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Top 10 Software Testing Trends to Look Out For in 2018

software testing trends 2018

2017 witnessed the introduction of advancements in testing such as AI (Artificial Intelligence), Machine Learning, Adoption of DevOps, cloud computing etc. Since they were at introductory state many organisations and Software Testing companies have still not adopted it.

But there will be a huge change in 2018.

If you are curious enough to know about what’s going to happen, go through this blog and find out what they are.

1.  Prominence of DevOps

We are at a juncture of time where product has to reach the market as quickly as possible. However, quality is something which no one is willing to sacrifice whatever the urgency is. For this to happen the best possible way is to rely more on DevOps method. Basically the idea behind DevOps is to create seamless integration between departments.

Let’s hear what IBM distinguished Engineer and Solution Architect Sanjeev Sharma has to say about DevOps

app testing

Video Credits : developerWorks TV

Obviously software testers will be a crucial factor; however, they will share multiple roles rather than the traditional way of planning and execution. Testers have to be a part of continuous testing process, writing and generating reports and to encourage team members to be a part of the process.

It is expected that more Software Testing Companies will adopt DevOps method in this year owing to the efficiency of the process.

2. Test Automation Shall Reign

Automation has always been the reason for a process to become fast. Same is in the case of Software Testing. Automation of test will assure that the testing process has been carried out swiftly, effectively and flawlessly. But the issue that has been prevailing now is the inability of testing processes to connect. 2018 will see fully integrated testing process at a deeper level as it has become the necessity of the agile software testing world.

3. Mobile Testing and Mobile Testing Automation Shall Be the Star

It has been estimated that around 95% of app customers uninstall their app owing to various reasons. Among them, technical issues with the app are said to be the biggest. So it is obvious that mobile based testing will have all time rise.

Since Automation is the best methodology to be implemented in this particular scenario, testing engineers will go for automation than any. Unfortunately, at the moment there is a lack of efficient methodologies, devices or even tools for testing as gazillion types of mobile devices are available in the market.

2018 will witness the emergence of varied tools for the process which will make test automation process efficient than ever.

4. Open Source for all

Tools like Selenium, SoapUI, Cucumber, VirtualBox, Apache etc. are gaining importance than any other. The one thing that is common between these tools is that they are built on a open source platform. These tools can perform various testing types such as, Functional Testing, Security Testing, Performance Testing, etc. with ease and that too with unbelievable perfection and efficiency. 2018 will see more organisation and companies relying on open source tools than that of commercial ones.

5. Shift of Performance Testing to Performance Engineering

User Experience and success of an app is directly proportional. Higher the UX higher will be the success rate. In order to provide the best UX, performance engineering is the best option rather than performance testing. Performance engineering mainly focuses on architecture, design and implementation of software. Etc.  The most astounding benefit of performance engineering is that it assures less development time and performance requirements on time.

6. Analytics for Smarter Software

Applications are not just informative or amusing nowadays. They are now put to use in diverse industries to automate various processes. So it is evident that to test software’s like this smarter tools are required. Since integration of software and modularity is the next big thing, the need for security, performance and functionality testing will be in huge demand.

With the integration of analytics to testing framework it will be able to predict possible outcomes of a test, detailed real time data, visual depiction of data etc.

 7. IOT will have its foot hold in Testing Too

Cloud Computing is going to be one of the most important advancement that’s going to happen for testing this year. IOT simply means connection of multiple devices which can exchange data between each other and work harmoniously. For it to do so, testing is essential to check whether factors like, Security, connectivity, performance, compatibility etc is in perfect condition. 2018 will witness IOT and its application extensively for testing purposes.

8. Big Data Testing will be Big for Testing

Big data is large volume of data which can’t be processed by a traditional database. For instance, Amazon has got millions of product to them and they have millions of visitors each day. All this data needs to be processed on the demand of the customer so that there will be product list and suggestions. For doing so, database needs to flawlessly process volume and velocity of the data in it.

Test-your-WebApps-for-better-stability

For this to happen, databases has to be tested especially the performance of it. 2018 will see emergence of high-grade analytical tools and frameworks to test these databases.

9. Omni-Channel Application Testing will be the Need of this Time

It is indeed a difficult task to test applications that are supposed to work seamlessly with multiple devices and in multiple platforms. 2018 there will be much more diverse tools and methodologies to tackle this situation. Stability of the test environment and management of test data are the most important issues with the problem which to an extent will be rectified by the arrival of new technologies.

10. Artificial Intelligence will increase the Efficiency of Testing

Smart test automation tool will mark a period where testing will be efficient and flawless than ever. Both Artificial Intelligence (AI) and Machine Learning (ML) will be put to use simultaneously to create tools that can predict application behavior, to build advanced test case scenarios, offer smart analytics etc.

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