“A System is never finished being developed until it ceases to be used” - Jerry Weinberg
Within the Agile methodology, Testing is one of the crucial DevOps levers, which is utilized by organizations for ensuring that the end-users are satisfied with the manufactured products. In order to achieve this, Companies have been building delivery pipelines, containers and ecosystems for delivering software faster. So what is the future of Testing in Software and that of the Software Testing Industry in general?
In spite of all efforts, QA teams are still faced with several bottlenecks and glitches. Hence, the Software Testing field is marked by continuous pressure to innovate, resulting in technological progress within the testing landscape.
Thus, there do exist ample opportunities to rethink and reconfigure the work we do and the way we do it. All these potential changes, sums up the future of Software Testing.
In this blog, we shall look at the future of Software Testing in terms of the future scope of Software Testing as a field. We shall also consider the value of Test Automation as an important factor in determining the future of Software Automation Testing.
What is the future of Software Testing?
In trying to comprehend the future scope of Software Testing, it is important to understand that future of Software Testing will inevitably be conditioned by the upcoming technologies and the needs of the time. There is no denying the fact that there will be greater emphasis on quality through quality assurance, in order to ensure a delightful brand experience.
Organizations shall strive to achieve the dual combination of delivering the best value at best quality. Additionally, the future of Testing in Software is expected to be dominated by Test Automation using Artificial Intelligence and Machine Learning.
Let us discuss some of these key software testing trends which are likely to influence the domain of Software Testing.
Future of Software Testing: A look at Influential Technologies
Artificial Intelligence combined with Automation helps in equipping Software Testers with augmented efficiencies. AI is being increasingly deployed in detecting testing flaws as well as lessening human intervention.
This is extremely useful in determining the functionality and performance of a product at the data-server as well as machine level. Additionally, while considering future scope of Software Testing, it is important to remember that Artificial Intelligence will have a lot to contribute towards the processes of analytics and generation of reports.
In this respect, it will provide for:
Test Suite Optimization: Eradication of unnecessary test cases
Defect Analytics and Log Analytics
Differential Testing and Declarative Testing
Machine Learning (ML) is the sub-category of Artificial Intelligence (AI) which is based on the principles of Computational Learning Theory and Pattern Recognition. It makes use of algorithms (which are regularly updated through human input) in order to arrive at decisions.
The implication of Machine Learning for the future of the Software Testing world is granting of autonomy. This implies that by making use of testing experience from the past as well as existing application usage; smart machines will help in building, running and interpreting tests without human intervention.
One of the biggest advantages of Machine Learning in the future of Software Testing, will be to make use of extremely complex product analytics data for detecting and anticipating the needs of the user. This is facilitated through observation of every user interaction on a software application and understanding of their experiences and issues.
Agile and DevOps
Agile methodology emphasizes on iterative and incremental development and delivery, where software is developed and tested in short iterations. Agile methodologies require continuous involvement of testers throughout the software development lifecycle, enabling them to identify and address issues early on.
DevOps, on the other hand, emphasizes the integration of development and operations teams, promoting communication, collaboration, and automation across the entire software development and deployment process. DevOps enables a continuous testing approach, allowing testers to test the software continuously and deliver high-quality software faster.
The combination of Agile and DevOps practices creates a culture of continuous testing that emphasizes the importance of quality throughout the software development lifecycle. It enables the early detection of defects and the ability to respond quickly to changes in requirements, ensuring that software is delivered on time and meets the needs of end-users.
The framework is based on the principle of continuous development wherein inter-team communication and collaboration is believed to advance specifications and solutions. Agile is being combined with DevOps in order to shorten the Software Development Life Cycle from system development to operations.
User Experience Test
One of the crucial concerns for any organization is end-user satisfaction. If the product fails to be user-friendly or does not adequately meet the needs and expectations of the consumers, it is doomed to failure. Thus, the future scope of Software Testing will surely include increasing cases of User Experience Testing.
This kind of testing which generally involves actual users, help in testing diverse aspects of user experience. This helps in determining the best course of interaction between a product and its audience.
It might include testing for first impressions, time on page, trust, comparison and so on. The objective is to identify possible defects and consequently improve upon them.
IoT (Internet of Things) Testing is another important software testing trend for the future because of the growing adoption of IoT devices in various industries such as healthcare, transportation, and manufacturing. IoT devices are becoming increasingly common in everyday life, and they need to function reliably and securely.
IoT Testing involves testing the software, hardware, and communication protocols used in IoT devices to ensure they meet functional, performance, and security requirements. It involves testing different aspects such as sensor functionality, network connectivity, data accuracy, and user interface across various devices and platforms.
The complexity of IoT systems, combined with the need for high reliability, security, and interoperability, make IoT testing a challenging task. IoT devices may have different hardware, firmware, and software components that need to work together seamlessly. Testing of these components and their integration is essential to ensure that IoT devices work as expected and can communicate with other devices and systems.
Failure of IoT devices can have serious consequences, such as patient safety in healthcare or road safety in transportation. Effective testing of IoT devices can help to ensure their reliability, security, and compliance with regulations.
Automation Testing is one of the prime aspects of the future of Software Testing and hence it was sought to be discussed in a separate section. While there is no denying the fact that increasing adoption of Test Automation would not imply the end of Manual Testing; it would definitely help in overcoming some of the crucial drawbacks of solely relying on Manual Testing.
Automation Testing has been held to be beneficial in shortening the testing cycle by providing for faster product delivery. Moreover, it helps to provide for greater test coverage and early detection of bugs.
While discussing the future of Software Automation Testing, it is important to remember that the face of Automation Testing itself is bound to undergo a change in terms of adopting a more risk based approach to testing.
When we talk about Automation Testing being the force of the future, the emphasis will definitely shift towards Codeless Test Automation. This idea is based on facilitating business users as well as testers to automate test cases without necessarily being proficient in coding.
Since this reduces the time which is usually spend on understanding the code, it does help in automating large test suites quickly. With decrease in automation time, the speed of delivery goes up and it helps in earlier detection of bugs.
As a matter of fact, the future of Software Automation Testing will rest on the usage of high-end AI technology coupled with visual modeling for building Codeless Testing Tools. These tools generally facilitate the writing of test cases in easy language such as English with the help of NLP, which is then converted to code in the backend.
Thus, Test Automation would no longer be a developer focused task. Rather it would be much broadened in scope as each and every non-technical person too, would be able to write and author effective test cases.
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The given list of trends does not represent an exhaustive list of factors, which alone would shape the future of Software Testing. The future scope of Software Testing as a domain is bound to be influenced by the rising importance of several other technologies as well, such as Blockchain, Cyber Security and so on.
However, herein we have focussed on the more generalized trends which would be the key driving factors in molding the future of testing in software.
It is evident that the role of a Software Tester will go through several twists and turns as the domain of Software Testing, itself evolves and develops. Those aspiring to be a Software Tester, do read our blog on “How to become a Software Tester?: Let us Find Out”
The future of Software Testing is clearly geared towards the Agile and DevOps model, based on a closer nexus between the development, operations and testing teams. This has only accelerated the demand for individuals with development as well as testing capabilities. These individuals are Software Development Engineers in Test (SDETs).
We, at Syntax Technologies, provide you with the lucrative opportunity of capitalizing upon this in-demand job position by developing expertise in the field. Read more about our SDET training course.