Test Automation Strategy to Achieve Product Development Goals


The full potential of test automation lies in a well-formulated strategy. As the demand for feature-filled applications rises, independent software vendors and organizations focus more on delivering reliable and efficient products within strict product delivery deadlines.

However, as more and more companies are adopting agile and DevOps methodologies making application development a complicated process, manual testing can no longer be relied upon. When it comes to ensuring the quality and functionality of the software while speeding up its market launch, automated testing is the only viable option. Some of the key strategies adopted by firms to ensure best use of test automation are given below.

Steps to set your test automation strategy

  1. Ascertain your goals

The first step is to determine a successful enterprise test automation strategy and find out which test to automate. The best example of test cases are the ones that run often, are time-consuming, requires an extensive amount of data to perform a task, can be tested over multiple platforms, and have a high probability of test failures and risk.

The first strategy for successful test automation is methodically planning it out and defining the scope and goals of test automation.

2. Preparing a test approach

The test approach influences testing practice in organizations. With test automation and agile methodology, testing is becoming an integral part of the software development process. Once the team finalizes and decides to adopt a specific test approach and determines appropriate testing levels, roles and responsibilities are assigned to the respective team members.

Deciding on the right testing method will provide the maximum value when automated. Different testing levels requires various testing methods. Below are some of the testing methods that can help you to achieve maximum values.

  • Unit Testing

In agile methodology, unit testing is an important test automation strategy as it yields high ROI. The developers can write, execute, and maintain a small piece of code in form of either function or method, which are used during unit testing.

  • Smoke Testing

Smoke tests verify and provide instant feedback about the system builds. It confirms that all complicated functionalities are working without errors and defects. For an efficient smoke test, a few manageable test cases should be selected to quickly execute the tests.

  • Regression Testing

Whenever new features and functionalities are implemented in software, it introduces new errors in the build. Regression testing allows checking these features repetitively to detect defects. Regression testing can be automated to reduce the burden, time-to-market and cost.

  • Component Testing

Component testing tests the comprehensive business value and does not focus on the quality or quantity of the entity. Component testing can be automated to reduce time and expenses.    

  • End-to-End Testing

End-to-end tests can be complicated. Hence, the testers need to select the right tools, which are easy to use, maintain and scale to ensure high ROI.

  • Integration/API Testing

The software development relies on API and SDK, hence validating the comprehensive application performance is critical. Integration and API testing confirm the system’s performance and stability with external systems. Automating frequently run API tests is important as some of the changed codes may affect the API functionality.

  • Cross-browser Testing

Running app’s test manually over multiple browser / operating systems / devices can be a time-consuming task. Automating the cross-browser tests enables you to run these tests quickly. It is proven that cross-browser test automation has increased the test coverage, reducing the testing time and effort significantly.

3. Selecting test automation framework

Writing and running tests is based on detailed guidelines like coding standards, procedures, test-data reporting and more, etc, which is known as test automation framework. Here is a list of test automation framework,

  • Linear Scripting

Linear scripting is the most useful framework. With record and playback features, you can record the steps in sequence and play it whenever you need them.

  • Library Architecture

Library architecture identifies, divides, and group common tasks. The functions are saved in the library and used whenever the test scripts are required to use them.

  • Modular-Based Testing

In this type of framework, an application is divided into separate units and the testing is conducted in the unit base. Each part has respective test script, which is later combined as merged tests.

  • Data-driven Test

The errors found in linear & modular-based, data-driven test overcomes it. It allows one to store data and access it from the external file to test the same feature with different sets of data, whenever needed.

  • Keyword-driven Test

Keywords are stored externally and are used to represent or test the GUI of an application. The actions are tested following certain guidelines and are usually separated from the test logic.

  • Hybrid Testing

The hybrid testing facilitates application flexibility and provides accurate test results.

4. Selecting the right tool

As a part of a test automation strategy, it is important to select the right testing tool. Selecting the right automation tool is based on an understanding of the technology upon which an application is built and test requirements of the Application Under Test (AUT).

One of the main aspects of selecting the right automation tool is to address the testing demands of certain kinds of applications. The right automation testing tool must be compatible with the platform and easy to use.

As the number of platforms grows, the automation testing tool to validate application performance across the platform must be wisely selected. An ideal test automation tool is the one that supports cross-browser testing and has the ability for maximum use of the test scripts.

5. Create and run the tests

The next step is to write and execute the scripts. The following are the steps,

  • The test cases must be written in a way that enables the testers to use it in multiple projects
  • To remove the redundancy, it must be validated to see if a similar type of case has been written before
  • The test cases must be written in such a manner that anybody other than a test scripter would be able to execute it
  • Based on the feature and component, the user must prioritize the test cases
  • The high-priority test cases must be executed first

6. Maintaining test scripts

Scrutinizing testing parameters is important for maintaining test scripts. Regression test may take more time for the applications, which are rich in features, resulting in the importance of test automation to wane out.

Maintaining the test cases plays a crucial role; hence test cases must be optimized and categorized. It allows evaluation of test case subsets, and clearly defines the purpose of test automation. Process of test automation becomes easier with smaller test cases.

Importance of a successful test automation strategy to achieve product development goals

Importance of test automation strategy is to help you achieve product development goals. Finalizing test automation strategy helps in,

  1. improving test accuracy – Test automation improves accuracy by reducing human errors, which occurs in manual testing
  2. saving time and effort – Test automation reduces time and effort by delivering results faster
  3. offering test coverage – Test automation improves software quality by expanding the depth and scope of testing and ensuring a thorough examination and investigation of various software features
  4. increasing test case efficiency – Test automation improves test case efficiency by making slight improvements during the testing phase of software development cycles so that the product could be launched in the market on time
  5. Reducing maintenance cost – Test automation allows you to change and update testing methodology, reducing maintenance costs
  6. increasing the speed of the test execution – Test automation allows test experts to focus on more challenging, case-specific tests while executing redundant and lengthy test cases
  7. reducing manual intervention – Test automation can run with minimal manual intervention, which can be long, prone to errors and tedious
  8. analysing involved risks – Test automation analyses involved-risks delivering accurate results within the stipulated time


Having a successful testing strategy and framework can impact your business and organization in many ways. Test automation encompasses more comprehensive testing allowing you to accomplish complicated test automation tasks easily. A right automation strategy promotes the reused cases of critical components and improves employee productivity. The test automation strategies help in understanding business objectives and defining the product development goals.

Yethi’s well-managed Test Centre of Excellence can efficiently handle the test resources and infrastructure while ensuring the quality of applications. We help you meet your business objectives and product development goals with our test automation strategies.

Our proprietary 5th generation codeless test automation tool – Tenjin is an intuitive automated test suite. We have a test repository of 450k+ test cases, which help us to offer you high test coverage throughout all aspects of digital transformation and application testing like functional, UI/UX, performance, compatibility, security, geo-based and network testing. This smart tool blends with all test automation framework facilitating end-to-end testing like unit, regression smoke, integration, cross-browser and many more.

Importance of Continuous Testing in Continuous Delivery and Integration

The quality of software can be determined when it adapts to changes and promptly responds without any delays. However, overtimes with extensive use the code may change, and manual testing needs to be conducted again to identify the impact of these changes on the functionalities of the system.

A software is manually tested at the software development stage but comes with several drawbacks as follows:

  1. Manual testing of regression packs delays the release of the software. It takes weeks and months to get feedback from the developers as the written code is tested. The entire process is relatively time-consuming and expensive.
  2. Even the most advanced and expert testers may not perform regression testing with accuracy. It might be hard to detect the impact of the set of changes in a complex software system through inspection.

All about Continuous Delivery

Alongside code writing, it is equally important to focus on quality during continuous delivery. Testers work closely with developers to help them create unit tests. They start by writing code to automate the small number of tests that cannot be covered by unit tests. Continuous delivery allows us to rapidly test product with our users and collect data on the possible outcome. Continuous delivery enables you to carry out experiments quickly in the on-going production stage.

With continuous delivery, there is no need to ensure quality of software at the end of the development cycle before its launch. The code goes straight to production allowing for quality check at the same time it is created. The testers closely work with the developers to ensure that the quality is maintained.

Automation propels testing and focuses on the quality of the applications, and so most of these applications are tested in the unit testing phase itself. The tested code is deployed at the production stage for continuous delivery as soon as it is checked into source code management and passes a deployment pipeline.

Why Continuous Testing is important?

Developing software and testing them are not two separate activities, but a part of the same equation. Hence, testing should be performed simultaneously along with developing the application. Automation like test automation, deployment automation, and environment automation allows you to execute these changes faster with minimum effort.

Application and systems need consistent updating of test documentation to keep it ready with the changes in the applications. Many different types of tests, both manual and automated, need to run continuously throughout the delivery process. Followed by continuous delivery and integration, continuous testing automation is included in the deployment pipeline. The deployment pipeline allows creating packages that can be implemented in any environment and runs unit tests, providing feedback to developers.

These test packages need to pass comprehensive automated tests that run against them. These packages are available for self-service other environments for activities such as exploratory testing, usability testing, and ultimately release after they pass all these automated tests. Automation testing is important for continuous delivery, which is followed by continuous deployment. Hence, it gives rise to the need for continuous testing to keep a track on changes.

In the deployment pipeline, the changes are implemented simultaneously with continuous integration during product release. If the common defects are not highlighted in the deployment pipeline, it could delay product release. However, some tests are improved and updated in the pipeline if defects are detected later. The focus here is to find the issues as early as possible to reduce the release time of the product.

How Continuous Testing can improve Continuous Delivery?

Implementation of continuous testing in continuous delivery can benefit your delivery pipeline. The following are the points that would explain how continuous testing can improve continuous delivery: –

  1. Executing API, UI, and Performance testing along with Regression testing will ensure the quality of the app in various customized cases. Continuous testing will allow the developers to perform a live test of the implementation, functionality, and behaviour of their code with testing tools.
  2. The DevOps team can implement parallel tests with automatic notifications after making the necessary configurations to the CI environment. Testers can notify developers whenever there is a failure in any build component. Testing of all changes can be done automatically using continuous integration.
  3. The QA team can verify and validate the product quality by running regression, load, and functional tests deployment. The automation testing will be continuously carried out if the test module configuration is correct. In case if there is a build failure in the system, it can be fixed by manual testing.  

There are some best practices for continuous testing in continuous delivery:

  1. Continuous testing enables you to test operating systems and devices before production. It saves money in the long run as instead of running a large volume of test cases, load tests implemented every day at specific target areas reveal smaller bugs and fix them immediately.
  2. Accurate results can be obtained conducting test simultaneously during the development phase as compared to running tests in a controlled lab environment.
  3. Detecting defects and fixing them will be much easier and can run at the same time if the entire test suite is divided into several smaller tasks.
  4. To have adequate knowledge and detect the issues or discrepancies in app architecture and test automation, the metrics must be properly used. Proper use of metrics can also help up to prevent the risk of failures and its impact.


Continuous deployment and continuous delivery require a well-structured and planned environment for continuous testing. In absence of which CI and CD effort would not be successful. At Yethi Consulting, we follow an agile test automation framework. Our scriptless test automation platform, Tenjin, is a plug-and-play banking aware solution. Its robotic capabilities enable them to learn and adapt to the application and its updates. Regardless of the complexity and number of updates, Tenjin facilitates continuous testing, minimizing the manual effort and speed up the test execution.

All About Crowd Test Automation

The world of mobile apps is vast and competitive.  The quest for user attention requires significant investment in ensuring apps are accessible, easy-to-use and cause-no-harm.  In house Quality Assurance practices and rigor allow organizations to iron out a majority of the kinks in their applications.  While such practices allow us to understand app stability and performance in a controlled environment, if your app is to be used by millions,  you would be well advised to look at a more real-world simulation with all its uncertainties before seeking out paying clients.

Crowd Testing allows you to invite a wide team of professional or amateur “testers” to use your application in a “real-world” environment, allowing you to monitor its performance across diverse scenarios.   

1. Beta & Compatibility testing

The final steps for testing are beta testing and compatibility testing. The in-house testing can hint at possible defects, but the scope of crowd testing is much wider and elaborate. The in-house testing team would lack in resources and time and may tend to overlook for complex areas. A specialized crowd testing firm follows a more recent trend such as cloud computing or BYOD (Bring your own device) resulting in compatibility across varied configurations.

2. To test wide Usability

When you are addressing a wide market and seeking for tangible data, crowd test automation is the most appropriate solution. It gives access to data like how the product is used, how the interface is navigated, which feature gets more engagement and so on. Crowd test automation helps you in procuring viable feedback maintaining your budget constraint. It covers wide provincial usability.

Benefits of Crowd testing

  1. Diversity

With the diversity of language proficiency, level of expertise and experience, crowd testing team has a wide range of attributes, which in-house QA team lacks. Rest assured that organizations will get an unbiased approach as the software will be assessed by a team who has not developed it. Moreover, there would not be an unnecessary compulsion of getting the desired result over an actual one.

2. Hardware and environment variety

Crowd testing allows test automation to be carried on a variety of devices, considering many real-world environments. Multiple testers in the crowd testing would be using a diverse set of devices to run the software. There is likely to be different form and factors of hardware and operating system. Crowd testing team use their skill, knowledge, and expertise to discover functional and user experience limitations in products and platforms. This practice provides real user testing in highly varied real-world conditions at an extraordinary scale and efficiency.

3. Efficiency & Scalability

Crowd testing is just not limited to hardware and software combinations big consumer software corporations but equally beneficial for the smaller or non-consumer-facing software companies. The organizations can test their software at scale in real-world conditions. This practice makes companies be more prepared and confident about what they release in the market. 

Crowd testing can be conducted based on-demand. It is flexible and whenever you need them, you can avail it by implementing a complete and final test cycle without pulling your resources out from different projects. But in case crowd test is set-up on regular basis it would be able to keep up with the need for continuous development cycle. Continuous testing would run parallelly to continuous integration and delivery.

A quick look at some of the benefits of crowd testing:

  • The crowd testing is available 24/7
  • It provides a fast and unbiased continuous testing source
  • It provides valuable feedback on the functionality and user-friendliness of your websites, mobile apps, chatbots, or games from an end-user perspective
  • It is customer-centric
  • Its emphasis is in the testing and development of user interfaces and visual
  • It is flexible, scalable, and quick for your digital software development

At Yethi Consulting, we offer intelligent testing services covering end-to-end product and testing solutions. Our flagship 5th generation codeless test automation tool – Tenjin is AI-driven. It is developed with new technology in automation testing for core banking application and includes a repository of 450k+ test cases for banking application in software testing. Our no-code less code capability of AI-driven test automation tool releases you from the restrictions and limitations of your development process. With seamless integration and performance, Tenjin can run on multiple devices and operating system, reducing your cost, time, and human effort. We are making the process of continuous testing simple, affordable for the agile and continuous delivery team.

Importance of Artificial Intelligence in Banking Software Testing

The current 5 years ongoing trend speaks of 50 million deployments in 2015 annually, which if broken down would be one in every second. There is no reason not to believe that by the end of 2020 and beginning of 2021, the number of software deployment would certainly rise. Can you afford to release your software without being tested? No, you cannot.

Testing software before its release has become a conventional choice for software developers and testers. Building a feature-enriched application does not just end with development, it extends further beyond checking the features and functionality to ensure that your banking and financial application breathes life with flawless performance and integration. Right from testing the application acceptance by customers to identifying the defects and fixing them, testers monitor the entire software development lifecycle.

Testing allows you to protect your financial applications against potential failures and risks involved during its implementation. Software testing has a larger purview, as through APIs, one application interacts with another. As testing moves towards automation, it aims for higher accuracy and a leap towards digital transformation.

Improving Software Testing with AI

We are now progressing towards Software Testing powered by Artificial Intelligence with the growing need of achieving rapid and error-free results through automation testing. The entire foundation of AI-based software testing thrives on data, computing power and robust algorithms. In contrast to manual testing, AI-based automated testing enables the machines/system to execute the test codes automatically and respond better with minimal human intervention. AI empowers machines to learn and improve with very less human cognitive input. AI is a step ahead, which allows the software to test, diagnose, and heal itself.

Why AI is important in banking software testing?

  • Software testing requires developers to acquire possible combination of data, which could be a time-consuming and strenuous task. AI can smartly recognise the available data combination through automation based on repetitive patterns of data access.
  • Software testing requires more time, human resources, and investment. Artificial Intelligence can be a suitable option for developers who need to deploy the financial applications promptly, even with inadequate infrastructure.
  • Since testing is mostly checking the data repeatedly, which already exists in the banking software and has been running in close succession, AI can efficiently help in automating testing processes with minimal human effort, cost, and time.
  • The developed applications can recognise the issues and create unique and innovative test environments with the help of Artificial Intelligence. This leaves room for AI to automate the testing of repetitive tasks and leave operations to human creativity and reasoning ability.
  • The repetitive task not just requires extensive human effort and time but is also prone to errors and inconsistencies. AI-based automated testing will help in eliminating these testing irregularities.
  • Artificial Intelligence algorithms can be extremely helpful for testing banking software, ensuring its efficiency, and making it smarter for the end-user. AI algorithms imitate human actions and operate accordingly. Applying machine and deep learning algorithms can optimise the process with Artificial Intelligence.
  • Testers can detect bugs more efficiently in less time by using a smart algorithm making the application more reliable and accurate for users. Developers can use these outcomes to improve the product and learn through errors.

AI advantages in software testing

Artificial Intelligence-based testing provides solutions for problems that may surface during manual testing and are subject to frequent changes. AI testing saves time and money facilitating faster delivery to the market. With very less human intervention, software testing can be steadily conducted using artificial intelligence can be done steadily without much human intervention. Using artificial intelligence software automated testing tools yields high productivity. Testing software requires performing the same test steps repeatedly. AI-empowered testing tools enable you to execute these repeated testing more accurately and provide a detailed result and feedback every time the test is executed. AI-based testing improves the test scopes and software quality, enhancing the overall test coverage. As compared to human testers, AI bots can produce hundreds of test cases based on customer requirements.

Continuous Testing with AI

Previously, software was released annually, bi-annually, or quarterly; presently there are monthly or even more frequent releases. Developers and testers are now embracing Agile and DevOps method to accelerate the product launch process. To resolve errors and defects in software, which may arise because of quick market release, organisations are implementing continuous testing for uninterrupted performance to ensure user acceptance. It involves testing software early and often, ensuring that your customers enjoy an outstanding user experience. The gaps in testing applications at the complete phase of software development lifecycle, and later releasing it in the market can be bridged by continuous testing. But over time if these gaps widen then it will be necessary to take a step ahead.

With constantly reducing timeframes of software releases, continuous testing may not be enough to keep up the pace of faster delivery. We would need strong and intelligent additional support to be able to provide outstanding performance speeds and uninterrupted user experience. AI and Machine Learning are well-equipped to expedite the complicated phases of simultaneous software development and testing. Tasks that require human learning and reasoning abilities to automate will be made easier with AI techniques.

Concluding AI in Banking Software Testing

The rise of AI and full-stack frameworks can control increasing technical complexities and the rate of changes in software at its development phase. As the capabilities of AI are constantly evolving in software testing, we at Yethi, deliver accurate, extremely rapid, and high-efficiency testing capability with our 5th generation AI-driven codeless automation testing tool-Tenjin.

Its intuitive features can help you to reduce the regression testing load, repeated testing of the same set of tests, and launch your product within a strict timeframe. With a repository of 450K+ test cases, we can cover end-to-end testing of your applications, saving you time, money, and effort. With over 6 years in the industry, we have built our reputation by offering complete QA solutions and support to our 70+ BFSI clients across 17 countries.