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How are AI and ML Turning the QA Industry?

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How are AI and ML Turning the QA Industry

Artificial Intelligence (AI) and Machine Learning (ML) are the big-time game-changers. From healthcare to the manufacturing industry or other verticals, they have managed to transform multiple sectors of the economy and are helping together to improve our daily lives in numerous ways.    

Many workplaces such as education, retail, healthcare, finance, and technology leverage AI to reduce costs, automate tasks, and make data-driven decisions. In our homes, personal digital assistants, home automation, security cameras are real-life examples of AI.  Similarly, Machine Learning plays a pivotal role in improving many industrial and professional processes.  

For example, multiple industries and fields can utilize ML for image processing, medical diagnosis, learning association, regression, classification, and prediction.    

How AI and ML will Redefine Software Testing & QA Industry   

In the 21st century, companies are implementing AI in software testing across various areas to help businesses understand their customer behaviors using computer vision, knowledge graph technologies, and data. All these techniques help organizations target their audiences through personalization that helps drive more auxiliary revenue.    

Today, AI is a buzzword and a critical factor for optimizing the testing process, designing the self-healing software, and overcoming test automation bottlenecks.    

But the point is – How Machine Learning enters into the software testing company for Quality Testing?    

As the volume of test data increases, Machine Learning could be the answer to sort through it all. Nevertheless, expanding test automation and maintaining it over time remains a challenge for DevOps organizations.    

Development teams can apply ML in their test automation platforms for writing, execution levels, and post-execution test analysis that help in searching for patterns, trends, and business effects.    

Why is it essential to use ML & AI in software development? Software testing alone can cost 25 percent to 40 percent of the overall project’s budget.    

Testing any software application can be expensive but necessary to perform to ensure that it will work correctly. Larger companies already have dedicated teams for AI testing services to help get the maximum cost and business benefits.  On the flip side, smaller development teams don’t provide you many options for software testing services.    

That’s why it becomes essential today to choose the QA industry for its 500+ dedicated teams available across the globe always ready to help you. They not only reduce software development costs but offer accurate results with an advanced level of AI and ML testing and that too through AI-based software testing solutions.    

Meanwhile, the growing market demands encourage QA industries to think about rapid development phases and look for ways that help in reducing cost, improving the scope and reliability of testing.   

Moreover, market demands allow companies to deliver software before client expectations and deadlines. Similarly, it becomes vital for testers to move into the world of Artificial Intelligence and Machine Learning, which ensures low pressure to them while working on the software testing processes.    

Not only the QA industry, from medical sectors, governments, to Insurers, everyone is trying today to leverage Artificial Intelligence for several different purposes.    

In case you are still not convinced with the idea of using AI for your software testing needs, let’s jump on the benefits of using AI in the software testingprocess taking you closer to the findings how AI and Quality Assurance can help enhance the software testing industry and its processes.    

Benefits of Integrating AI in Software Testing    

Undoubtedly, risk-based automation helps users understand which tests they need to perform to achieve the greatest coverage when getting the testing done in a limited time is a critical factor.    

With the fusion of AI in test creation, implementation, and data analysis, testers of the Best Software Testing Company can eliminate the need for updating manual-based test cases.   

By integrating Artificial Intelligence in software testing, one can identify relationships between defects and components in a far more efficient manner.    

Here are some of the notable benefits of AI in software testing that you can check out one by one.    

Shortening Software Development Lifecycles    

How does AI affect Software Development? While Artificial Intelligence (AI) in software development is not a new concept. This technology is used for a couple of years to support human developers at every stage in the development life cycle.    

In this era, engineering teams are on the frontier of talent and maturity as they release and update new software consistently. In addition, the use of microservices and the popularity of third-party APIs and other software packages leave development teams for building multiple software with hundreds of thousands of different dependencies, which require testing at each step.    

The increasing demands of customers enable companies to shorten the lifecycle of software. Therefore, for every new feature, it becomes imperative to perform rigorous testing to make sure to consumers about software accuracy.    

Given the breakneck pace of new product launches and software, companies have no choice left except to use Artificial Intelligence in software testing that helps in shortening the software development lifecycle and improves resource management, cooperation between participants, and cost-effectiveness.    

Improved Accuracy    

Humans are prone to errors. Even the most proficient software tester can make mistakes while carrying out manual testing. This is where we need to introduce AI in software testing to perform tasks accurately whenever they execute.    

With automated testing, testers don’t need to worry about working on repetition-based manual testing, which consumes a lot of time when it comes to creating software tests and dealing with complex features.    

When using AI and ML (Machine Learning) in QA testing, it becomes feasible for developers to find a balance in Software Development and reduce pressures that they face while providing delivery of software at a specific deadline.    

Artificial Intelligence (AI) and Machine Learning are automation-dependent, which is a familiar topic to developers. So, the advanced features of AI and ML can apply to Software Testing to minimize the cost of complex releases and improve the pace and accuracy of the software.    

Both AI and ML have come to transform the future of the software testing and QA industry. Wherefore, by integrating AI and ML into software testing, one can experience fruitful benefits.    

AI & ML Improve Code Coverage    

In Software Development, there is a regular debate over how much code coverage is sufficient for a testing suite. Some companies believe that software testing can achieve 100 percent code coverage, and some assume it a pipe dream.    

Attaining 100 percent code coverage is impossible without automation, especially if you want to create adequate tests and wish for quality products.    

The reason for the lack of code coverage in some testing processes is that customers’ demand changes over time, which means managing the development with testing and technology can become an over-burden process if you skip utilizing the AI and ML in your testing strategy.    

The blend of both technologies assists in improving code coverage as the role of AI in automated testing is to support the development and maintenance of an application. However, ML needs the training to understand codebase and produce tests per the code units it finds.    

With training, ML can learn context, predict outputs, and prioritize what matters most to customers. Additionally, it can generate tests to run automatically. Furthermore, it is possible to get automation for entire test suites that make it possible to achieve 100 percentcode coverage and a realistic proposition for many online projects.    

Reduce Regression Testing Bottlenecks    

The objective of regression testing is to ensure that software will work even after making code changes. It also assures that no bug will remain left in existing code after adding new features and introducing new updates.    

Yet, this process is very time-consuming because predicting the new demand from the customer’s end is impossible.  One should have to make a change in the software whenever any stakeholder requests it to do so.  It is the responsibility of developers to make sure that the new change will never influence the existing codebase.  

However, when this effort combines with the need to deliver minor updates quickly, regression testing causes a significant issue in the testing process. Thus, it is crucial to overcome such issues using AI-driven automated testing that lets you perform complete test suites for every change promptly.   

AI can reduce risks better than humans, and this technology can combine with parallel testing to save testing time for other processes. Therefore, the future of the Software Testing and QA industry is AI and ML and will prioritize more to complete the variety of tasks within a short span of time, but with complete accuracy.   

Automation, enhanced customer experience, intelligent decision making, business continuity, medical advances, research & data analysis, easy management of complex problems, and repetition tasks are some of the incredible benefits that you can acquire as a QA company while leveraging AI and ML to your Software Testing.    

Kanika Vatsyayan is Vice-President Strategies at BugRaptors who oversees all the quality control and assurance strategies for client engagements. She loves to share her knowledge with others through blogging. Being a voracious blogger, she published countless informative blogs to educate audience about automation and manual testing.

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Tango Networks Unveils Mobile-X Extend, BYOD Business SIM™ for Work-from-Anywhere Communications

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Service embeds app-less business extension into employees’ personal dual SIM mobile phones.

Tango Networks today announced Mobile-X Extend, the communications industry’s first service using a modern electronic SIM (eSIM) to instantly add a business-controlled extension to a mobile phone.

Mobile-X Extend places a full-featured, secure and controlled business phone on employees’ BYOD devices. Now employees can use their own mobile phones for business communications with a business identity while their personal communications remain separate and private.

“Today’s work-from-anywhere business world demands that we rethink how our employees communicate,” said Douglas J. Bartek, CEO of Tango Networks. “Mobile-X Extend is a first-of-its-kind service that reinvents mobile communications for today’s corporate users. It transforms not only how we communicate in commerce, but it greatly improves company operational efficiency and employee productivity. Now employees working in any location can be as reachable and responsive as if they were in the office at a desk phone.”

By integrating into Unified Communications (UC) platforms or UCaaS services, all business calls and texts on a personal mobile phone automatically use the business identity and can be captured and recorded for archiving or monitoring. All personal calls and texts remain private and external to company control.

“The mobile network is the most extraordinary machine that mankind has ever built,” said Andrew Bale, Tango Networks General Manager of Cloud Services. “Today we give individual businesses unprecedented control over that machine. This represents the greatest advance in business communications technology in a generation.”

With Mobile-X Extend, a business can cut landlines and the huge expense of buying, managing and upgrading company-paid mobile phones. This reduces the company’s carbon footprint while shrinking administrative overhead and expenses. The solution eliminates the cost and hassle of managing expense claims for business calls on personal mobile phones.

The service is mobile native, using the mobile network and the device’s native interface for all communications and features. That means it requires no apps or special phone clients and no training. The service offers superior, business-quality communications not possible with over-the-top VoIP.

Mobile-X Extend is based on Tango Networks’ Mobile-X fixed-mobile convergence technologies covered by more than 90 patents.

Businesses use Mobile-X for Mobile Unified Communications, Mobile First and Mobile Only communications, and work-from-home, hybrid and work-from-anywhere flexibility. It brings fully integrated business communications to mobile employees, deskless employees and first-line workers, many for the first time.

Mobile-X Extend is available for customer pilots now and will be generally available in 1Q2022. The service is sold solely through Tango Networks’ value-added resellers and communications service provider partners.

About Tango Networks

Tango Networks is revolutionizing business communications with the industry’s first mobile network built for business, controlled by businesses.

The Mobile-X service turns any mobile phone into a fully featured extension of a company’s communications platform, putting mobile voice, text and data entirely in a company’s control for the first time.

Businesses use Mobile-X to deliver easy-to-use, business quality communications for work-from-anywhere programs, remote workers and employees working from home, the distributed workforce, deskless employees, and workers on the go.

Mobile-X empowers companies to transform operations, streamline collaboration and boost employee productivity across the board. Learn more at tango-networks.com.
              

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Lessons learned from remote education: Teaching will never be the same

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remote education

Before March 2020, catching ‘fresher’s flu’ was a right of passage for university students. Fast forward 18 months and students around the world stayed indoors to keep illness at bay. However, the pandemic has taught the education sector an important lesson — the value of selecting the right communication tools.

According to UNESCO, more than 1.5 billion students around the world were forced out of their typical learning settings in 2020, with many participating in lessons online. Globally, education in the 21st century has never seen so much disruption and it has prompted critical conversations about the role of technology in delivering education.

Education isn’t the only sector that’s facing an overhaul. Over the course of the pandemic, and for several more years to come, communication technologies have grown increasingly more sophisticated. The UK increased its fiber connections by 50 percent in 2020, and while its broadband connectivity stills lags behind many other countries, the nation is undergoing massive change. As Openreach switches of the public switched telephone network (PSTN), every business will be communicating differently by 2025.

Research by broadband company Zen shows that 17 percent of large organizations are still unaware of the switch off. Education facilities also risk becoming out of the technology loop if they don’t learn from the past 28 months.

Going remote

Throughout much of 2020 and 2021, educators had no choice but to deliver teaching remotely. However, even though in-person teaching has widely resumed, distance learning could become an increasingly favoured choice, rather than an obligation.

Distance learning isn’t a phenomenon of today’s society. Back in 1969, The Open University (OU) pioneered the concept by offering students the chance to gain a degree without needing to set foot on campus. It was a radical idea for its time — yet proved highly popular. By the time applications closed for its first year of enrolment, the university had received over 100,000 applications.

However, The OU’s popularity has decreased over time with numbers of full-time enrolments slipping over the past decade. But things could be set to shift again. Increased demand for upskilling and reskilling, as well as an emphasis in the attractiveness of online learning spurred on by the pandemic, has caused a surge in OU registrations.

Overall, the total number of OU students enrolled for the 2020/21 academic year is up 15 percent on last year — from just over 141,000 to more than 163,000. While distance learning has seemed like a short-term fix to keep people safe, it’s also encouraged a newfound appreciation for the teaching method that could lead to long-term behavioural changes.

Getting prepared

We won’t be saying goodbye to fresher’s flu any time soon. While most forms of education continue in person, education facilities shouldn’t neglect the promise of distance learning.

What’s more, the past 18 months has taught every industry to expect the unexpected. Most businesses were not prepared to go remote overnight at the start of the pandemic, and education was no exception. However, having the right tools in place to ensure distance learning can be carried out effectively is the best way to plan for any other unforeseen circumstances.

One essential piece of any education facility’s armoury is the right communication tools. In particular, facilities should opt for a Cloud-based solution. Cloud-based platforms provide an easy way for educational institutes to streamline their academic communications and collaborations. They can achieve this by combining real-time voice, video, and messaging capabilities with their business applications.

Using Cloud-based software that enables Voice over Internet Protocol (VoIP) makes it easy for students and teachers to interact collaboratively by using real-time messaging and video. This can effectively improve completing group projects, enhances the way teachers communicate with students and cuts down obstacles in the system of education. Because technologies such as VoIP enable calls through the Internet, rather than a fixed telephone line, it’s far easier for education providers to interact with geographically dispersed students and with less ongoing costs.

As such, 90 percent of data breaches are a result of human error and using the Cloud to manage communication tools and store their associated data can help universities better manage sensitive information.

At Ringover, another huge benefit we see for VoIP technologies in education is its scalability. Our own software can be easily scaled to suit the size and needs of any business, whether it requires a complete professional phone system or additions to its existing infrastructure. With collaboration tools such as screen sharing, instant messaging, and video conferencing, Ringover’s software can help facilities of any size communicate effectively.

After several weeks of getting to know each other, it’s likely many students are battling fresher’s flu right now. However, no matter which education route a person chooses, having access to effective communications tools is crucial. Post-pandemic education won’t look the same as it did previously, and having scalable, streamlined software in place will help any facility to future proof.

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Introducing the 5G Workforce

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It’s been a long time since a technology breakthrough generated as much anticipation and fanfare as 5G. Buzz around it has been building for some time and with good reason: 5G will fuel an economic and social revolution that disrupts how companies operate while opening-up incredible new opportunities for those who have the talent to support it, a 5G workforce.

To fully grasp the necessity for a 5G workforce, you need to recognize the impact this technology standard is going to have. Consider the following:

  • PwC’s “The Impact of 5G: Creating New Value across Industries and Society” reports that 5G will fuel a variety of new opportunities. This includes “the optimization of service delivery, decision-making, and end-user experience,” which “will result in $13.2 trillion in global economic value by 2035.”
  • Ericsson’s latest Mobility Report states that the number of 5G smartphone subscriptions worldwide will exceed 500 million this year. That’s double from 2020 and the momentum will continue in 2022 when subscriptions are expected to pass one billion.

With numbers like these, it’s easy to understand the excitement around 5G. But for businesses to see the benefits, they need employees with skill sets that extend beyond the 3G and 4G worlds we are leaving behind — these networks utilized similar technologies which eliminated the need to upskill teams, hastening the transition from 3G to 4G.

This is not the case now. 5G requires people with aptitude and experience in an entirely different set of technologies. This explains why Boston Consulting Group estimates that it will create 3.8 million to 4.6 million jobs in the US alone.

As businesses begin searching to construct their 5G workforces, various skills are required to start building your 5G workforce. Some examples of areas that your 5G professionals must be skilled in include:

Software-Defined Networking (SDN): You will be looking for people that have experience with SDN, a new architecture that turns a wireless network infrastructure from a close environment to a more agile and cost-effective network, where external controller control is moved from network hardware to external controller. This allows teams to quickly introduce new services or changes. Many view SDN as the key to enabling 5G to meet its ultimate promise.

Some specific skills here include network engineering experience focused on designing, implementing, deploying and supporting a production network at an enterprise-scale as well as at an enterprise scale

Software-Defined Radio Access Networks (SoftRAN): SoftRAN is key to supporting network slicing, which is the process of creating multiple virtual networks. While each is part of a physical network, network slices can be automated and used for distinct applications with specific requirements.  

When it comes to SoftRAN, you’re seeking people who have experience in network programming, radio frequency transmission systems, C++, Linux, and Java.

Edge Computing: While 5G delivers dramatically increased network speeds (4X that of 4G LTE), it’s the edge that dramatically reduces latency. It brings the computing capabilities we experience in the network to the user, regardless of location. This includes those areas notorious for spotty connectivity that we are all familiar with. Ultimately, the edge is essential for 5G meeting its full promise.

Your edge computing people will have experience in continuous integration and delivery, Java and Python, as well as edge/IoT applications and system design.

Network Virtualization (NV): NV removes the network’s dependency on hardware, allowing it to run virtually on top of the physical network, where it can accelerate the deployment of applications, improve security, and reduce costs.

Key NV-related skills include experience with continuous configuration automation tools, application programming interfaces (APIs), programming languages, as well as success in deploying and optimizing VMware NSX environments and NSX virtual networking implementations.

5G is likely to be the standard in just a few short years, and its impact will be felt across all industries. In healthcare, a connected ecosystem will be born that is predictive, preventative, personalized, and participatory. In manufacturing, we will see new smart factories that fully leverage the power of automation, artificial intelligence, augmented reality for troubleshooting, and the Internet of Things (IoT). The list goes on.

All these innovations and many, many more are within reach but will be fueled by the next generation workers who have the requisite skills to make it all happen. For businesses, the time to begin assembling your 5G workforce and forging an ecosystem of partners to help with this journey begins now.  

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