Top 5 Software Testing Trends 2020

Throughout the year 2019, software testing field has been witnessing a challenging and thriving hot seat in market working towards the development of technology. Continuous software development and tech etched devices demands functional software shift-left testing approach as per the latest scenario.

Software testing trends are about to spend an important role in the upcoming software methodologies and the apt time of adopting digital technology into your work can paint a new look to software testing field. Automation in testing is no more getting new to testing team as 2020 will be the year of automation!

Gathered from the scratches the below list of technology testing field can shine brighter in 2020.

Here is the list of top 10 software testing trends in 2020:

• Machine Learning and Artificial Intelligence to Dig Deep in Testing
• Big Data Testing
• Testing in Agile and DevOps
• IoT Testing

Survey Feed

• August 2019 report from Nelson Hall’s states that next generation testing accounts for 24% of the software testing services spending and is the fastest growth offering with a 12.8% CAGR for 2018-2023. While the growth is driven by mobile testing, the accounts still value for approximately 75% of all next-gen testing spend.
• According to Gartner, by the end of 2019, the costs of developing the IT industry will grow to 3.76 trillion. This signifies that technology plays an important role in all our lives.
• NelsonHall 2019 survey highlights that software services is expected to grow by 5.6% over the 2018-2023 period resulting in financial growth from $23.0bn to $30.0bn.

Machine Learning and Artificial Intelligence to Dig Deep in Testing

Trails upon infusing the work of artificial intelligence and machine learning in software testing is one of the welcoming trends in 2020 that can bring about a wide range of possibilities and revolution in application development.

Application of artificial intelligence and machine learning can bring smarter way of testing and optimization in quality assurance.

Now, what machine learning can do in testing?

If artificial intelligence can bring advancement in recent technologies, the advancement machine learning can bring is one step further than AI. Infusion of AI and ML can turn today lags into leads.

Machine learning and AI testing can be expected to help below fields in 2020:

• Optimize test suites
• High risk points in application
• Configure test prediction
• Log analytics

How far QA team have applied ML/AI in testing?

Using the fantabulous combination of these two high techs, the up to date functionalities of any QA team in 2020 should include,

• Test objects detect
• Test quality prediction
• Prioritize test cases
• Defects classification
• Interaction with Application Under Test(AUT)

Even though the AI testing is at an early stage, it is expected to get matured in coming years.

Big Data Testing

By the end of 2019, Big Data testing has been trending topic and is still showering its acknowledgement through its support in various fields. Yes, Big Data is reducing the burden of handling diversified huge volumes of data into segments and make apt decision making processes.

When testing the terabytes of testing it is responsible to check if every byte of information are properly processing and the level of difficulty is one more concern to consider.

In 2020, we can expect more platforms that could simplify the data handling process and can promise to deliver the following:

• Improve the speed the data processing
• Minimize the application installation time
• Parallel processing of new and old data
• Eliminate the need to create new archives for every iteration

It is expected that Big Data testing is going to grow exponentially as a wide range of industries are chosen to enter into data oriented world. Forecast simply unfolds the rise of big data application in 2020 with more fascinating features and so does big data based testing.

Testing in Agile and DevOps

Keeping quality and faster release in mind, many enterprises are flocking towards DevOps and agile technology aligned methodologies. This has increased the need of improving the output quality and hence fine software/app testing become the common target for both fields.

Today testing has become a mandatory process to be a part of any agile project methodologies and DevOps is working on the improvement of reducing the time duration for testing. It is expected that in 2020, more companies will find DevOps as a reinforcement for a huge impact on how testing is being done.

IoT Testing

The prediction shows that by the end of 2020 there will be more number of smart devices approximately 20.8 billion. The estimation clearly points out the improvement of IT industry and so does the Internet of Things.

Yes, the Internet of Things is no more new to the market and is still blooming full fledged in the market.Every product is a bit of Internet of Things and the entire connectivity depends on internet and software.

Ultimately, this drag software testing into business and testers face a tremendous challenge on monitoring every communication protocols and the operating systems and all possible elements involved in a communicative device.

Seeing the wide range of IoT devices in real time application the QA team has to deal with ways to improve usability, performance and security.

Here are the following ways that are expected to be checked in forthcoming IoT devices:

• Check on the compatibility of the device
• Device connectivity
• Device Security
• Data integrity evolution
• Testing protocols
• Availability of device, authenticity and authorization
• Scalability

Blockchain Based Project Testing Adds One to Trending

Blockchain! Blockchain! What’s new about blockchain is the question that immediately pop up in every one’s mind.

Being a disruptive technology ever found in the world, Blockchain has it own advantages and disadvantages at the early time of its appearance. But today Blockchain is used in most of the application and has never been held low by any niche.

53% of surveyed organization reveal that technology has been the critical concern to their business and showed welcoming interest towards blockchain- based on Deloitte survey. They understood the need of the technology as when integrated with third party applications.

Again there arises the necessity of QA testing strategies to be followed while integrating with third party application. Hence further development and adoption of the technology will prolong the need of QA specialist in the field to ensure the quality and security of the devices/applications/software.

Conclusion

“The perfect functionality of a product lies in the hands of Quality Assurance”- Technology is becoming more advanced and so do assuring the quality. Incoming days all these advancements will help software testers to extend and upgrade their strategies in order to perform progressively in complex tasks.