something known as synthetic transaction monitoring, where tests are run in the production phase to catch ‘errors in action’ before it gets used on third-party platforms and your users detect the errors.
Some of the most popular test automation tools are Selenium, Katalon and TestComplete, and these tools keep evolving, so the testing becomes easier and more effective.
4. Utilising the magic of Artificial Intelligence
With AI and ML, you can achieve impossible feats in software development, and even meet several challenges that were once impossible. However, it is not yet the time to explore the full potential of AI and ML in testing because it is still in the early stages. But one thing is for sure, smart analytics and visualisation can help the teams to understand and detect the faults and focus on areas that need improvement. You can expect more precision in testing with AI and ML in the coming years, with full focus on quality, fault classification, test case prioritisation etc.
Since we have more software developers and more apps and more launches in the coming years, artificial intelligence in software testing makes it faster and more efficient, and automated testing takes it to a whole new level. With AI and ML in software testing, the entire software development cycle can be shortened. Tedious tasks in development and testing will now be fast through methods like reasoning and problem solving.
The developers and testers have their tasks cut out for them, and they don’t have to worry about which tests to run and not to run. ML can augment the skills of AI, by collecting and analysing huge amounts of data after testing is done, and this helps in the decision-making aspect of the data based on the previously collected ones.
While using AI and ML, it is important to know where to focus the testing on, so the data must be collected from all phases – the testing phase, of course, but also the requirements, design, implementation etc.
5. Scriptless automation tools
As the name suggests, scriptless or codeless testing is the method of automating tests using tools and not by writing test scripts. This is done by using test automation frameworks like Selenium, and they combine AI and ML algorithms, with excellent and consistent results. These tests are user-friendly and certainly save a lot of time and reduce maintenance costs.
Other scriptless testing tools that are used widely are Perfecto, TestGrid, Virtuoso, testRigor, Katalon Studio, Accelq, ZapTest and TestCraft, to name a few.
6. Big Data Testing
This is a very prominent testing tool that’s been widely used in various industries like banking, healthcare, retail, media, telecom, finance etc. As the name goes, big data testing is used for testing and validating big data. One of the specialities is the Batch Data processing test where the test procedures take place when the applications are in batch processing mode. There is real time data processing as well, and this is done when the application is in Real-time processing data mode. And then you have the Interactive data processing test. In this technique, you integrate the real life test protocols (exactly as how a user would interact with the app) to complete the testing.
There will be more test environments and data, thanks to the development of IoT. This is a huge relief for software developers because of the sheer size of softwares working in so many different kinds of devices, big and small. There is already a spurt in the cloud-based and containerised test environments, and there is much to look forward to.
What is software testing and how does it work?
Want to become a Software Tester?
The author: Sascha Thattil works at Software-Developer-India.com which is a part of the YUHIRO Group. YUHIRO is a German-Indian enterprise which provides programmers to IT companies, agencies and IT departments.
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