5 Key Practices for Automated Security Testing in 2022

Never send a human to do a machine’s job – This is the key principle driving continuous and automated testing in the DevOps world. The key to agile methodologies lies in continuous and automated testing software…

Never send a human to do a machine’s job – This is the key principle driving continuous and automated testing in the DevOps world.

The key to agile methodologies lies in continuous and automated testing software during the development phase. To run a continuous delivery pipeline or continuous, reliable integration, automated integration, unit and acceptance tests are indispensable quality controls. Sadly, security tests are often left outside the ambit of this procedure due to some flawed belief.

Is automating security testing a good move?

Yes, it sure is. Just think about the scenario where you just need to examine if known flaws have crept into your software codes or its functionality and have a person to run these checks manually. Wouldn’t it be a sheer wastage of manpower as these routine tests can be done easily and efficiently by automation? True that you will always need intelligent professionals for ensuring top-notch quality and testing certain aspects of the software, but engaging people for routine security tests isn’t economically feasible, more so when you can easily automate the process and put the freed human resources to better use somewhere else.

Compared to penetration testing of yesteryears, the need of the hour is continuous and automated testing as continuous deployment demands continuous configuration, development and testing.

Bringing the developers and testers together

In DevOps world, you need a secure SDLC (Software Development Life Cycle) approach. Remember – you just can’t ignore or compromise with security. But as it happens in small increments, you can start small without feeling overwhelmed, in case you haven’t started running continuous and automated testing.

Step-by-step approach

1. The first step is to plan, where you will have to –

spot unsecured frameworks and APIs
map parts of security sensitive codes such as user authentication/password changes mechanism
understand User roles and their level of authentication at each level of application
foresee regulatory problems and chart out a way to overcome them

2. The second step is to get your developers involved and connect them to security. You should encourage an open door approach and if necessary, opt for online collaboration and communication solutions like Confluence, Jive etc.

3. The third step would be to empower your developers by asking the testers to provide them with secure frameworks and Service Component Architecture (SCA) tools that can offer rapid, frequent security feedback on pre-commit stage. This should be followed by automation where you integrate within your build (Bamboo, Jenkins, TeamCity etc) and leverage SAST, DAST and IAST. You should mark the build a “failure” if it doesn’t pass the security bars.

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Security testing levels

You can classify security tests with respect to automation as given below:

Functional Security Tests: Used to verify and test if security features such as log out and authentication are functioning as expected. You can use existing acceptance testing browser automation tools like WebDriver/Selenium to automate these.
Application and Infra Security Tests: Open Source tool OWASP ZAP is ideal for such exhaustive security scanning.
Non-functional Security Tests: Misconfigurations and known weaknesses can be tested and automated as the glitches are known already (even when the Dev Team doesn’t know, the Security Team will know it for sure). Thus, whether it’s using weak SSL ciphers and suites, or not using HttpOnly flag on session cookies, you can test them by leveraging a fusion approach where browser automation and a proxy server is used to examine and inject requests.

Many believe that you can’t use automation to test application logic. It’s true to some extent as finding errors in the logic of the application would need a human brain at work. That’s because automated tools can’t deal with the different functions that need to be tested in such cases, by drawing upon past experiences and skills. However, once the glitches have been noted (say, how an attacker may attempt to transfer funds from a bank account to his/her accomplice’s accounts), you can define the parameter and record them as automated tests. These can then become a component of the security regression tests.

Setting up security goals and their implementation

In the DevOps world, security goals must be stated clearly and driven by the business objectives. Since all teams work as a close-knit unit in DevOps, there should be open communication and collaboration and the security tests must be understandable by all stakeholders.

In other words, you should be ready to –

expose your processes to testing
record routine manual security tests and automate them
ensure that the security tests fit into DevOps workflow and CI/CD (Continuous Integration and Deployment) pipelines
make sure the security tests’ logic are independent of navigation code
check for test errors and test failures
keep a close eye on test maintenance
perform regular sanity checks along the way
ask your testers to provide you with a starting point of ready-to-use security tests

Integrating security testing into your automated build process also needs you to use regular methods like WAF, periodicpen testing, reviewing the code for security-sensitive portions. The basic principle is to get everyone on the team involved in the process and bring developers, testers, QAs and IT-Infra people together so that it’s a team effort and there isn’t any “them”…it’s only “us”.

TechArcis is an organization specializing in the area of Security Testing Solution that has a team of highly skilled, co-located software testing professionals who ensure delivery of quality products that help quicker go-to-market and also control efforts and expenses.

The Future of AI: What is the role of Artificial Intelligence (AI) in Test Automation?

Artificial intelligence (AI) is rapidly transforming many aspects of our lives, from how we work and communicate to how we access information and make decisions. It has the potential to revolutionize industries and bring about significant changes in the way we live and interact with the world around us.

One of the most significant impacts of AI is in the field of automation. Many tasks that were previously done by humans can now be performed by machines, thanks to advances in machine learning and natural language processing. This has led to the development of self-driving cars, drones, and robots that can handle a variety of tasks, including manufacturing, transportation, and even healthcare.

AI is also changing the way we communicate and interact with each other. Virtual assistants like Siri and Alexa use AI to understand and respond to human voice commands, while messaging apps like Facebook Messenger and WhatsApp use chatbots to provide customer support and handle routine tasks. These technologies make it easier and faster for people to get the information and assistance they need, improving efficiency and productivity.

In the business world, AI is being used to improve decision-making and optimize operations. Companies can use machine learning algorithms to analyze data and identify patterns that can help them make better decisions and improve their bottom line. For example, AI can be used to analyze customer data to identify trends and preferences, or to optimize supply chain management and improve production processes.

Another area where AI is making a big impact is in healthcare. Machine learning algorithms can be trained to analyze medical data and help doctors make more accurate diagnoses. AI-powered systems can also be used to monitor patient health and alert healthcare providers to any potential problems.

Overall, it’s clear that AI is changing the world in many ways, and the impact is likely to only grow as the technology continues to evolve. While there are certainly concerns about the potential negative consequences of AI, it’s clear that this technology has the potential to bring about significant benefits and improvements in many areas of our lives. So, we can say that the future is going to be very exciting with the adoption of AI in all sectors.

Today, software and business applications have become more complex and require the best quality and detailed testing prior to their release, deployment, and go-live. Applications need seamless testing and positive test results for business owners to make the proper decision for production deployment. But a simple lack in the test script update according to the latest update in the application may significantly affect the general automated test flow. While Artificial Intelligence (AI) is a relatively new concept, it can be immensely useful in the field of test automation and automatically create new test cases and perform the testing using test bots.

Impact of AI on Test Automation

Automated software testing is a must in today’s time especially when speed to market and great end user experience is key to success. Everyone is aware of the importance of testing for applications. But now the question is what has AI got to offer in this aspect? It can change the approach of testing and how it is implemented. The various potential solutions that AI can offer for the testing ecosystem are:

Reduce Release cycle times
Move from manually creating test cases to the automated way of doing things
Adopt AI, Data, Algorithms, and newer techniques to advance the way you test.

Primarily the use of AI emphasizes test management and the concept of creating test cases automatically. It lessens the level of effort (LOE), with the built-in standards and keeps the process consistent. The second helpful use of AI emphasizes generating test code automatically by understanding the user requirements and acceptance criteria.

AI technology has yet another use for test community that is codeless automation, it will create and run tests routinely for various mobile and web applications without the automation guys writing any code.

How it works?

AI is trained to understand your applications
Tests are composed visually
Functional tests are reliably executed

Training the AI Bots

Simply put AI is the capability of a machine to comprehend the environment and develop the input data to perform a smart action and then work to make it better automatically. Like the Voice search concept, Google Assistant and Amazon Alexa employ AI to process the input and do the smart actions to give the desired answers to users. Here is a lesson/example: the developers allow the bugs, and often they react in place of preventing. To develop AI test bots, developers must guide the bots to process the input data by asking the queries in order to make it perform smartly, same as Google Assistant. The bots will keep on improving constantly with the improvement of the algorithms to identify the input patterns and user behaviors.

How does a Bot learn to Test?

What does an application look like?
What is the business flow we are testing?
The sequence of steps involved in testing
What are the variables we need to consider in testing?

Purpose of AI tool implementation

The purpose of AI tool deployment is not for replacing manual testing, the goal is to explore the possibility of AI and machine learning use to improve the testing and receiving reliable results within the specified time.

Available AI tools

There are many tools being introduced in the marketplace to cope with the changing requirements of AI in the test automation industry. Few of those are listed below:

Appdiff (test.ai)
Applitools
Mabl
Sauce Labs
Testim
Others………..

Limitations of AI-powered tools

AI test automation is still in developing phase and has areas to be worked on. The hurdles you might face while creating AI-powered apps for testing are:

Finding and making all the required algorithms accurate
Gathering lots of data to feed the bots
How bots response to the fed or input data
The process of input of the data will be unending as the algorithms will keep upgrading.

Conclusion

To sum up, AI-based test automation is a great development from the testing aspect and can reduce a lot of effort on the tester’s part. They reduce cycle time and improve the end user experience in the least possible time for any web or mobile apps.

At TechArcis, our experts are trained to provide reduced time to market and great end-user experience with advanced Automation. Our testing professionals provide continuous testing to provide the desired outcome. We can be reached at contactus@techarcis.com

Five Mistakes to Avoid in 2024 While Testing In an Automated Agile Environment

With the IT industry having undergone numerous dynamic changes, it has brought forth a number of new perspectives and objectives for automated testing. This pertains specifically to those areas that have emerged in the past decade such as e-commerce, SaaS applications, and cloud-based services.

Over the past five years, there has been a rapid growth in the number of Scrum and Agile projects while the IT industry has adopted the use of numerous new tools to be in tune with an ever-changing approach. One of the most noticeable advancements in this field has been that of automation testing.

Automated testing offers a number of benefits but at the same time, if not done correctly, it may result in failure. Some of the common sins committed while automating testing in an agile environment include – choosing the wrong time to start automation and making use of inappropriate automation testing tools. The test automation framework also deserves special attention.

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Let us now take a look at some of the top mistakes that you should avoid while running an automation test in an agile environment.

1) Selecting the wrong automation tool

Problem: A popular automation tool may contain a commendable, rich set of features while being extremely affordable. Nevertheless, there may be hidden problems that are not too obvious at first glance. A lack of reliability and insufficient product support are among the problems usually encountered. Both open source and commercial tools can be prone to such issues. An agile environment can be used for performing test-driven as well as behavior-driven development. However, the high licensing cost often proves to be a stumbling block in automating the testing process.

Solution: While selecting a commercial test automation tool for your project, considering the prices and features of the tool are not enough; you need to analyze the recommendations and feedback from those individuals who have successfully implemented the same on real-time projects. The first thing you need to consider is the community support for these tools are powered by support from the user community and not necessarily a vendor. A strong community and active forum will help resolve the issues you may encounter with your automation tool.

2) Choosing the wrong time to start

Problem: A common mistake at the start of test automation is starting on the automation too early. The efforts required in redevelopment of automation scripts does not always justify the benefits, or lack of it, achieved in the final stage of iteration. This is a particularly serious issue for graphical user interface (GUI) test automation. A GUI test automation script is more likely to be broken down by development than other automated test types such as API tests or unit tests. An early start of test automation may result in spending meaningless, repeatable efforts on redeveloping the automated tests.

Solution: Over the phase of a development process, the Quality Assurance (QA) team members should spend a good amount of time in the creation of detailed manual test scripts for automation. If the test cases have sufficient details, you can automate them successfully once the given feature has completed. Writing an automated test from beforehand may not be a bad idea but it should be done only when an individual is certain that further developments within the respective iteration will not disrupt the new tests.

3) Inability to select the right development framework

Problem: The biggest issue with the traditional agile framework is that the absence of user points does not encourage the inclusion of test automation framework development tasks. However, it is far from a secret that a good and effective test automation calls for both framework and tools. Even after spending a few thousand dollars on test automation tools, a framework will yet be needed for test automation engineers so that it fits in easily with an agile development process.

Solution: A test automation framework does not require more than two weeks to develop so you should probably take care of it in the very first agile iteration. However, you should also take note that in certain cases the project requirements may run over a number of iterations before it is completed. The development product can be tested within that duration itself. While the manual testers will have to deal with an increase in their workload, these tests will be limited to development and back-end tests so that the pressure balances itself.

4) The right test case selection

Problem: Another mistake in agile test automation process is to try and automate all the test cases. However, if the focus lies on efficiency and quality, automating them all does not represent a viable solution. It can lead to a useless expenditure of money and effort without contributing value to the overall product.

Solution: Some cases are better off when automated while others do not prove so effective. A test case should be automated only when it requires lot of manual testing and consumes lot of time in executing manually. If you have an application whose functionality frequently changes, then automating the test may prove too expensive and is not a viable solution.

5) Test automation or manual testing: The right way forward

Problem: When the automated testing and manual testing teams within an organization are not on the same wavelength, it proves to be an agile test automation error. You may end up spending a whole lot of effort only to be greeted by a sub-par software in the end. Sometimes, a lack of skills on the part of the manual testing team forces them to hand-off responsibility to the automated testing team, leading to loss of synchronization among the units. Moreover, certain sections of the application receive greater focus while others are not covered at all.

Solution: Ideally QA team members should work closely with Agile teams for a better quality, early delivery and value for business. Whilst this might not be cost effective always and in varied circumstances QA teams can also work in distributed locations. The test cases should be presented in easily readable and understandable formats so that even non-technical staff can understand it. This can be achieved in a number of ways such as keyword-driven frameworks or maintaining a clean code. Moreover, agile development dictates that you have only one testing team to take care of the manual as well as automated testing process, working closely with the team of developers.

These are some of the most common mistakes that affect test automation efficiency of a project, leading to production of poor quality in results. Test automation activities should be considered an integral part of project quality assurance and if you are serious, avoiding most of these mistakes won’t be too big a task!

6 Ways to Improve Performance of Distributed QA Teams in 2022

It is quite common for organizations to have multiple product lines. Take the case of Microsoft. The brand is massive – Windows and Office being the two biggest product lines. Each product line has plenty of associated applications to deal with, and needs a dedicated sprint cycle and release cycle. This goes deeper in terms of inherent dependencies. The same could be the case with your organization. Your QA team could be spread across multiple product teams with equal divisions. And to top it, they work 10 hours ahead of your time zone! To ensure effectiveness, you have even set up a Scrum team that actually works in different time zones.

However, at the end of the day, some questions still shade your mind- How to maintain consistent communication link with QA team that is distributed? How to make sure Scrum environment is giving effective outcome? Are there any innovative processes that QA Testing Solutions Provider can take help from to attain their objectives?

Well, we have compiled a list of 6 ways to improve performance of your distributed QA teams. Read on-

Tip #1: Keep your team updated every day via email

Prior to leaving office, it is your duty to send a mail consisting of brief touch points to your QA team. These touch points are those that don’t stay the same every day- statuses, software build availability, and shifting company priorities.

When you communicate your expectations and thoughts in terms of QA focus for the following day, you save time, and efforts, as all are on the same page.

Tip #2: Let the ideas effuse with the help of IM group chat

Instant messaging tools are nowadays available in plenty. Use IM group chat to let the chats happen 24X7 every day. A thread is a great way for the QA team members to stay updated on every day requirements and enhance everyday performance helping each other, and staying connected.

Tip #3: Maintain a common data pool

This refers to a strategy, an important one- It is about maintaining and using a central repository. This central repository contains valuable data to analyze test results and other test cases.
When multiple versions of test case suites are distributed to team members, it only creates a chaos. Members get confused and frustrated. As every team member gets a different version of the same test case suite, there arises a threat of version control issues which sucks the time, efforts, and energy of team members affecting performance.

Hence, getting a test management tool is important. If it does not fall within budget for any person or organization, you have free, cloud-based spreadsheet applications. These allow access for all the concerned team members and managers.

Tip #4: Maintain a knowledge wiki

This refers to ensuring all team members are provided with a dedicated QA knowledge source or wiki. This source will perform the crucial task of serving unique needs and concerns of your QA team. It will help team members know more about your products, and testing environments. It will help your QA team members to know effective testing strategies and leverage them to achieve sustainable goals. It will help your QA team members to know more about OS testing specifications, and thus enlarge their knowledge base and improve performance. After all, “Knowledge is Power.”

Tip #5: Have minimum one QA team meeting every week

IM group chat and emails are valuable, but we cannot ignore the efficacy of face-to-face interactions, video and telephone con-calls in strengthening individual perception towards a common goal. It is a great way to solve nuances and work towards bigger goals.

Tip #6: Role of favorable feedback and constructive criticism

If your QA team is distributed geographically, it may happen that teams can often miss on valuable feedbacks from remote locations or due to difference in time zones. During such cases, it is essential to develop a common source of communication which happens at one time- a time that is reported to all and agreed subject to everyone’s convenience. In this way you will be able to share favorable feedback and constructive criticism with team members.

Now, are there specific practices you find essential and not mentioned here? Please share.

How Performance Testing can help enterprises in 2022 to stand out from the crowd

Products that have interesting and innovative features always taste the fruit of success. But to achieve the fortune, they must come through extensive testing, and research and development modes. Enterprise product testing, hence, is the key to success. It provides a sound backing to a product, whether it belongs to the consumer goods or software category. It ensures the readiness of a product in the market. Undetected flaws in a product particularly a software product can initiate downtime, which would depressingly affect the overall performance of the organization, it belongs to.

This is the age of technological advancement, in which software applications are composed in accordance with the requirements of consumers. The article focuses on the principalities and top benefits of software testing and quality assurance, during the development of software products.

To increase the performance and acceptability of a product, it is very important for an IT enterprise to test out its product’s every single feature and facilitation. To analyze, and to remove all defects from its base configuration is crucial. And it is not a quick process. It may take months of time for the developers to reach the best solution that will be hitting the market, and striking the end users. However, the well-timed launch of a product also matters a lot in the success of a product.

Alongside the run of ITES and software development companies, there are present a number of software testing service provider firms that offer result driven, quick (as quick as possible) product testing solutions for enterprises. They follow methods that uncover and harmonize the development and functional errors from the application. They make sure that the product meets the quality expectations of users.

If we dive deeper into the sea of software and quality assurance testing, we would find that the whole thing follows three rounds: Component Testing, Feature Testing, and Functional Testing.

The first, Component Verification goes on with the development of the tool. This round of analysis makes certain if the design module and the key requirement sets are being deployed in the development or not. In general, the component scrutiny exercises are performed by the development team itself. But many times, third party testers are hired during the development. There are used unit testing hardware for the effective component testing.

And this is the scenario where TechArcis can help you in agile testing. The analyzers try to spot the integration errors of an IT product. The Functional Testing is performed keeping related products and applications in reference. This advanced procedure consists of heaps of methods that are: Alpha, Boundary, Negative, Automated, Stress and Load, Performance, Usability, Beta, Reliability, and Acceptance Testing.

All these procedures make safe the success and acceptance of a software product. They ensure if a product has features and functions of users’ interest and TechArcis makes it so facile for you to achieve the success with advanced automation testing. To get more information and expert test support you can contact us @ contactus@techarcis.com

Things You Need to Know about Software Testing in 2024

The past half-decade, and most of 2016 markedly saw a surge in new technological trends in various walks of the software industry. While IoT and machine learning driving a shift towards artificial intelligence, the year left a gaping requirement in many fields of software development to catch-up. Software Testing, a phase which has always been a part of the SDLC did see a lot of transformations and new tool set being implemented. 2017 has already seen some old habits fade away and new ones being adopted that are perfect from the technology perspective.

Swifter Releases

Agile Software development isn’t a new concept. It has been around for a long time but over the past year, the concept has undergone a lot of development. Organizations are increasingly favoring adoption of Open source software especially in case of Agile because it allows collaboration among the teams. The result is faster development cycle and reduction in the costs. Developers prefer to use the code that is readily available as solution and thereby increase the efficiency.

The IOT Challenge

IoT is a complex network of connected devices embedded with electronics, sensor and software to enable collection and analysis of data being exchanged. This unique architecture of systems call for various kinds of tests to ensure that the IoT applications function perform as per expectations and are secure. The development of interfaces and connection and communication algorithms, were in full swing during the most of 2016, there wasn’t much interest shown into the area of testing. If IoT as a concept has to manifest itself into the real world, a proper end to end testing of the various communication and interfacing components needs to be developed.

Digital Transformation through Agile and DevOps

If one is to zero in on a trend which has markedly made its mark within the enterprise-wide technology space, it must be DevOps and the Agile methodologies which come bundled with it. A research commenced in 2016 asserted that as many as 54 percent of all the big enterprises across the world, were running digital transformation projects and revolution arising procedures entailing one agile technology or the other. As corporate move towards faster deliveries and pushing releases through the agile pipeline, it is needless to stress upon how important the testing wrapper around it will be. The real challenge in this is not just around having the testing procedures developed, but in deciding as to which ones are the most effective ones to have, that can be turned around in the least of time frames. This will be crucial in terms of minimizing technology spends for companies, while maintaining a competitive advantage over their peers.

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Security Stand point of Software Testing

Do you remember what the buzz words were for the past year, in terms of the technological innovation space? There undoubtedly were ‘IoT’, ’Mobile’ and ‘Cloud’. Look at each o these and try and answer as to what is one common theme which comes out as a concern for all of these? Security! With the enterprise systems and resources moving largely out of premise on cloud networks, and being increasingly access by mobile users, there are grave threats to the working of such technologies from a security standpoint. Trust the world Security Report to realize the true potential of this threat, which clearly states more than 86 percent breaches occurred at the application level in enterprises. Needless to say, the focus in 2017 has to move from just developing applications on Cloud or in the mobile or IoT space, to having they being water tight in terms of security.

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Enhanced automation Testing

As technological innovation came on to transform all the fields of working as we know, automation has come on to manifest itself within the testing arena as well. Automation needs to become an integral part of modern application delivery methodologies like continuous delivery. This is the reason why a whole lot of tools such as Selenium were adopted to bring in automation of test cases in the various testing paradigms followed in enterprises. Most software testing professionals focused on implementing the testing automation for the basic functionality within the application, and this was the direction of the flow in 2016. For an automated software delivery, it makes sense to have a code that can automatically run through a build process to include automated tests. As testing automation is manifested and companies start to realize the benefits in terms of cost savings, customers become all the more demanding. This is why a smarter approach to software testing automation needs to be developed in 2017, stressing customer experience within the entire software testing framework. The automated processes will enable organizations to overcome the seemingly impossible range of variables they have to cater to.

Any new initiative needs to be properly funded, if it is to have its desired effect in the long term. Software Testing and quality assurance is no different and the corporate have surely realized this. Therefore the progression from 2014 to 2016 saw a surge of about 38 percent in the spends on testing budgets. Although 2016 was all about swelling quality assurance budgets and spends, there is a dire need to make sure that this investment bears maximum fruit. This is the reason why optimizing these spends, and putting the money on only the most optimized testing approaches should be the driver in 2017.

2022: How you will let you Businesses Easily Adapt the Digital Transformation

Today’s digital age has brought customers much closer to businesses, which in turn has a significant impact on testing and quality assurance functions. The new age customer loves to stay connected and expects to get the desired information at his/her fingertips. No wonder that they have made companies rethink their business models and operations, accelerate the necessary changes and respond to emerging external market forces to offer customers superior products and better customer service. However, in their quest to embrace the digital future, quality shouldn’t be compromised. Rather, emphasis should be given on quality assurance and testing as they will reduce the time-to-market, thus helping to enhance performance, security and customer satisfaction, all of which will let businesses easily adapt to the digital revolution.

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QA and testing trends and how they will affect the transition to digital

Though customer experience, security and corporate image remain the most vital strategic IT drivers for ensuring the quality of digital transformation, the emphasis is also given on efficiency and effectiveness as significant testing and QA objectives.

According to the World Quality Report 2016, higher QA and testing spends wasn’t triggered by a higher level of digital focus. Yet, in their bid to improve the time to market, businesses are increasingly adopting DevOps and continuous integration, which in turn influences the QA process.

The report predicts that among the entire budget allocation for QA and testing for new developments, new digital solutions like mobile, cloud, IoT and BI/BA will claim a significant share of 60%.

To stay ahead in the competition, agile testing and continuous delivery will be increasingly emphasized upon. When it comes to agile methods, the development and test teams need to have a string relationship and collaborate effectively. For example, agile scrum is a holistic, flexible product development strategy that’s changing how testers function by encouraging teams to self-organize and ensure regular communication. Continuous delivery too is going to be in the limelight as it would help in early detection of problems, help in assessing the effectiveness of a change and decide whether such a change can meet the end-user expectations or not.

Setting up of TCOEs to align quality efforts in sync with business needs is another trend that’s going to stay. Focus on mobile testing and cloud-based testing is also going to pick up and QA and testing teams will increasingly need to find ways to allay fears related to privacy, security and control of data.

Recommendations for beating the competition

Security: With digital transformation, security would demand a multi-layered approach. For example, you can correlate multiple events from different systems using artificial intelligence and machine learning, which would help spot sources of a breach and learn adaptively how to offset it. Companies should research new technologies, such as ephemeral systems, software-defined security and homo-morphic encryption together with considering new processes like bringing the development, testing and operations teams together to offer smart, pervasive security.
Automation: Virtualization and automation are increasingly replacing human interactions with codes that handle everyday tasks, thus bringing a huge change in how business process, IT infrastructure services and interactive customer services function. To get ready for a future where more complex tasks will be performed by software apps, small steps can be taken. This could include automating interface creation or testing and coding hand-offs from requirements through deployment. Leveraging emerging tools like modeling languages is also a good option as you can use it to describe processes that a human and a computing system would both understand.
APIs: As APIs become an integral part of company resources that encourage innovation and drive revenue, businesses will need to find ways to develop, share, use, secure and monetize APIs. One way is to design services that don’t just support technical functions but even specific business capabilities like an inventory check etc. A successful strategy for API-driven ecosystems would also need continuous integration, DevOps, testing, logging and tracing, messaging, monitoring, service registration and discovery among others.

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Final words

QA and testing is crucial for any digital transformation journey. So, businesses need to identify the right tools, measures and methodologies to make their organization future ready and assure top-notch quality of their products to enhance customer experience. With TechArcis, you can stay ahead of the curve by being ready to undergo a digital transformation without sacrificing quality. Contact us today to know more.

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Month: January 2022