testsigma
left-mobile-bg

Natural Language Processing (NLP) Based Test Automation

November 6, 2024
Shruti Sharma
right-mobile-bg
NLP based testing Testsigma
image

Start automating your tests 10X Faster in Simple English with Testsigma

Try for free

What is NLP?

Natural Language Processing (NLP) refers to a branch of Computer Science, or in more simple words, let us say it refers to a branch of Artificial Intelligence (AI).

It is a process with which computers are able to understand the text and the spoken words in the same way as human beings can.

NLP describes the process of making the interaction between human languages and computers possible.

This technology has been around for years and is now being used by several people on a daily basis. We all must have come across NLP in some way or the other in our daily lives.

Alexa, the Amazon voice service is an example of a solution based on NLP. Siri, the voice assistant by Apple and Google Assistant also use this technology.

Some other examples of NLP include:

  • Spell Check
  • Voice text messaging
  • Spam filters
  • Autocomplete

How is NLP Helping the World?

If we look around, natural language processing is present everywhere, either in the form of text or speech. There have been numerous studies to make our interactions with machines effortless.

Natural Language Processing(NLP) is when new tools/devices/software/machines are made to understand natural language and make it more friendly to interact with.

NLP is a branch of artificial intelligence that aims to make the interactions between machines and humans as much simple and close to natural language as possible.

When NLP is introduced to a system, you don’t need to learn a new set of rules to work with the system. In some systems, the input is in the form of natural language while in some, the output is readable. Making the natural language interaction with machines, software and systems possible reduces the overhead in learning multiple programming languages for interaction and precious time can be used to accomplish the task at hand efficiently.  

Current Practices in Test Automation Industry

Now, there are multiple tools in the test automation industry that are being used to automate test cases and workflows. There are a few tools that gained huge popularity at one time. Because the majority of people are trained in these tools and also because of lack of sufficient analysis and planning at the time of choosing the right tool for automation, adoption of new technology-based tools have been tough and people still continue to use these tools that have been in the market for a long time.

What is overlooked is the time that it takes to design these test cases and the compromises done with the ease of maintenance and understandability of the test cases for other stakeholders.

Most of the times, design and maintenance takes the majority of the time allotted for automation of test scenarios and there is an extra cost for maintenance of the test automation team and training on specific tools being implemented.

Test script development is a tedious process and updating and maintaining them for every change does not come easy. A lot of time is spent on the initial test script authoring.

Write automated tests in simple plain English for Web, Mobile, Desktop and APIs with Testsigma.

Try for free


It is important that we perform automation to keep pace with the increasing complexity of applications. A simple but effective approach to Automation Testing would be Scriptless Test Automation.

Though there are other approaches like the Record and Playback method to automation testing, NLP based testing is not only intuitively easy but reliable. 

NLP Based Test Automation

Scriptless Test Automation using NLP is like the icing on the cake because scripts are created in Natural language and still give the option to add more complex scenarios or adapt to new changes. 
With NLP, you can still write your own tests but without the complexities of traditional test automation.

Tools like Testsigma implement NLP in Test Automation in a way that complex automation can be done easily in plain natural language that can be understood by all. With a minimum or no amount of training, complex automated tests can be written with no coding involved.

The dynamic locator strategy is a powerful feature that makes sure that the tests do not break for any change in the application UI. The test cases can be run on a custom cloud with your preferred web, mobile devices.

Testsigma also has an AI(artificial intelligence) core which suggests fixes to affected test cases as a result of a change.

What does NLP with Smart Test Automation Look Like?

Using NLP in Smart Test Automation, the tests are carried out in natural understandable language. The use of NLP in test automation minimizes the test creation time. It is done in a format that is intuitively easy for anyone to quickly adapt and use.

There are several tools like TestSigma that use simple plain English to automate tests. The changing UI elements are maintained by AI.

NLP-based tests can accommodate changes anytime and can easily be edited(if required). NLP makes it easier to automate all of your test cases and tightly integrates them with your dynamic delivery pipeline while optimizing the user experience.

Why NLP for Smart Test Automation?

There are many benefits that can be gained by using NLP for Smart Test automation.

  • Low Learning Curve. Since the tests are written in natural language, it is not mandatory for a tester or anyone from the team to have programming knowledge in order to go through it.
  • Since the test cases are created in natural language which does not need to be learnt. The time spent on test creation is reduced.
  • And similarly, the test cases become easier to maintain as well.

When Not to Use NLP?

There are some disadvantages to the use of NLP in test automation:

NLP should not be used in scenarios where your project requirements are not fulfilled by all the functionalities the tool can offer via NLP. In such cases check if customization is allowed in other languages. Or go for another tool that lets you automate according to your project requirements

Tools that Use NLP for Smart Test Automation

Tools like Testsigma use NLP in Test Automation in a way that complex automation can be done easily in plain natural language that can be understood by all. With a minimum or no amount of training, complex automated tests can be written with no coding involved

In addition to plain natural language test creation, Testsigma also offers some additional features that make your test automation smart. These features include:

  • Possible Failure Detection – Affected Test Cases
  • Test Management Capabilities(Requirements, Test Suites, Test Case priorities etc)
  • Automatic Bug Reporting(JIRA)
  • Shared Object Repository
  • State Management

Another such example of a smart test automation tool is ‘uphorix’.

Features include: 

  • Low code automation
  • Intelligent scripting
  • Swift compatibility
  • Native Test Data generator

Advantages of Using NLP Based Test Automation Tools

  • Low Learning Curve

One of the major problems that NLP aims to solve is the high learning curve for most of the automation tools that need some programming language to be learnt to automate test cases. NLP supports the creation of test cases using Natural Language which means there is no specific set of rules that needs to be learnt or understood.

  • Easy to Read and Understand test cases
  • When test cases are created using Natural Language, they are not only but understandable for users at all levels. These include BAs, Manual Testers, QA Managers, stakeholders, etc. This means any member of the team can have a look at the test cases and review them if needed.

  • Easy to Maintain test cases
  • When the test cases are easy to read with just the need to set up some configurations in the background, re-iterating through them and introducing changes becomes easier too.

  • All Stakeholders can be involved during test case creation
  • As creating the test cases only needs the knowledge of natural language being used for eg. English, the test cases can be created by anyone in the team, this means manual testers who know the system better can be involved to write the test cases and also, anyone from the product or project management or the client-side can drop in to enhance the quality and coverage of the test cases.

    Disadvantages of Using NLP-Based Test Automation Tools

    • A new tool

    Not really a disadvantage but when a new tool is adopted for some major workflow in an organization it means there will be some time taken to evaluate what it offers, how it is different from the previous tools and then finally how to use it to best suit the organization. This involves a bit of an effort at the outset.

  • Existing automation infrastructure will need changing
  • For an NLP based Test Automation tool, the major disadvantage for a team that already has a full-fledged team working on a test automation solution is the cost of moving to a new tool may prove too much and at such times the decision to move to a new tool should only be taken when it is sure to  prove beneficial in the long run. Also, let us not forget the reluctance to abandon existing automated testing approaches and make a shift to a rather new approach to automation testing.

  • Special Automation Team can seem redundant
  • As is common practice, legacy automation testing tools need special skills for automation, it becomes essential to keep a dedicated team of automation testers. For NLP tools, automation testing can be performed by manual testers, BAs and stakeholders. The automation testing team may seem redundant to some but there are more important things to manage.

  • New Tools may not have a great online presence
  • When new tools are being researched on, one of the major reasons behind choosing them is their online presence. When adopting new tools for eg. the ones with NLP, this may prove to be a road-block, but the tool owners aim to provide full help and support via their support staff.

    Why Does the Test Automation Industry Need to Move to NLP?

    Tools like Testsigma use NLP for test case creation and have AI at its core and need special mention here because they aim to provide end to end solution for automation on the cloud reducing test automation worries to the minimum.

    NLP based automated tests can easily be edited(if need be) and makes it easier to automate all the test cases and tightly integrate them with the dynamic delivery pipeline while optimizing the user experience.

    With the simplicity of NLP based tests, flexible, easily understandable tests can be created which well suits Agile development and allows for iterative delivery of quality software!

    Check out how you can write reliable NLP based test scripts that make Test Automation effortless!

    Build and run tests 10x faster for web, mobile, desktop and APIs under Testsigma’s unified platform.

    Try for free

    Frequently Asked Questions

    Is NLP Part of Automation?

    Yes, NLP is part of the test automation tool. NLP-driven test automation tool makes it easy to write the test automation script using plain English used in day-to-day life. NLP-supported test automation tool required little or no knowledge of programming language.

    What is NLP Used For?

    NLP means natural language processing. It helps to communicate with computing devices and software in plain English. For example, if a test automation tool provides NLP’s, then you will be able to write the test cases in plain English used in day-to-day life instead of using the scripting language.

    What are the Four Applications of NLP?

    Four applications of the NLP are

    • Test automation- Used in the test automation tools to make the test script creation easy.
    • Email filter- It is used in email management software to categorize and filter emails automatically. 
    • Predictive text- Whenever you get the suggestion of text or a whole sentence, NLP works behind the scenes. 
    • Language translation- It helps to make language translation more efficient and effective.

    Testsigma Author - Shruti Sharma

    Shruti Sharma

    Shruti is a writer and a content marketer with more than 10 years of experience in testing and test automation, and has been associated with Testsigma since about 3 years. She loves to read, learn, and write in detail about testing, test automation and tools. In addition, she also writes fiction. One cause she deeply cares about is mental health and psychology.

    image

    Start automating your tests 10X Faster in Simple English with Testsigma

    Try for free
    imageimage
    Subscribe to get all our latest blogs, updates delivered directly to your inbox.

    By submitting the form, you would be accepting the Privacy Policy.

    RELATED BLOGS


    Smart Test Automation using NLP: What you should know?
    MOHAMMAD ADIL
    NATURAL LANGUAGE PROCESSINGTEST AUTOMATION