Top Trends To Revolutionize Software Testing In 2021

Latest 9 Software Testing

The year 2020 might have been generally chaotic, but it did show us that technology could sometimes be the ultimate solution to our problems. However, with the year behind us now, we need to learn from our digital experiences and move forward into 2021. The evident aggressive continuation of digital transformation has given rise to the need for better QA trends. Some fundamental needs that are defining automated software testing trends today are:

  • Increased awareness resulting in enhanced involvement as the focus shifts from “What to test” to “how” and “why”.
  • From being suddenly exposed to new use cases to using any test tool available to judge a software’s design and functionality, the year 2020 has taught us the importance of exploratory, risk-based, automated testing and this will form the base of software testing in 2021
  • Focus on bettering performance and load testing techniques
  • Security testing will continue to be a priority
  • With digital transformation increasing its coverage, ensuring app accessibility becomes paramount
  • An unprecedented increase in native app creation enhances the need for a good testing strategy exclusively for these apps
  • Apps dealing with virtual conferencing and meet-ups need advanced add on features and dimensions to facilitate seamless virtual interactions.

Consequently, modern testing solutions are changing. They are revolutionising and evolving. QA has become so much more than just finding errors and bugs. Today, it is a complex technical process involved in:

  • Product idea evaluation
  • Behavioural predictions
  • Threat and opportunity analysis etc.

Thus while well-known testing methods still form the cornerstone of software testing, certain new trends are set to redefine the concept of software testing in 2021. They include:

1. Agile and DevOps

Agile is a software development approach that emphasises the need for team collaboration, continuous planning and learning leading to incremental delivery. Therefore, for Agile, software testing is an integral and inevitable part of SDLC.

DevOps looks to shorten the SDLC and enable end-to-end process management by combining two key verticals of Dev or development and Ops or operations. By erasing the existing boundaries between development, operations and testing, it:

    • Increases speed of deployment
    • Cuts downtime to market  
    • Promotes better ROI

Thus when adopted, these processes help shorten SDLC and enable the release of qualitatively superior apps. These are not relatively new, but adopting these practices to adapt to the current times will certainly be a software testing trend worth watching.

2. QAOps

This has started trending very recently. It combines QA techniques with IT operations or Ops to guarantee incremental delivery without compromising the app quality. The core of QAOps deals with integrating QA techniques into the CI/CD pipeline to enable better communication and collaboration between team members. Key benefits of this ideology include:

    • The development of a superlative product
    • Increased ability to meet deadlines
    • Quick addition of new features etc.

New thought processes are also looking at the possibility of integrating QAOps with DevOps. This will effectively combine continuous testing with CI/CD. The resultant benefits would be an accelerated product-to-market timeline and quick error detection.

3. AI and ML

The potential of AI and ML have yet to be fully realised. Hence, the trend of incorporating AI and ML to automate business processes will continue in 2021. Statistical predictions when putting the popularity of these in absolute terms state that:

    • AI is to grow at a CAGR of 36.6% from 21.5 billion dollars in 2018 to 190.6 billion dollars by 2026
    • ML market is slated to grow at a CAGR of 44.1% from 1.03 billion dollars in 2016 to 8.81 billion dollars in 2022.

This growth is primarily because they:

    • Facilitate the use of real-time data for better business decision making
    • Enhance the quality of automated software testing by enabling quick error detection etc.

Leveraging AI and ML enables QA teams to keep up with frequent app releases and improve automated software testing strategies. By using redundant test case detection, AI-powered test apps optimise test suites. Additionally, analysis of keywords present in the RTM maximises its test coverage.

Currently, AI is being developed for use as part of the self-healing and visual testing mechanisms present in automation testing tools. With AI-enabled visual testing, fewer written tests would be required for functional testing of the user interface.

The development of the AI-powered self-healing mechanism will reduce costs incurred in automated test creation, decrease test maintenance and effectively fix test script issues quickly.

Intelligent automation is impossible without ML. While human intelligence is still the ultimate tool available for forecasting consumer behaviour patterns, predictive analytics from ML enabled apps can be used to amplify human intelligence by detecting unexplored areas within the app.

For now, the use of ML in software testing is just an exciting possibility. The future will, however, witness analytics-based initiatives gaining traction. This will further enhance the identification of problematic areas and bring them under test coverage.

4. Scriptless Test Automation

Today, different types of apps are being developed and released with increasing speed. This means testers need to keep learning new and complicated programming languages whenever required. It is a time consuming and frustrating experience. However, scriptless test automation prevents testers from spending extensive hours on programming.

By using scriptless test tools, testers can automate robust, reusable tests by incorporating AI/ML algorithms within a self-healing mechanism. Today, scriptless test automation is being increasingly endorsed as a very prominent software testing trend because this process:

    • Is user-friendly
    • Reduces maintenance cost by requiring less time and effort
    • Helps fill technical level gaps
    • Gives fast results

5. Big Data Testing and IoT

This crucial software trend will positively impact diverse industrial sectors by enabling them to:

    • Validate information
    • Improve market targeting
    • Take data-driven marketing decisions
    • Form appropriate, result-oriented strategies

Today, Big Data is rampantly used across industries like finance, healthcare, retail, media, banking, telecom etc.

Big Data deals with data generated from different sources in huge volumes at a very high velocity. Since it cannot be tested using the traditional methods, there will be an increased demand for functional, performance and data quality testing in 2021. Additionally, a rise in IoT enabled apps has resulted in the enhanced generation and accumulation of diverse data in huge volumes.

The complexities associated with the growth of the IoT network pose quite a challenge for the QA market. Combinations now need to be tested across innumerable different devices, OS, platforms, protocols etc. Thus, the year 2021 will see an increased demand for functional, usability, security, performance and compatibility testing also.

6. Security Testing

Technology grew at breakneck speed in the past year and this speed is expected to increase in the current year. As a result, huge amounts of data will be generated. While some of it might be inconsequential, most of it would be critical and prone to hacking and tampering. Cyber-security and security compliance testing would continue to get priority in the year 2021 to ensure that:

    • Data breaches, code errors and leaks can be prevented
    • You have the opportunity to patch-up your weaknesses and vulnerabilities before the bad guys get the hang of it
    • You are better prepared to face downtime when it happens etc.

Performing regular penetration testing is good for building a good reputation. It also strengthens trust between clients, customers and organisations.

7. Shift Left Testing

Many people have been advocating shift left testing in recent times. The pandemic hastened its implementation by exposing app vulnerabilities when forced to work under stress and duress. Shift left testing is an approach that advocates performing tests early in the SDLC and enabling everyone own quality in their spheres of influence.

Traditionally in an SDLC workflow, requirements occupy the left side while testing and delivery the right side. This proved to be time-consuming, resulted in escalated costs and delayed bug detection. Implementing the shift-left approach helped QA, development and product teams to collaborate and work proactively in tight coordination to:

    • Judge the feasibility of software codes written
    • Ensure their proper and bug-free development

Organisations benefit from this approach as it enables them to deliver quality products within reduced timelines.  

8. Test Automation

The writing is very clear. Continuous delivery is impossible without automated software testing. Adopting the Agile approach has enabled faster detection of bugs and defects. Thus, test automation increases QA efficiency and plays a vital role in the implementation of Agile, DevOps and CI/CD. Further, it benefits software organisations by:

    • Speeding up release cycles
    • Improving quality of software released
    • Increasing test coverage
    • Providing feedback loops continuously
    • Saving time mostly on repetitive tasks
    • Reducing manual intervention

By enabling quality checks at every stage of SDLC, test automation empowers QA engineers and helps them achieve the required test frequency.

However, this does not mean that manual testing becomes irrelevant. A good comprehensive strategy is one that combines the benefits of both manual and automated software testing thereby making QA teams more effective and efficient.  

9. Blockchain Testing

This is a fast emerging and advanced technology for providing secure encryption. The fact that Blockchain-powered apps enable expansion of the decentralised data structure without changing it makes it extremely resistant to frauds and hacking.

For all enterprises around the globe that need to communicate and store sensitive information securely, blockchain technology implementation is the answer to all their cyber security woes.

Simply speaking this technology is a programmable incorruptible digital ledger that can virtually facilitate and record not just economic and financial transactions but everything of value. However, there are certain challenges associated with its implementation like:

    • High adoption costs
    • Inconsistencies in legacy system integration
    • Compliance and privacy issues etc

It also comprises certain intricate steps that involve data validation, its encryption, decryption and successful transmission. A single hitch anywhere collapses the whole system and causes it to stop working. Thus, improvement in blockchain testing is an important business-critical software testing trend for 2021.

Software testing has gained traction as the need to release high quality, bug-free apps within shorter timeframes gains momentum. The above software testing trends are slated to change the way the world currently perceives QA testing as well as weave in quality into the core development efforts in the most effective manner. Thus, software development companies need to take immediate cognizance of these software testing trends and qualitatively improve their QA procedures.

About the Author

QA InfoTech

QA InfoTech

Established in 2003, with less than five testing experts, QA InfoTech has grown leaps and bounds with three QA Centers of Excellence globally; two of which are located in the hub of IT activity in India, Noida, and the other, our affiliate QA InfoTech Inc Michigan USA. In 2010 and 2011, QA InfoTech has been ranked in the top 100 places to work for in India.

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