Defining QA and testing
Prior to developing any content that shows technical or non-technical prowess, we need to research and analyze the data and the apparatus and post development of those contents (here content is anything from a technical or non-technical perspective), we require to acquire a process of testing or quality assurance (QA). As the name shows, testing and QA is all about 360°-wise checking the construction of that content, and the performance of the behavior of that content. In simple terms, how that software/application/content is functioning and whether it needs to be more amended, that answer lies with the testing and QA. It is now said to be the collar-bone of the software/application.
Why Is it important?
Similar to any process, this process has become a critical factor in developing the IT industry, starting from a supporting role-player initially. And it is not just from a business perspective, but from the perspective of the customers’ satisfaction. According to the World Quality Report, a software, web or mobile application, has to go through some critical testing cycles before entering into the market to keep the promises of the businesses intact.
How its role brings a significant impact
QA and testing do not rely just on making any software bugs free, rather, it needs to be customer-specific as well. How the end-user is clicking features or that software, how it is fulfilling their needs of using that software and so on, these factors are required to be focused more deeply. Hence, highly skilled testers and QA engineers technically drive the market with their testing capabilities and supporting any application to rule the market or just washed out from it.
Jobs in Testing
The changing trend in software testing and development also brought immense jobs and opportunity for the people. For example, Oprimes has become the largest crowd-testing platform in India that purely runs on the methods freelance testers residing globally. This SaaS platform is not just a boon for the people who are great in testing but also for the businesses as well.
What Exactly is Future of QA and Testing in the Market
With the development of Agile Software Development and DevOps, the implications of QA have been transformed from a supporting entity to an important one. It has been assessed and observed that in the near future, the goals and approach of organizations setting up the testing units more thoroughly and hence, more employment opportunities can rise more frequently. With this, the role of testing in providing services at high velocity have also been taking its place. The major developments are IOTs, AIs and ML, and Deep Learning. They are said to be the real future of not only the business, IT sector and others, but also for the testing and QA sectors as well. The good analytical and observational skills, with a blend of slight technical skills, of the testers will play a key role in amplifying these technologies in the market.
Future of QA and Testing in AI
Although the discussion of differences between AI and IOTs is said to be ongoing, the role of testing in both of these entities is still drawing an important and undisputed conclusion. With the advancement of AIs (or say IOTs), the advancement of automation in testing has also made its place. Considering one case study over ChatBot, we have seen a lot of changes transferred from manual testing to automated one. And the exciting thing is their inter dependency at times. When we test an AI-driven tech, it is a possibility that we have used AI-driven testing methods also. Hence, we can say that the automation tools the test cycles are going to have can use AI methods to test some AI-embedded techs, for example, ChatBot.
Role of Testing in ML and Deep Learning
It is an exciting and latest debate though. Deep learning is said to be a sub-field of machine learning where an artificial neural network, which uses complex algorithms, similar to the human brain is made to mimic the learning methods of a human brain. When the prospects of any network is made, the testing based on recent testing trends are reported to be required. And where we can see the glimpse of the innovations in testing and QA sectors. Moreover, the analytical approach is immensely important to understand whether the neural network is compatible with the real world. Hence, the deep neural nets that resembles the human-world interactions will require the same, or say extensive, way of analysis a tester uses while performing software testing.
Testing Possibilities in Blockchain Technology
Blockchains are famously known as decentralized ledger tech, and testing approaches and vision in these technologies is a long, latest and ongoing discussion.
Being said, the testing phases such as block testing, performance testing, API testing, security testing, etc – all similar to other testing cycles – are known to be possible testing and QA activities that any blockchain based technology will go through and need to pass, we must say.
Some blockchains testing tools also come across with the testers routine. These tools are Ganache, Etherium tester, Hyperlaedger composure, etc.
Lastly, we can watch and analyze the continuing trend that mainly focuses on the importance of QA in blockchain technology and if passed, we can see this trend in Non fungible tokens and other features also.
Let’s Discuss some Challenges
Everything we have gotten brings some challenges as well. Let we mention some current and upcoming dilemmas we might have in uploading the new approaches of testing and QA discussions. These might not be the final version of challenges library but yes we can start from these.
- Analytical testers: With the increase in the methods and frameworks in the test cycles, more analytical minds are needed. Sometimes it is difficult for the platform to find the right talent.
Automation and comprehensive approach: If, at any point of time, some automation is required or possible for the test cycles, any team would face issues with the approach with which they move forward. However, these are minor issues but as we move in the era of DL, AI and ML, we can expect a rapid increase in dilemmas towards the plannings and all we will require is a more detailed approach.