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Top Software Testing Trends to Focus in 2021

The importance of software testing has escalated worldwide due to the Covid-19 pandemic forcing people to shift most of their work dealings from home. Therefore, the need to upkeep applications, we need software testing that directly maximizes business operations.

In the earlier days, software testing was limited to finding errors and offering product improvement recommendations. These days, the impact of technological advancement has transformed the approach abided for testing and quality assurance. The usefulness of various tests across the SDLC (Software Development Life Cycle) indicates this process’s extensiveness.

Why is Software Testing Gaining Importance?

ImpactQA - Software Testing Trends & ModificationsThe count of applications used by organizations is growing which is further fueling the cost related to safety and security measures. This is the reason why software testing is under the spotlight for all good reasons. As per the World Quality Report, 60% of the organizations agreed that cost is the biggest test environment challenge. Furthermore, testing finances are now merged together with software engineering finances since QA is actively implanted in the development cycle. As a result, the majority of the businesses have started acknowledging the importance of quality assurance and have put their trust in software testing companies for offering specialized assistance.

“The principle objective of software testing is to give confidence in the software.”

This year has witnessed noticeable changes within the software testing arena. Several major players have broadened their operations to adapt to the remote working model. Based on all such tweaks and upgrades, the latest software testing trends already in motion and the ones set to impact in 2021 are cleared discussed in this blog. 

Fresh Opportunities with Artificial Intelligence (AI) and Machine Learning (ML)

The primary purpose of incorporating Artificial Intelligence in the software testing model is to achieve a smarter testing approach. The enhancement in reasoning and problem-solving skills is a result of AI & ML, which automate and upgrade the overall software testing process. Furthermore, the dependency on manual testing is reduced with the availability of artificial intelligence.

In 2019, AI & ML together worked suitably to speed up the test automation process. Moreover, these technologies’ combined effect was also reported to improve test quality, classification of defects, and interaction with an application under test (AUT). It is expected that in the following year, AI & ML will take charge of more complex tasks within the SDLC and further encourage test creation and test execution.

Also Read: What is the Impact of Artificial Intelligence on Software Testing?


                              QAOps & Its Popularity in Software Testing

Transformation to QAOps

The precise meaning of QAOps is the integration of quality assurance (QA) and CI/CD (Continuous Integration/Continuous Delivery) channel. In simple words, this model stresses on integrating the software process with the CI/CD pipeline. Based on this arrangement, the QA team must close work with the operation team and development team.

Under QAOps, DevOps is merged with continuous testing to ensure any software changes are readily forwarded to the CI/CD pipeline’s production phase. It prevents the hassle of conducting software testing at vague intervals without any clarity on quality issues.

Performance Testing Driven By Performance Engineering 

The performance testing of applications has reached a higher level where security, business value, configuration, and usability are vital benchmarks. Different software testing service providers have revamped their priorities inclined towards a user-centric approach to match up with this tendency. It includes the prevention of potential performance defects at the initial stages of the product’s life cycle. The advantages of performance engineering and testing engineering have transformed performance objectives for an application, including speed, stability, and scalability under varying circumstances. The system is now analyzed for discrepancies with the search operation thoroughly conducted to find their root causes starting from the development process. 



ImpactQA - Performance Engineering & Software Testing

Popularity of IoT & Big Data Testing

At present, the demand for the Internet of Things (IoT) has transformed into a global situation. We are living in a connected world that is filled with millions of devices that are directly responsible for increasing testing activities. As we can see, the components to be tested vary between platforms, devices, operating systems, and protocols; the overall software testing & QA market is likely to experience escalated demand for performance, security, usability, and compatibility testing.

A similar situation can be seen in terms of Big Data. With the rising demand for IoT-enabled applications, there are better opportunities focused on widespread data volumes required and accumulated for larger projects. Therefore, testing of big data certainly improves an organizations’ capability to confirm data-driven decisions. Furthermore, its effect can also be seen in refining market strategies with a broader perspective. 

The above-mentioned software testing trends are aligned with growing business needs to bring positive outcomes. The proliferation of AI, ML, and IoT has already created a major breakthrough and prominent upgrades related to software testing are likely to occur in 2021. QAOps and Performance Engineering are the promising segments gaining higher traction from leading software testing companies like ImpactQA, to reap bigger and better benefits in the coming years.

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AIOps Role of Testing Professionals for Successful Implementation

The excellence of Artificial Intelligence (AI) has revamped the software testing arena. This is evident with the recent propagation of “AIOps,” which effectively incorporates artificial intelligence across IT operations. On a much broader canvas, we can also view it as the constructive method of using machine learning or data science to resolve IT-related discrepancies.


Presently, artificial intelligence to supervise multiple IT functions, such as performance monitoring, service management, remediating blackouts, etc., is gaining popularity. Therefore, it is slowly becoming imperative to get hold of AIOps for ensuring fast-paced software delivery.

Growing Demand for AIOps

The extensiveness of AIOps as part of the software testing plan is positively responsible at the global level. This is mainly due to this process’s usefulness and its ability to assist the quicker release of complex applications. Many organizations have greatly benefitted as AIOps can handle vast amounts of data without much worry.


ImpactQA- AIOps Process Roadmap


Machine learning (ML) and Big Data are seen as the two primary components of AIOps. Therefore, this unites data from monitoring and further assists in automation tasks accomplished in a streamlined order. Numerous companies planning to remodel their testing approach have placed their trust in AIOps to receive useful insights. According to recent research updates, many large enterprises have exclusively preferred AIOps and sophisticated monitoring tools to examine applications and associated infrastructure. Such operations are a great benefit to the organization as it helps enhance overall business value.


The global AIOps market is estimated to reach USD 237 billion by 2025. These statistics highlight impressive growth that is majorly supported by modern technologies such as machine learning, big data platform, and predictive analytics.


How can Testers Contribute to AIOps Operations?

For the implementation of AIOps, you need to gather a team of testing professionals having a clear idea about the components and steps involved. Similar to DevOps, AIOps also requires a significant cultural shift with the tester placed in an important position.


At the beginning of AIOps implementation, testers’ team needs to get familiar with the AI and ML terminologies. This step is essential and proves beneficial while imparting training. To understand the complete role of a professional tester in an AIOps environment, let us stress on the pre- and post-implementation stages for better insight.


Pre-Implementation Stage of AIOps

AIOps is known to assist teams in smartly carrying out performance testing operations. Usually, performance testing is conducted during the staging environment but without the involvement of production-related data.

Before AIOps is actually implemented, the testing team ensures the scripting of performance testing scenarios. These are then reviewed in collaboration with business and development teams.


The latter approach by the testing team is to execute the load tests. According to professionals’ tests, it was revealed that the scripting failed while the server collapsed when it reached peak memory usage. At this moment, the utilization of system resources was reasonably high.  


While the testers analyze the script execution results and application log files, they can ask the IT support team for additional assistance. This includes a comprehensive analysis by the IT team focused on various alerts related to the APM monitoring system.


Post-Implementation Stage of AIOps

During this phase, the testers select performance testing scenarios by seeking help from the IT & infrastructure teams. This stage acts useful towards better decision-making carried out by the business & development teams.

After implementing AIOps, the IT support team gets to prepare curative automated scripts for handling the peak usage of various system resources. At the time of performance test execution, the testers are notified regarding dynamic errors, which are carefully resolved by the IT team’s scripts.

Hence, system resources are very well managed; therefore, the testing team can completely dedicate themselves to performance testing activities. It is essential to understand that even after implementing AIOps, the testers’ capabilities are utilized from time to time per system resources. 

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How are Neobanks Driving the Future of FinTech?

The market for Financial Technology (FinTech) has transformed majorly since March, with the COVID-19 virus breaking loose at the global level. You might wonder how a pandemic influences FinTech, but since all businesses require finances & banking support, the current financial technology changes are understandable. We have started this new decade where people are ready for the digital transformation that improves their financial lives. Individuals who have maintained decade old relationships with big banks are now open to the idea of ‘Open Bank Movement’.  

According to this arrangement, the financial services industry has backed the emergence of fully-digitized banks known as Neobanks. Also called ‘challenger banks,’ these are viewed as new banking options in direct competition with various legacy institutions.  

What Is The Present Situation Of FinTech?

To be honest, almost everyone from the digital banking space is aiming to establish themselves firmly in the market. So, looking at the most notable challenges faced by digital banks at present, customer growth does top the list. Moreover, the extended targets do focus on profitability and good digital experience, which can now be achieved via Neobanks. This banking model plans to improvise and outshine traditional banking methods for a better future.

“Fin-Tech and banks need a cultural reconciliation: risk appetite and tolerate trial errors” – Hugues Delcourt

You can very well see that the use of disruptive technologies like artificial intelligence (AI), cloud computing, and big-data analytics are systematically merged with Neobanks all around the globe. This straightaway highlights the transforming nature of FinTech and how Neobanks are functioning as a supportive banking model during the coronavirus pandemic. Furthermore, you can analyze a growing belief in this latest digitized financial structure that can smartly tackle the limitations imposed by traditional banking institutions.


ImpactQA - Neobanks & Impact on FinTechWhat is Neobank?

Neobanks can be defined as a modern version of banking services. With traditional banks, you get to access online services; however, the dependency is primarily on their physical branches. But the best part about Neobanks is their ‘digital-only’ financial setup that is gaining quick popularity in 2020.  

If you wish to access the services offered by a Neobank, there is no need to visit the bank’s headquarters to fulfill documentation or meet any representative. Each process with a Neobank is fully digitalized and can be conveniently managed through the bank’s official website or mobile app. The concept of Neobanks was first introduced in the United Kingdom. Post the financial crisis, banks that were struggling to cope with heavy financial losses could not lend money to each other. This situation pushed the government to amend the regulations, thereby permitting Neobanks to generate capital and put in place an online infrastructure before finally applying for a full banking license.  

Neobanks avert the need to spend funds on constructing a physical branch. The main focus is to offer online banking services supported by AI-based risk assessment tools, user-friendly interfaces, fraud detection systems, and chatbots for streamlined customer interactions. Taking the example of Switzerland, which is the world’s most modernized nation for banking, the rising popularity of Neobanks has been carefully demonstrated. Based on the Swiss Payment Monitor (2020), an annual study conducted by the University of St. Gallen and ZHAW (University of Applied Sciences Zurich) School of Management and Law, around one-tenth of 1,200 Swiss residents who were surveyed during the end of 2019 were already associated with new online-banking solutions delivered by Neobanks at least once. One of the prime reasons for choosing Neobanks was the availability of competitive exchange rates preferred by the candidates.  

Neobanks & Their Relationship with Gen Z

The younger generation can very well reap the benefits associated with Neobanks. To be precise, the digitally-savvy category of consumers who want to avoid bureaucracy and desire more flexibility from traditional financial institutions can readily opt for this digitalized banking option. You can easily spot that the current generation is dedicated to online loans that can be managed within a few clicks. This is why Neobanks gain an extra edge since they are characterized by high speed, useful services, and customer-friendly support staff.

ImpactQA - Neobanks & Global GenZWhat makes Neobanks so efficient? Incorporating the latest technology, such as AI and Big Data, proves helpful in self-assessing risks and not hiring any external security testing service. You can view Neobanks among bespoke financial services that are expanding their customer base by appealing clients with low credit scores or no credit history. Unlike the outdated risk assessment model, the upgraded structure of neo-banks stresses multiple factors to assess risk. It includes examining the applicant’s online activity and spending history.

Neobanks for the Underprivileged  

The outburst of virtual banks without any physical presence has initiated new dawn for FinTech. A majority of these banks are equipped with the latest innovation to fulfill the requirements of underserved market sections, including the unbanked and the under-banked. This segment comprises immigrants, small businesses, independent contractors, freelancers, etc. All categorized under one tag: ‘Underprivileged.’ The mentioned user classes had suffered monthly and annual fees due to low account balances and lack of appropriate advice from big banks.   

The overall working model of Neobanks is operated over customer data to present an innovative scheme. It includes the launch of new products and partnerships to attract more customers by serving attractive benefits. Since smartphone usage has risen in the past couple of years, the introduction of challenger banks gets a better platform to outsource banking activity to individuals. We can clearly state that Neobanks are leading the mobile banking revolution supported by flawless design and customer-centric features.

How Trustworthy are Neobanks?

You can surely see Neobanks as a reliable financial model viewed as a revolutionizing weapon in the global FinTech arena. If you are worried that the bank doesn’t possess a physical branch and deals in digital-only services, causing trust issues, try to broaden your perspective! Neobanks is undoubtedly a new idea, but its operations are managed in a highly regulated manner where different companies need to abide by strict security & quality standards. Since everything happens online, cybersecurity is a concern that is smartly self-assessed without the involvement of software testing companies for delivering flawless online banking platforms.

Once all such specifications and quality checks are performed, Neobanks are proven fit to receive a license. At present, Neobanks are investing enormously to ensure fraud detection systems and manage protected authentication. With all these measures put in place, the growth of FinTech does appear promising. To smartly manage security checks for Neobank platforms, you can connect with any renowned software testing company like ImpactQA. Our association with FinTech services is a decade old; therefore, we can relate better with modern Neobanks and their different testing requirements.

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How is ImpactQA Revolutionizing Software Testing Industry in this Modern Era

Regardless of the industry, you belong to, the role of technology and its various tools have become an important aspect. In order to acquire higher returns on investment, the software is essential to carry out tasks in a smooth manner. For every business that deals with the development of applications, software quality should be the prime focus. To upkeep this requirement, you have numerous software testing & QA companies which make sure your applications are structured in a full-proof way.

ImpactQA is a leading software testing company that has been showcasing its expertise in the industry for almost a decade. Over the years, the company has smartly adapted to the latest technology trends and business needs to maintain its shining status. It wouldn’t be wrong to say that ImpactQA has been at the foremost of revolutionizing the software testing industry with the active incorporation of certain modernized testing methodologies.

This write-up offers a clear insight towards the contributions put in by ImpactQA within the software testing industry. Let us try to focus on some of the prime techniques that have proven supremely effective:

Digital Transformation

As per the statistics delivered by the World Economic Forum, the market for digital transformation is expected to hit $100 trillion by 2025. ImpactQA has been sound and aware of the changing trends and has utilized digital transformation to augment its software testing suite. The company has been a step ahead with its digital transformation consultancy that offers new digital features that work to polish important features like flexibility and agility of the QA processes.

Over the years, ImpactQA has been supportive of major digital upgrades that have proven effective in pulling more clients from the global front. The company has been pushing its limits in increasing its technology pool with an aim to explore innovative techniques.

Shift towards Performance Engineering

The usefulness of performance testing to assess operational ease for applications is necessary for almost all enterprises. In 2020, the role of performance engineering is slowly gaining higher prominence than performance testing methods. Based on this structure, you get to conveniently evaluate customer experience that helps in better commercial viability.

ImpactQA is among the top software testing companies in the USA that have successfully implemented performance engineering to gauge product performance. In the near future, the company wishes to expand the role of performance engineering within its service offerings by laying more focus on vital elements like the realism of use, customer value, and configuration quality.

Enhanced Role of AI/ML

Artificial Intelligence (AI) in software testing is useful in making the testing efforts grow smarter and efficient. It should be known that AI and machine learning, when applied to test operations, tend to improve problem-solving features. Hence, you get a better hand at automated steps to benefit from advance testing.

ImpactQA has been an ardent follower of AI in software testing. The company has understood its value towards time conservation due to the replacement of manual testing with upgraded automation testing. Moreover, ImpactQA has further strengthened its test suite due to the availability of log analytics, defect analytics and forecast features, all thanks to the involvement of AI.

Cloud & Software Testing Operations

The world is shifting towards cloud computing services as they offer a better and cost effective option. Proper involvement of cloud in software testing allows you to receive in-depth information associated to application, infrastructure, and network.

ImpactQA has built a well-structured arrangement for cloud computing merged with AI-based testing service. The availability of such a refined and modern software testing option permits your applications to run smoothly. The methodology precisely includes deploying the application on the cloud that allows the measurement of dormancy in the best possible manner.

You can connect with ImpactQA for gaining more knowledge about its software testing approach. Each of your queries will be addressed by the professionals for better clarity.  

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Technology and its Usefulness in Battling Coronavirus

The novel coronavirus or COVID-19 outbreak occurred in mainland China at the end of December 2019, which has now spread globally to infect millions of people. It is marked as a global crisis and the WHO itself has declared the situation as a ‘pandemic’.

Governments and healthcare authorities around the world are rigorously working to fight this virus. Among the efforts put in place, the role of technology is inevitable. For instance, the deployment of numerous types of AI-powered tools and gadgets is proving effective in carrying out diverse relief operations. Meanwhile, the vitality of robots to carry out interactions with sick patients is quite relaxing.

Earlier, the use of high-end technological aid was majorly deployed across China. However, with the Coronavirus outbreak intensifying across Europe and North America, healthcare services are being very diligent with their options.

This blog focuses on highlighting the utility of technology for countering Coronavirus at the global level. Below mentioned are the prime tech advantages put in place to fight this rare illness:

Active Use of Robots and Drones

It is very important to know that Coronavirus is contagious; therefore, human-to-human interactions need to be managed remotely. Both in public and hospitals, carrying out remote communication between patients and health workers should occur without any transmission. As a safer solution, robots along with several other automation tools are being preferred.

For instance, robots are actively used to communicate with infected people, disinfect rooms, extract vital information, and even deliver medications. Interestingly, a robot was used in Seattle to assist doctors to treat an American patient diagnosed with COVID-19.

AI-Based Diagnosis

Metabiota and BlueDot, two public health data surveillance firms were responsible for tracking the initial outbreak of COVID-19. It was BlueDot which successfully informed its clients about the coronavirus risk days before the WHO (World Health Organization) had officially issued a global warning.

At present, similar technology has been distributed across channels to monitor social media posts along with publicly available content to spot signs of the virus’s spread.

By conducting a deep analysis as to what every COVID-19 patient is receiving, AI is capable of chalking out satisfactory treatment strategies. For instance, Jvion, a renowned health care analytics company, is making good use of AI to examine 30 million patients across its data collection for identifying people who are highly susceptible to COVID-19. This is made possible by bringing along 5,000 plus variables which cover medical history, lifestyle as well as socioeconomic factors. Further, Jvion’s platform helps to create a proper list of people who need to be contacted regarding their vulnerability to COVID-19.

Potency of Smartphone

Believe it or not, smartphones are listed among the topmost tech aids helping in reducing virus exposure. For example, delivery apps assist in contactless delivery, where the riders are guided to drop food at a specified location. Meanwhile, the use of mobile payment apps is proving effective in reducing transmission as compared to paper money, which is known to carry the virus for up to 17 days.

Big Data Indicator System

The smart implementation of a transparent and handy public data has permitted the creation of dashboards for tracking virus outbreak. Till now, not only the WHO but many small organizations have contributed immensely to cater to the development of such big data dashboards. As a result, users can go through real-time updates conveniently via familiar apps.

Online Platforms for Business Stability

With a worldwide epidemic on the loose, there is a serious challenge to maintain business operations. It is observed that several tech organizations are lending a helping hand by offering free online collaborative tools. Furthermore, the use of online meeting applications has assisted other businesses to successfully imposed work-from-home policies. This also includes the usage of LBS technology and collaboration platforms to ensure a streamlined working of an employee.

Soon, this fight with Coronavirus will strengthen and technology will surely lead from the front. Several software testing companies including ImpactQA have readily followed work-from-home guidelines and are maintaining business operations using shared online platforms.

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How is Drone Technology Effective in Tackling Coronavirus?

In a matter of few months, Coronavirus or COVID-19 has transformed into a pandemic starting its track from China and reaching the United States with a global infected count of 1,018,649 and the death toll rising to 53,281. The foremost steps taken by authorities are to upgrade medical facilities and practice social distancing. These measures have proven effective for China to fight this virus in its 3-4 months of struggle. 

The role of technology cannot be sidelined as it is one of the crucial components used to curb Coronavirus. For instance, the Chinese government has been advising methods to implement drones for providing vital assistance in this alarming situation. Many nations have taken positive out of these experiments and have responded actively to this global health crisis.

At present, both public and private health systems are trying to extend the use of drone technology with a vision to mitigate future chaos due to Coronavirus. Below mentioned are few important ways how drones are proving advantageous in the battle against this rare virus.

Aerial Disinfection

The sole purpose of using drones was originally to spray pesticides under agricultural applications. However, China adapted well with this technology and started to spray disinfecting chemicals across several public spaces and on prevention vehicles that travelled between infected areas. Since Coronavirus is majorly transmitted through respiratory droplets and can transfer by contact through contaminated surfaces spraying disinfectants is a good way to help reduce virus transmission.

For ensuring a safe model for aerial disinfection operations, several in-bound organizations in China such as XAG Technology, China Agricultural Machinery Distribution Association, DJI Agriculture, etc., have joined hands to issue operational guidelines and technical provisions to interact with local authorities. Such measures are essential in streamlining the efforts so that the purpose is served without any hindrance.

Supply Medicines and Test Kits

According to a recent study, it was revealed that the delivery of supplies made using drones can help in covering a larger consumer space in Europe. Interestingly, close to 40 million Europeans will benefit from drone delivery under current circumstances. The correct use of Artificial Intelligence (AI) with drone technology is the reason for the success of such operations.

This model has been carefully tweaked and there are test runs to provide Coronavirus test kits with the help of drones. It is simply through the elimination of humans to transport test kits, we get to majorly lessen the tendency for community spreading of Coronavirus. The reduction of human contact is a must and through this technique, it helps to reach out to a vast patient count in lesser time.

A lot of Europeans, Americans, and populations in other infected nations are scared of community transmission and extended quarantine time. Drone technology is a suitable way to effectively curb these scares by the delivery of food, vaccines, and medicines.

Social Advantages

As analyzed by researchers, the use of drones to transport groceries, medical supplies, etc., in the U.S can enormously benefit the Americans in battling it out with COVID-19. It is highly evident that drone delivery would increase social distancing; hence, reduction in the spread of Coronavirus. Areas that are already marked as high-risk zones for COVID-19 can make the most out of drone services.

Furthermore, the active merger of drones and public health response is a greater benefit to people who reside on the outskirts of major towns and cities. This group can now receive essential groceries and other supplies from stores that are located at a distance from their place. In simple words, drone technology would effectively expand the options related to grocery stores and other important services in remote areas while maintaining social distancing.

Let us see in the coming months how governments and medical authorities across the world inject modern technology to control the spread of coronavirus. This combat against Coronavirus requires a systematic blend of technology and medical assistance. Drone technology has been suitably fed with Artificial Intelligence (AI) and other automation upgrades to make it more resourceful. Software testing firms like ImpactQA have been supportive in testing newer AI upgrades and validating their effectiveness by carrying out system checks and corrections.

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What is the Impact of Artificial Intelligence on Software Testing?

The propagation of Artificial Intelligence (AI) as new technology has received worldwide recognition.  Although it’s not a new concept, the implementation of AI techniques across software testing has proven advantageous. It is interesting to know that, development teams across various platforms are switching to online and e-learning assets all thanks to AI.

However, the misery for QA Engineers at present is linked to surplus difficulties and time wastage while looking for a solution. The scope for making new additions or expanding existing new codes requires them to carry out fresh tests. It is a rigorous process and if planned manually, does overwhelm the QA experts.  

This is where the usefulness of an AI-based testing approach comes into play. Such an arrangement can help identify changed controls skillful in comparison to manual efforts. Furthermore, the identification of even the slightest alterations with the algorithms can be observed by including AI in the process.

This write-up aims to highlight the vitality of AI testing towards software testing and how it will provide supreme assistance in the coming years.


Also Read: How AI Adoption Actually Bang and Turn QA Expectations?


Importance of AI for Software Testing


The future is untold but technologies such as AI have already given us a positive outlook about what comes ahead. Artificial intelligence is praised as a smart addition to software testing, with future innovations expected to drop more surprises. Below mentioned are some of the notable effects of AI on software testing which should be learned and acknowledged. 

  • Regarding automation testing, the utilization of Artificial Intelligence is primarily associated with object application categorization fixated at all user interfaces. Under this, recognized controls get categorized when tools are created. Moreover, testers are equipped to pre-train controls which are usually available in out of the box arrangements.
  • We already know testing simply means the confirmation of results; hence, one does require possession of surplus test data. As a modern concept, Google DeepMind has an AI program that is structured across deep reinforcement learning efficient enough to play video games by itself. Such an action permits the acquisition of sufficient test data.
  • In the coming years, Artificial Intelligence is likely to monitor users who perform exploratory testing contained within the testing site. This also covers human involvement for assessing and spotting the applications which are getting tested. Consecutively, such a step will attract business users to actively implement testing and customers would be given the chance to fully automate test cases.
  • Risk automation helps users in specifying which tests should be imposed to achieve greater coverage under limited time. As AI testing is added to the test build, execution, and data analysis, it permits testers to permanently get rid of spot links flanked by bugs and components in a much better way.


AI Testing & Related Advantages  

Finally, we mention some of the prominent benefits of AI testing which makes it a bonus inclusion for software testing:


1. Fastens Manual Testing

It is a well aware fact that countless test lines are coded even by the most skilled application development companies.  Manual testing is not that efficient in maintaining speedy processing even after all efforts are put in place. Above all, functional testing tends to be expensive, thereby, consuming additional time and money.

The incorporation of AI testing is known to facilitate and address time-wasting issues. As a result, developers are relaxed when it comes to writing all scripts and investigating large chunks of data sets since they are now managed in a faster manner. Artificial intelligence is capable of sorting via log files, thereby, saves precious time and improvises programming accuracy.


2. Assistance to Developers and Testers

The usefulness of shared automated tests can be reaped by developers for identifying problems before passing it on to QA. To be precise, tests can be executed automatically every time the source code variations are checked in. This also functions as an effective move to notify the team in case of a failure.


Also Read: 5 Ways AI is Shaping the Future of Software Testing


3. Enhanced Time-to-Market

Software tests are repeated whenever the source code is altered. It should be understood that manually repeating such tests is indeed time-consuming and can also prove highly expensive. However, automated tests can be operated multiple times without any additional cost and at a quicker pace.

Some of the AI-based test automation tools include Appvance,, etc.


4. Advanced Test Coverage

As AI is merged with automated testing, it works to enhance the overall depth and scope of tests. Automated software testing can easily access memory, file contents, data tables, etc., for determining the working status of the software. On the whole, test automation is capable of carrying out 1000+ test cases related to each test run offering coverage that isn’t doable with manual tests.

The potency of AI testing and its collaborative actions under software testing is very well defined in this blog. As the testing arena is gaining strength and skill in this modern setup, the superiority of AI-based software testing operations will achieve a greater position in the near future. If you hold any queries related to the expanse of AI testing services, simply connect with testing experts at ImpactQA.

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5 Mobile App Testing Trends Set to Surface in 2020

The role of mobile apps in the currently thriving modernized setup has acquired an imperative stature. It is primarily to enhance the scale of convenience both at the consumer and enterprise-level that mobile apps have grown to become a major hit!

For the success of any software or application, there are different types of mobile app testing. App quality is the foremost factor that predicts the success and sustenance of a particular mobile application. Over the years, mobile app testing trends have shown serious variations. The sole reason for this shift can be attributed to the rising count of mobile devices, thereby, supporting enormous disintegration in terms of screen sizes, OS, etc.

Furthermore, it becomes essential for a mobile app testing company to adapt to new features and restrict threats linked to new bugs. According to recently updated research, the global market for mobile app testing services is anticipated to exhibit USD 13585.73 Million by 2026. These are mind-boggling statistics highlighting the importance of mobile app testing in today’s time with an expected CAGR growth of 20.3 % by 2026-end.

A new decade has initiated to bring in new technological trends in the world of mobile app testing. Let us focus on the five prominent mobile app testing trends set to unfurl in the year 2020.


Automation is the Key

Automation has taken over the global mobile app testing market. In 2020, it is expected that the majority of the testing companies will actively stride towards automation which functions as a prominent factor towards quality assurance. In addition, the selection of automation tools and frameworks is known to lessen testing time. There are several benefits of test automation and because of such advantages it is likely to benefit the mobile app testing market with soaring results.


Spotlight on IoT

These days, you will find that most devices are linked to each other, thereby, preaching comfort as the fundamental aspect. For instance, mobile devices are now connected to headphones, smartwatches, home accessories, etc. This overall concept is termed as the Internet of Things or IoT. Although the incorporation of IoT does exhibit convenience, security threats are rising on IoT since devices are getting more complex.

In 2020, it is expected that a mobile app testing company would be able to access more sophisticated technology. In simple terms, the IoT testing process will involve not just mobile phones but several other hybrid devices for quality assurance.


Testing with Real Device Cloud

As per research insights, close to 1.5 billion smartphones will be operative in 2020 having different screen resolutions, OS versions and more. It is practically impossible to test a particular mobile app on all devices which are used by the customers. As a valid solution, incorporating a real device cloud is the perfect way to enhance testing efficiency. For the current year, the favorable strategy implied for mobile app testing is concentrated at amalgamating the use of real devices with cloud technology.

Such an arrangement will pinpoint evident performance defects. Moreover, the chances of having forged positives or negatives are also decreased. Among the latest mobile app testing trends, the deployment of real device cloud is highly efficient since it targets everything, be it network failures, hardware issues, etc.

The future holds untapped mystery, especially when it comes to technology and its wonders. As the year passes, it is believed that Artificial Intelligence (AI) and Open Source Tools will surely share a significant role in accelerating the mobile app testing market.


AI Testing

The popularity of Artificial Intelligence as a growing technology has brought major changes within the software research arena. It is observed that the implementation of machine learning and artificial intelligence over the testing platform can prove fruitful. For instance, the AI testing algorithms can be useful in creating better test cases, scripts, reports and data to receive efficient outcomes.

The usefulness of AI testing can also be highlighted while designing test models to determine errors and loopholes effective for mobile app development. With the power of smart visualization and analytics, AI is extremely serviceable to search and rectify defects without much hassle.


Propagation of Agile and DevOps

The reputation of Agile has escalated in the market since organizations are switching towards rapid changes. Moreover, the collaboration of DevOps for accomplishing speed requirements is another factor that is expected to rocket in the near future. It is expected that DevOps will implement the rules and practices together to set out operations and development processes on mobile apps.

It is a major advantage of testing with DevOps and Agile for creating better mobile apps. Quality and speed are the foremost factors that are meticulously assessed with this productive association.

It is essential to take a look at all 5 mobile app testing trends set to rise in 2020. This allows us to polish and improvise mobile testing methodologies for the future. For additional information and insights, you can connect with professional software testing company, ImpactQA.

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8 DevOps Trends to be Aware of in 2020

  • Automation will become the major focus
  • Shifting attention from CI Pipelines to DevOps Assembly Lines
  • Rise in Artificial Intelligence (AI), Data Science Boost
  • Concept of “everything as code”
  • Hype in using Server Less Architecture
  • Automation through AI and Data Science
  • More Embedded Security
  • Kubernetes has evolved significantly

According to a collective study, DevOps market generated 2.9 billion in 2017 and the market is expected to reach at $6.6 billion by 2022. DevOps has become a key focus and has shaped the world of software and many experts predict that DevOps is going to be the mainstream and is going to reach its peak at 2020.

Enterprises are not only showing interest in DevOps but are gradually adopting DevOps-related practices and technologies. As per Hackernoon article citing Statista, there was a 7% boost in DevOps adoption from 2017 to 2018. DevOps software market is projected to grow from $2.9 billion in 2017 to $6.6 billion in 2022 (source: estimates from IDC).

DevOps Projected Growth 2019

Fig: Google trend is shown for “DevOps” and a hypothesis of its estimated growth in 2019.
DevOps offers the following benefits:

  • Fast response towards an amendment
  • Offers great speed and makes the security arrangement more agile
  • Establishes a perfect channel of collaboration and communication
  • Fast identification of bugs or vulnerabilities in the code
  • Team can effortlessly put their sole attention on other critical things instead of focusing on security features

Many enterprises are adopting DevOps and there is a boost up to 17% in the year 2018 than what was about 10% in the year 2017 (according to Statista)

Image source: Statista

Predictions of 8 DevOps Trends to be aware of in 2020:

1. Automation will become the major focus

Companies that have already implemented DevOps have seen high efficiency and faster deployments. When it comes to DevOps, DevOps automation is what we talk more about. Zero-touch automation is going to be the upcoming future. Understanding the 6 C’s of the DevOps cycle and to apply automation between these phases is the key, and this is going to be the major objective in 2020.

2. Shifting attention from CI Pipelines to DevOps Assembly Lines

The final goal of DevOps is to improve collaboration between planning and automation of the delivery procedure. It is not just about doing Continuous Integration (CI) but it is all about CD (continuous delivery). Companies are investing extra effort and time into understand about automating their whole software development process. In 2020, the attention is going to shift from Continuous Integration (CI) pipeline to DevOps assembly lines.

Advantages of Assembly Lines:

  • Powerful nested visibility
  • Native integrations
  • Fast on board and scale with “as-code” philosophy
  • Perfect CD (continuous delivery) with interoperability
  • Team-based business intelligence and analytics

3. Rise in Artificial Intelligence (AI), Data Science Boost

Growing number of Artificial Intelligence-driven apps will push data science teams to look for DevOps philosophy in their workflows. DevOps method is expected to be their prominent option in dealing with automated pipelines, maintaining, and testing multiple deployed models in the production chain.

This is going to boost further as data science & development teams move closer for high efficiency in development, deployment & managing AI & ML-driven apps.

4. Concept of “everything as code”

We cannot deny the fact that coding has now become the backbone of the IT sector. Understanding various DevOps tools and automating scripts plays a crucial role in the software development and this is going to dominate in 2020. The future of this industry depends on the technical capabilities of the developers, testers, and people of the operation.

Since, DevOps is all about easing the delivery cycle, there is a need to bring in the code which can be used to increase the software production cycles efficiency. The thought of “everything as code,” is DevOps’s built-in practice and it can be present in the SDLC to create a wave in the DevOps trend 2020. Software Testers are likely to suffer if they do not learn to code and write their test scripts.

5. Hype in using Server Less Architecture

DevOps can be reached to the zenith level with server-less architecture. This is not free of server; however, there is a cloud service which takes care of the complete architecture. This extraordinary architecture allows the software developers to concentrate focus on the “Application Part”. BaaS and FaaS are the two critical aspects of the server less architecture. By employing server-less architecture, you can save time, cut down the costs, and ensure resilient work flow.

6. Automation through AI and Data Science

The main objective of 2020 is zero-touch automation. The continuous increase of Artificial Intelligence and Data Science has become a game-changer. Various apps are fueled with AI, which is pushing DevOps teams to seek automation possibilities to discover prospects within their workflow streams.

7. More Embedded Security

With the exponential growth of security breaches and the bad impacts to the company’s reputation, cyber-security has become business imperative. In 2020, DevOps will rapidly include security.

Recently we have seen a buzz trend of DevSecOps. DevSecOps is all about injecting security first in the app development life cycle, therefore decreasing vulnerabilities and improving business reputation.

The shift to DevSecOps will also bring great collaboration in software development. It will ensure the development processes remains flawless, efficient, and effective.

8. Kubernetes has evolved significantly

Kubernetes has turn out to be the top growing container technology. Globally, technologists and CIO’s have preferred Kubernetes because of its offerings and it is expected to grow by 2020. This year, we saw the adoption of Kubernetes take off as companies of all sizes embraced containers for running cloud-native apps. In 2020, we will start to see container orchestration software replacing several old DevOps functions.

Solution- How can we help you?

Whether it is all about offering software development services or other services, DevOps has become the inevitable part of any organization. By staying up to date with the newest trends, you set your business up to get the enormous benefits from DevOps.

As an industry leader in DevOps Testing Solution, ImpactQA give holistic agile and DevOps adoption services across diverse domain segments, backed by its dedicated DevOps Continuous Testing practice. We implement a robust plan to manage both resources and testing tools in a new environment and to facilitate continuous testing and delivery.

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How IoT and Machine Learning is changing the World?

  • What is Machine Learning?
  • What is the Industrial Internet of Things (IIoT)?
  • How IoT (Internet of Things) and Machine Learning affect our life?
  • Challenges- IoT and Machine Learning
  • Solution

IoT and Machine Learning are getting smarter. Companies are incorporating artificial intelligence (AI)—in specific, machine learning—into their IoT apps. From smart thermostats to wireless sensors, IoT devices are gradually but positively garnering mainstream adoption. Virtual assistants like Siri, Alexa, and Cortana are only making this technology easy to adopt.

The core purpose behind advancement in the IoT space is to help information move smoothly and seamlessly. For as much as we condemn technology, we can all recall a moment when the right message has appeared at the right time, with perfect user experience.

The truth of IoT and Artificial Intelligence – specifically machine learning – is far less sinister. It is shaping the way we live, travel, work, and communicate. In fact, it is shaping our lives smartly and the decisions we make.

The proliferation of smart IoT devices is shaping the future and gives instant access to the information world.

Let’s have a glance at these burning IoT statistics:

  • There are about 17 billion inter-connected devices in the globe as of 2018. With more than 7 Billion of these IoT (internet of things) devices. (Source- IoT Analytics)
  • According to McKinsey Global Institute, each second, 127 new IoT devices connect to the net.
  • The global IoT market is expected to be worth $1.7T in 2019. (Source: CBI Insights)
Worldwide Iot Active Connection Graph
Worldwide IoT Active Connection Graph

What is Machine Learning?

ML is one of the critical components of AI, where a computer is programmed with the ability to improve its performance. In short, Machine Learning is all about analyzing big data – the automatic extraction of information & using it to make predictions.

Netflix, Amazon, Google, and other E-Commerce platforms use it to bring semantic outcome. It is based on algorithms that analyze the user’s purchasing history to predict their preference. Machine learning is gradually integrating into all verticals, through automation of physical labor, we are improving the connectivity and shaping the future of AI and the IoT.

What is the Industrial Internet of Things (IIoT)?

The Industrial IoT or Industry 4.0 or the 4th industrial revolution are the terms generally used for IoT technology in a business setting. The concept is similar to the consumer IoT; to use wireless networks, a mix of sensors, big data and analytics to optimize industrial processes.

IoT devices provide information and analytics to connect the world of hardware devices and high-speed internet.

We can separate the Industrial IoT into two main categories:

  • Industrial IoT- The Industrial IoT, connects devices and machines in sectors like healthcare, transportation, power generation, etc.
  • Commercial IoT– Commercial IoT sits between industrial IoT and consumer and shares aspects of both.

How IoT (Internet of Things) and Machine Learning affect our life?

IoT and ML are improving the way we live and communicate in our lives. For instance, the AlterEgo headset easily responds to our brainwaves to control appliances and on the other hand, Alexa and Amazon’s Echo enables the voice-activated control of your high-tech smart-house.

This amalgamation of IoT and Machine Learning is changing various industries and the relationships that companies have with their clients. Businesses can easily gather and transform data into valuable information with IoT.

IoT is also transforming business models by helping companies to move from concentrating on products & services to companies that give the best outcomes. By impacting organizations’ business models, the blend of IoT-enabled devices & sensors with ML creates a collaborative world that aligns itself around results & innovation.

Challenges- IoT and Machine Learning

These days’ enterprises are flooded with data that comes from IoT devices and is seeking AI to help manage the devices. It is tough to manage and extract crucial information from these systems than we might expect.

There are aspects to IoT like data storage, connectivity, security, app development, system integration, and even processes that are changing in this space. Another layer of complexity with the Internet of Things has to do with functionality level.

Critical challenges that companies face with IoT and ML are with the application, ease of access, and analysis of IoT data. If you have a set of data from varied sources, you can run some statistical analysis with that data. However, if you want to be proactive to predict events to take future actions, a business needs to learn how to use these technologies.

Many firms are turning to the main cloud platform providers — for instance, Google, Amazon, Microsoft, Alibaba Cloud, or IBM. These companies offer a range of services to store IoT data and prepare it for data analytics, plus to train and run machine-learning models. They also assist in creating graphs, dashboards, and other simple-to-grasp layouts to visualize the information these models generate. Overall, IoT and Machine Learning are combined to provide high visibility and control of the wide range of devices connected to the Internet.

Solutions-How can we help you?

Futurists say ML (Machine Learning) and the Internet of Things (IoT) will transform business profoundly than the digital and industrial revolutions combined.

Are there some kinds of risks? Yes, as with any new technology, we have to accept both the profit and risks that come with mainstream adoption. We can do this with the confidence only when these technologies are tested against several odds.

One of the innovative solutions for seamless operation flow is IoT testing. There will be several other types of testing which require to be considered to cover the comprehensive functionality of IoT devices.

As part of ImpactQA’s Advisory Services, we also provide an implementation plan to help our clients improve time-to-market while keeping their business goals in mind. We use our assessment frameworks (like Chatbot testing framework, RPA Testing framework, etc.), based on industry best standards, focusing on processes, tools, and infrastructure.

Collaborate with our specialists to improve all QA areas – people, processes, tools, and infrastructure across the delivery life-cycle.

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