Bots and AI: The Future of Software Testing and Quality Assurance

Over the years, the evolution of technology has made the world experience the idea of innovation. Right from the introduction of the world wide web to the first-ever smartphone, technology has always transformed the way we live.   

One such aspect of advanced technology that has redefined the dynamics of the present and future world is the introduction of robotics and artificial intelligence. However, the greater innovation is these technologies making their way into the development process of other technologies, such as improving automation testing services.   

Yes, we are talking about Artificial Intelligence and Robotics. AI bots and artificial intelligence into software testing have not only made things a whole lot easier but have given the cost proficiency, ease of use, and necessary time-productiveness. And therefore, these technologies have managed to make a special space for them when we talk about software testing trends of 2021 and beyond.  

Though it may appear that the idea of Artificial intelligence has just made its way to the world a couple of years back, the very concept of AI and bots has grown rapidly. More importantly, people have adapted to these aspects of technology in a very quick manner making AI and Bots part of the new normal.   

The exemplary potential of AI-powered and machine learning technologies in software testing have made people envision the entire purpose of bots more quickly, redefining the way we interact with QA Software testing services.   

In case you are curious to learn how they can change things for the better, let’s dive and explore.  

The Bots and AI Effect on Software Testing and Development  

  When it comes to the impact of Artificial Intelligence and Bots on software testing service providers in India, some common areas which have been leveraged using these technologies are related to the improvement of test scope, debugging, and continuous testing goals. Let’s explore these in a bit more detail.   

1. Testing Scope & Workloads  

One of the most common challenges that QA software testing services tend to face is the increasing parameters of the test as the project progresses. This usually leads to the extensive buildup of workload on the testing professionals who are already have constrained ability, resources, and time to deliver with efficiency.   

However, the use of AI Bots allows testers to redevelop the existing test cases while adding all the additional parameters that appear during the progress stage. This simply helps to improve the scope and coverage of the testing procedures without burdening the testing teams. Also, these bots can help testers to run parallel tests and customize the efficiency tasks as the project reaches its advanced stages.   

This is why when you start working with the best software testing company, things start to streamline quicker as their testing teams have full access to practices like robotic test automation that has the potential to oversee, examine, and assist the DevOps and QA teams in simplifying the testing procedures.  

2. A More Efficient Approach To Debugging  

Since AI bots have the potential to run 24/7, they can be used to handle all kinds of debugging tasks as per the requirements. This simply helps to expand the total amount of time for running tests without any human intervention. Moreover, testers could devote their time to more productive tasks while leaving the debugging task to the bots. Besides, the technology enables testers to examine the test outcomes and work on any issues that are reported by the system.   

Furthermore, the developers and testers having coordination with the technologies like automated robot testing to transform the code. Ultimately, such an arrangement helps to get rid of any bugs and drive the full potential of the test procedures with an immediate check on weak spots.  

3. AI-Powered Continuous Testing  

When it comes to the use of artificial intelligence technology in the robotics process, it can be leveraged to advance the continuous testing process, expanding the existing capabilities of the traditional test practices. Consider using robotic process automation to create reports related to deviation and distinguish the data that is polluted.  

Also, the use of artificial intelligence technology in the QA process allows testers to avoid any grunge and aim at improving the quality of test procedures. All in all, when you are trying to focus on continuous testing, using AI technology allows you to find more viable solutions to all your test project requirements.   

As AI-powered bots are built using Machine Learning and Natural Language Processing technologies, they can help streamline all the requirements related to QA and software testing.  

Read more: Benefits of AI and Bots in QA operations

Automated Regression Testing: Learning Common Mistakes & Best Practices

With the ever-growing demand for technology, the development and testing process has become extremely tricky. From modification of code to implementing new functionalities, every major and minor requirement could lead to unexpected behavioral changes in the product.   

However, most development brands have found the solution for the same by making their way towards regression testing services. Regression testing allows testers to identify defects in a recently built code while allowing developers to address all the undesirable outcomes right away.   

Regression testing is all about re-running the test scenarios made for every build until a new functionality or code is deployed to the system. Such arrangement allows validating that the previously developed code and functionality performs seamlessly for all the new changes introduced. In short, regression testing helps testers to confirm that any new build has not caused any regressions or adversely affected any functional elements of the system.  

Regression testing these days has become more of a technical concept with the introduction of automation. Automating regression tests not only allows rapid compilation of the code for the last build to track its accuracy but even helps to save time, money, and resources. However, there are certain common mistakes and practices that are associated with regression testing. In the next few minutes, we will try to highlight the entire idea for automating regression tests along with common mistakes that you are likely to make when you resist hiring regression testers with professional expertise.  

Let’s begin.   

When To Automated Regression Testing?  

Regression testing is all about repetitive testing, and most software testing companies tend to struggle when they have to accommodate the same into their SDLC schedule. Thanks to automation as it is the only way to resist all those extremely consuming manual testing hours on checking the code.   

Nevertheless, the most important question that comes with the use of automated regression testing is to know the right conditions to use the technique. Some of few critical situations that might need you to hire testers for regression testing automation include:  

  1. Automation can be done easily for all the pre-existing functionalities.   
  2. When manual testing takes a toll on time and resources, automation saves the day.  
  3. When the system needs to undergo several iterations with the code.   
  4. When certain system components start to show defective functionality.  
  5. When the defined production costs involved budget for all the updates and fixes.  

Apart from these, there are so many other functionalities, conditions, and circumstances, where automated regression testing could help you simplify the entire quality assurance process. Since automation has the capability to resolve all the time and resource-related concerns with a development project, there are few important concerns surrounding its implementation.  

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Getting Started With A New Product: 5 Tips To Follow Before You Begin with Your Next QA Initiative 

Common Mistakes With Automated Regression Testing  

At times, automation may appear a solution to all the testing issues, but still, every quality assurance service provider firm resists the use of automated regression testing service for all their projects by default. This is because automating a task that involves regression testing may involve mistakes made by the QA experts. Some of these can be highlighted as:  

  • When technical teams do not find value in regression tests  

Regression testing is more of a process and not a task that reflects the immediate value to the project. This is why most testing professionals tend to develop a belief that investing in new features is better than investing in retesting the same features again and again. However, the truth is skipping on regression tests could make your project miss the opportunity to launch a seamless product into the market unless you have coders and testers who have the potential to develop the most precise builds.   

  • To skip the use of validation  

Test scripts made to execute without validation can be disastrous when you need to automate the regression tests. For instance, there is a webpage that needs the user to log in, validation allows testers to validate the achievement of the task, I.e., logging in to a page.   

On the other hand, regression testing service providers need to focus on using checkpoints for script validation so that web objects, page parameters, and any text can be verified before execution. Also, checkpoints should be placed at all the necessary points of code that need validation.  

  • To stick with visible validation only  

The next big mistake that testers make on their way to regression testing is failing to realize the importance of validation for non-visible objects. This can be related to the use of a POS system where the user is able to see the confirmation of the order on the screen, but the landing of information into the database is not assured.   

More importantly, when testers restrict validation only to visible elements of the project, it leads to so many errors compile in the background.   

  • Record & Playback Features  

At times, it may appear that record and playback features help testers working for a regression testing company to simplify the writing of test scripts. But the right way to create the most successful regression scripts is generating only the skeleton of the code using record features. Otherwise, the testers might miss all the chances of customization with the test scripts negating the benefits of automation.  

Read more: Best Practices for Automated Regression Testing

Mobile App Testing – Emulators Vs Simulators Vs Real Devices

A simple definition of mobile application testing would go like this “Mobile application testing may be a technique by that associate application code developed for hand-held mobile devices is tested for its practicality, usability, and consistency. Mobile application testing could also be automatic or manual reasonably testing.”

To go forward assuming to test a mobile application for an online flight ticket booking system we would take the following in note.

• Functional Testing
• Compatibility Testing
• Localization Testing
• Laboratory Testing
• Performance Testing
• Stress Testing
• Security Testing
• Memory Leakage Testing
• Power Consumption Testing
• Interrupt Testing
• Usability Testing
• Installation Testing
• Uninstallation Testing
• Updates Testing
• Certification Testing

Mobile Testing – Emulator Vs Simulator Vs Real Devices

Suppose we have a tendency to developing an associate application for a flight price ticket booking system. Once the product is entirely developed, as vicinity of mobile application testing services, we want to visualize if the application is functioning for sure with all the majorly used devices like automaton phones, iOS and alternative different types of tablets and iPads.

To do this type of testing, we want to acquire every device and so we will test if the applying behaves as per expectation. Affirmative!!! You thought right, as a product owner one can rebelliously notice this terribly big-ticket to obtain such an outsized variety of mobile devices and do testing. Thus is there any good alternative available?

The solution to the current drawback is to use mobile simulators and mobile emulators. These are primarily software programs designed to supply simulation for vital options of a smartphone. They’re terribly similar in nature, thus typically, they’re used interchangeably.

Let’s compare however testing on associate Emulator/Simulator is totally different from testing on a true device –

A simulator/emulator cannot mimic the subsequent options.
•  Mobile device battery
•  Mobile device’s camera
•  Difficult to mimic interruptions like incoming calls and SMS.
•  Not the most realistic simulation for mobile device memory usage.

Read More: Distinction between simulator and emulator

Key Considerations For Automated Web Testing

Website is the key focus area for any business these days. Especially when the world has moved so quickly to digital platforms, a website is a platform to showcase any organization. As more and more business operations have shifted to advanced tech platforms, it is necessary that modern websites should be made to meet the highest benchmarks of quality and performance.   

Nevertheless, the sudden shift of focus towards web testing services has given a boon to the agile operational environment and has helped tech brands to involve a shift-left approach on their way to workflow validation. The only purpose behind the use of automated web testing is to skip the human intervention and CI/CD pipelines that are part of the heavily consuming manual testing process.  

More importantly, businesses need automated web tests to offer a highly effective user experience and user interface. Web automation testing allows to validate and verify all the components of the website while eliminating any defects that can overwhelm the users on their way to seamless usability.  

Key Considerations To Effective Web Application Testing  

The Selection of Tools  

The first thing that you need to keep in mind on your way to leverage web testing services is the select the appropriate test framework and tools. This might need you to spend some time on research finding the right platform that can help you run test suites with the advantage of record and playback. Besides, the tools must be made to allow rapid report generation, take screenshots, and offer rapid error tracking.  

Codeless Automation Tools  

The next important thing that you need to consider on your way to quality website development is to opt for codeless automation tools. After all, the entire idea behind web automation testing is to ensure easier script maintenance while preventing any unwanted expense on time, money, and other resources.   

Process Common UI Elements  

Either you hire testers for web testing, or you have an in-house team of developers and testers, it is vital that developers must process common UI elements into the development process. Such an approach allows testers to prevent any struggle understanding the UI elements and track errors.   

Shared Object Repository  

When you need your developers, testers, and all other technical members to work collaboratively, it is vital that any test requirements, already compiled test scripts, and other test details must be kept in the shared repository. It allows easier test maintenance, cuts any hassle testing, and saves costs on experimentation. Also, the approach allows increasing the speed of the test process while allowing the test to move forward quickly.  

Maintain Standard Organizational Best Test Practices  

Last but very important, testers need to stick with the best code writing, compilation, and review process on their way to achieve the highest standards of organizational best practices for testing. This might even involve the use of web testing tools that can offer additional testing benefits to improve the overall outcomes of your web application.  

Read More: Automated web testing challenges

10 Key Elements For Successful Cloud Migration: Integrating Cloud Testing Services Into The Process

With time, the cloud has become the essence of the IT infrastructure for every organization. Moreover, the technical executives these days have their entire focus on upgrading their key enterprise applications to the cloud while making way for the business goals.   

In fact, the use of servers and computers has enabled businesses to attain the highest level of performance benchmarks. And the modern business environment that has some crucial requirements to streamline resources has found the cloud as the path to futuristic outcomes.   

Nevertheless, most business institutions right now are heading on to a race for taking mission-critical applications to the cloud, and the rush to lean on futuristic solutions has increased the prominence of certain mistakes. Though the idea of cloud migration has enabled the best use of hardware and software resources to attain scalability goals, there is still a huge scope for nurturing efficient resource utilization.   

Since cloud technologies have all the potential to increase business operations while diminishing any chances of downtime, enjoying seamless scalability with your cloud migration objectives needs to align well with certain best practices. With years of experience handling cloud testing services, here we bring you the list of 10 key elements that make it to successful cloud migration.   

Let’s begin.   

Deciding The Migration Architect  

Cloud migration is a highly strategic process, and therefore it needs extensive focus on planning the migration architecture. This usually involves defining the path to data migration, the solution requirements, benchmarking priorities, and any refactoring requirements that can help in a successful migration.  

In other words, the cloud migration process begins with technical decision-making and planning on the project. Besides, migration architecture allows working on the project-critical responsibilities such as cloud software testing that must be worked to ensure the success of the project.  

Cloud Integration Level  

Any cloud migration project that demands migration of on-premise data center to the cloud needs some integration. However, the integration could be fostered in two ways which can either be shallow integration or deep cloud integration.  

The shallow cloud integration is more of a lift and shift process where you only need to shift your on-prem application to the cloud without any need for server changes to make a suitable environment for running the application. This means the application is lifted, moved, and shifted to the cloud as it is.  

On the other hand, deep cloud integration is meant to offer additional cloud capabilities to the application. It can be auto-scaling, dynamic load balancing, or implementing serverless computing capabilities to the application while defining cloud-specific data stores such as Amazon S3 or Dynamo DB.  


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Single Cloud or Multi-Cloud Selection  

Cloud migration is a highly technical process that needs business leaders to make so many choices. One such choice needs to be made with selection between single and multi-cloud platforms. At times, the migration only needs a single cloud environment to work optimally, while there are applications that need a multi-cloud environment to prevent any disruption.  

Also, single cloud integrations are easy as they only need your technical team to focus on a single set of cloud APIs. However, working on a single vendor solution often involves downtime as any situation like server issues or closing of vendor brand would make you compromise a lot with your operations. On the contrary, using a multi-cloud approach could help you avoid all such issues but may need you to spend a little extra on the entire development, deployment, and maintenance process.   

Besides, it needs you to have a careful selection between different multi-cloud models when you need to yield the best possible outcomes within the defined budget. For instance, you can choose to run:  

  1. One application in one cloud and other applications on a different cloud.  
  2. Run single application on multiple cloud servers.  
  3. Building a cloud-agnostic application which means building applications that can run on any cloud server.  

However, each of these models has its own limitations and benefits, which must be understood well before any migration process is initiated. Also, you can run some usability tests and user acceptance testing within your team to find out what model can best serve your needs.   

Define Cloud KPIs  

Once you are done planning and making the initial moves with your cloud migration strategy, you can start with the planning of KPIs. In most cases, KPIs surrounding the application and the service are defined, while it is necessary that any KPIs that can improve the cloud migration and post-migration service should be considered.   

Some of the few important categories that you need to keep in account on your way to defining KPIs include user experience, performance, infrastructure, and business engagement. These metrics may further follow page load time, response time, throughput, CPU usage, memory usage, conversions, engagement rate, etc.  

All in all, it is essential that you must know all the metrics that can cause a maximum impact on your cloud migration model.   

Create Performance Baselines  

Creating a performance baseline is about measuring the performance of your application to reach the acceptable criteria. Baseline also helps you validate the improvements made after the migration while giving insights on any problems that you may encounter during or after the launch.   

Nevertheless, it is crucial that the baseline metric must be decided well in time so that the application data can be collected for a defined duration. Most of the time, the technical teams and even the cloud testing services recommend collecting data for a longer period as a larger amount of information can help with better representation.   

Above all, it is crucial that your data collection model for baselining must be focused on collecting the right type of data that can aid your business and operations with respect to industry standards.   

Set Migration Component Priority  

Another key element that you need to keep in mind on your way to cloud migration is to decide on the priority components. The process might need you to identify the connections between the services and the components using a performance monitoring tool. Besides, you can create an application dependency map to determine which components are most significant on your way to cloud migration.  

Such wise actions help you to understand that if you need to migrate the whole application in one go or there are certain internal services that must be migrated on priority to keep the operations flowing. The approach also helps you to resist any impact that your customers have to bear while your team is working on the cloud migration process.    

Application Refactoring  

Before your application is taken to the cloud, it is vital that you must have a quick tour of your application to identify any possible areas that need refactoring. Some of the most significant checks that you may need to make on your way to refactoring include:  

  • To check that application should run well on varying cloud instances that might need dynamic scaling.  
  • To improve any resource utilization capabilities  
  • To craft a service-oriented architecture for taking all your services individually and more quickly to the cloud.  

Strategize Data-Migration   

From planning to refactoring, every stage of cloud migration is easy until you need to work on data migration. Since the data access methods are dependent on the on-prem model, moving data to the cloud could affect the performance. The situation could be equally tricky when you have data on an on-prem server, and the data needs to be fetched in the cloud.  

However, you can involve a cloud testing company to keep a check on the system while you choose between bi-directional syncing, one-way synchronization, or use a cloud migration service like AWS to meet your data migration goals.   

More importantly, the planning of data migration when taking your application to the cloud should be worked with precision while taking insights to the cloud migration architect as it is the only way to resist any failure of expectations.   

Making A Switch To Production  

Once you are done working on the data migration process, the next big hassle that you need to encounter is planning to switch over the production from on-prem to cloud. This needs measuring of the architecture and complexity of the application model while keeping a watch on data.  

It can be done in two easy ways:  

  • One is to make a quick switch from on-prem to cloud, validate the system and switch traffic from on-prem to cloud.   
  • The second way works by moving a few customers to the cloud from on-prem in different windows of time until all the traffic is moved to the cloud.  

Application Resource Allocation Review  

The last stage of migrating your on-prem solution to the cloud is resource optimization, as the best thing about taking your operations to the cloud is to enjoy dynamic resource allocation.   

The process might need you to reach your team for creating resource distribution plans and scale your application and resources as per the requirements. Either it is adding more resources to the application or reducing the complexity of the architecture, dynamic scaling on the cloud can be used at the maximum to ensure hassle-free experiences.  

How Could Quality Assurance Help With Cloud Migration Goals?  

When it comes to cloud migration, the process involves sending applications and data to the cloud from an on-prem data center. On top of that, the process involves an extensive shift in the infrastructure configurations in order to align the existing technology with a new environment. All this process involves the use of cloud hosting services like AWS or Microsoft Azure that can help to foster the IaaS, Paas, or SaaS models.   

Here comes the role of cloud testing services. A cloud testing service provider on your way to cloud migration could help you with Pre-migration advisory, Assurance during migration, and validation of the system after the migration is achieved. Also, cloud assurance could help you guide throughout the migration route to handle any unexpected challenges that you might face with the structural efforts.   

Moreover, when you hire testers for cloud testing, the existing decision to migrate to the cloud becomes easier as they have all the knowledge required to lead your cloud initiatives for improved business performance.   

In a nutshell, having a robust cloud quality assurance plan in place is vital when you need to harness all the operational benefits that you need to yield with taking your existing operating system or software to the cloud.   


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