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Everything You Need to Know About Test Automation as a Service (TAaaS)

Ankur Vishwakarma
6 minutes, 24 seconds read

The enterprise-level digitization and adoption of DevOps and Agile have made test automation a necessity in today’s time. It reduces the time-to-market and hence the production cost. One can execute test automation on web/mobile/desktop application, performance, and APIs at once; generating a comprehensive report based on functionality, time, and build.

Test Automation as a Service is an on-demand automation offering that overrules manual testing. But before, let’s look at key problems with manual testing-

  • It demands manual effort during release/enhancement.
  • Manual testing requires greater resources.
  • Testers usually avoid lengthy testing because of time and resource constraints.
  • It has a limited scope of tests and cannot accomplish in-depth testing. In other words, manual testing has lesser coverage. 
  • It requires testing the application on multiple computers, mobiles, tablets, etc. with different configurations.
  • The scripts are not reusable, i.e. every time testing will require new scripts for instances like the change in OS version.

How Automation Speeds-up Testing by 70%?

Testing automation not only reduces manual efforts but also speeds-up the entire testing process. Here’s how.

  • It cuts down the repetitive tasks/testing, which the test engineers used to do at the time of product release or enhancement.
  • TAaaS covers lengthy testing, which was unattended by manual testing.
  • It also increases the testing coverage with fewer resources.
  • It finds critical defects at an early stage of testing.
  • Its scripts are reusable. Testers need not code new scripts every time for system upgrades and OS version changes. Tests can recur without errors.

The following are the test automation tools categorized application-wise.

Web-based Application Automation

Selenium Webdriver is an open-source tool for automating web-based applications only. Users can test web applications using any web browser.

  • Types of OS for testing in Selenium: Windows, Mac, Linux
  • Browsers supported for testing: Mozilla Firefox, Internet Explorer, Google Chrome, Safari, Opera

Additional Resource: Selenium Testing Automation Framework

Mobile-based Application Automation

Appium is an open-source tool to test web applications running in mobile browsers. It also supports the automation of native and hybrid mobile applications developed for iOS and Android OS. Appium uses Selenium API to test the applications.

You can test a mobile application in just four steps-

  1. Write your test script on Eclipse.
  2. Connect your device to Computer (PC).
  3. Start Appium server.
  4. Run your script (test cases).

Appium supports Chrome browser for testing Android apps and Safari for iOS.

API Automation

Testing is difficult in Java as compared to dynamic languages like Ruby and Groovy. REST Assured is a Java library that provides a domain-specific language (DSL) for writing powerful, maintainable tests for RESTful APIs. Most of the web services are based on REST architecture. Everything is a resource in the RESTful web service. It is lightweight, scalable, and allows creating easy to maintain web apps. How it works-

  • REST Assured captures the (JSON) response of the API call.
  • It validates if the response status code is equal to 200.

Windows App Automation

Winium is a Selenium-based open-source automation framework for the Windows platform. You can test your Windows App following these steps-

  • Write your test script on Eclipse.
  • Start Winium Desktop Driver.
  • Set the path of application in the script.
  • Using “UISpy” inspect the elements.
  • Run your script (test cases).

Frameworks for Test Automation as a Service

A framework is a collection of reusable components that make the overall test execution and development easy and efficient. It is a custom tool designed by Framework Developers to simplify test automation processes.

A framework is a well-organized structure of components. For instance, one driver file executes an entire batch of commands without any manual intervention. The following are the types of frameworks along with the use scenarios specific to Test Automation as a Service protocol.

Data Driven Framework

This automation framework focuses on keeping test script logic and test data separate. For testing, it inputs data sets from a variety of sources like MS Excel Sheets, MS Access Tables, SQL Database, XML files, etc.

When the same test case needs to be executed multiple times with different data sets, the data-driven framework provides data to the test scripts.

Modular Driven Framework

Here, testers create test scripts for individual, small modules of the application. These small scripts (or test modules) can be combined into a master script to test specific scenarios or end-to-end testing. The test modules can also act as a library of functions to use in the future.

When applications contain a lot of modules, a modular framework is suitable for testing.

Keyword Driven Framework

This framework is also known as table-driven testing because it uses a table format to define keywords or action words for each function that the tester needs to execute. It’s a user-friendly framework. Test Engineers can develop test scripts even with limited knowledge of automation tools and programming language.

Behavior Driven Development Framework (Cucumber Framework)

It is a testing framework which supports Behavior Driven Development (BDD). It allows the tester to define application behavior in plain English and simple grammar as defined in Gherkin language. The following are the components of the cucumber framework.

Feature Files: It is an entry point to the cucumber tests. Here, the tester describes the test cases in a descriptive language like English. Feature files are important because they serve as an automation test script as well as live documents. A feature file can contain one or many scenarios. The following is a sample feature file.


#Keywords Summary:

#Feature: List of scenarios.

#Scenario: Business rule through list of steps with arguments.

#Given: Some precondition step

#When: Some key actions

#Then: To observe outcomes or validation

#And, But: To enumerate more Given, When, Then steps

#Scenario Outline: List of steps for data driven as an Examples and <placeholder>

#Examples: Container for s table

#Background: List of steps run before each of the scenarios

#””” (Doc Strings)

#| (Data Tables)

#@ (Tags/Labels): To group Scenarios

#<> (placeholder)


## (Comments)

#Sample Feature Definition Template


Feature: Title of your feature

I want to use this template for my feature file


  Scenario: Title of your scenario

Given I want to write a step with precondition

And some other precondition

When I complete action

    And some other action

And yet another action

Then I validate the outcomes

And check more outcomes


  Scenario Outline: Title of your scenario outline

Given I want to write a step with <name>

When I check for the <value> in step

Then I verify the <status> in step


   | name | value | status |

   | name1 | 5 | success |

   | name2 | 7 | Fail    |

Apart from these testers also use Linear Scripting Framework and Hybrid Testing Framework for Test Automation.

Step Definitions: A Step definition is a small piece of code with a set pattern. The pattern links the Step Definition to all the matching steps. Cucumber executes a Step according to Gherkin Steps.

Test Runner: The JUnit runner uses the JUnit Framework to run cucumber. It is an open-source unit testing framework for Java. It is useful for writing and running repeat/reusable test cases. It requires a single empty class with an annotation-


@CucumberOptions(features=”features”, glue = {“stepDefinitions”})

public class TestRunner {}

Also read – How to perform load testing on applications.

Best Practices for Creating an Effective Testing Framework

  • Integrate Appium and Selenium to cover mobile and web testing together.
  • Integrate REST Assured for API automation to ensure APIs are working as per set functionalities. It saves a great deal of time and resources.
  • Integrate Winium/AutoIt for testing standalone applications.
  • Integrate Cucumber for behaviour-driven development.
  • Use Page Object Model to create generic packages of common classes (codes) that can be used over all the test scripts. It helps to achieve reusability of codes.
  • Integrate JUnit to manage test cases and generate reports.
  • Integrate Maven or Jenkins to achieve continuous testing. Jenkins also helps to run the script for lengthy testing and generate extended reports delivered to all stakeholders. It is useful for tests that take hours to days to complete.

We specialize in business-specific test automation services. Drop us a word at to streamline and accelerate your product/solution launch.


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Chatbots are the assistants of the future and they are taking the Internet by storm. Ever since their first appearance in 1994, the goal was to create an AI that could conduct a real dialogue with their interlocutors. The purpose is to free up customer service agents’ time so they could focus on more delicate tasks- which require a more human approach.

If you are thinking about including a chatbot on your website, here are the things you need to keep in mind to boost customer engagement and deliver high-quality services.

Define your audience

First things first- think about who will be interacting with the chatbot? Who are your customers? How do they talk? How can you address them in a way they’ll enjoy? How can you help them?

For instance, if your company sells clothes that are mostly designed for young adults, using a less formal tone will be much more appealing to them.

Lisa Wright, a customer service specialist at Trust My Paper advice: “Customer service calls are usually recorded, so listening to a few of them can be a good place to start designing your chatbot’s lines of dialogue.”

Give your bot some character

People don’t like to talk to plain, simple robots. Therefore, giving your chatbot some personality is a must. Some brands prefer naming their chatbots and even design an animated character for them. This makes the interaction more real.

For example, The SmarterChild chatbot- designed back in 2000, was able to speak to around 2,50,000 humans every day with funny, sad, and sarcastic emotions.

However, the chatbot’s character needs to match your brand identity and at the same time- appeal to customers. Think about – how would the bot speak, if they were real? Are there some phrases or words they would never use? Do they tell jokes? All these need to be well-thought through, before going into the chatbot writing and design phase.

According to a report published by Ubisend in 2017, 69% of customers use the chatbot to get an instant answer. Only 15% of them would interact for fun. Thus, don’t sacrifice the performance for personality. 

Also read – 5 Key Success Metrics for Chatbots

Revise your goals before chatbot writing

Alexa- Amazon bot has 30+ skills which include scheduling an appointment, booking a cab, reading news, playing music, controlling a smartphone, and more. However, every business bot doesn’t need to be a pro in every assisting job.

Before entering the writing phase, think over once again – WHY you need a chatbot? Will it help customer service only? Or will it also help in website navigation, purchase, return, refund, etc.?

Usually, customers want one of the three things when they visit your site: an answer to something they’re looking for, make a purchase, or a solution to their problem. You can custom build your chatbot to tackle either one or all of these three situations. Many brands use chatbots to create tailored products for their clients.  

Cover all possible scenarios

When you start writing the dialogue, consider the fact that a conversation can go in many directions. To ensure that all the situations are covered- start with a flowchart of all possible questions and the answers you chatbot can give.

To further simplify your chatbot writing, take care of one scenario at a time and focus on keeping the conversation short and simple. If the customer is too specific or is not satisfied with the bot’s response, do not hesitate to redirect them to your customer service representatives.

For instance, Xiaocle is one of the most successful interactive chatbots launched by Microsoft in July 2014. Within three months of its launch, Xiaocle accomplished over 0.5 billion conversations. In fact, speakers couldn’t understand that they’re talking to a bot for 10 minutes.

Also read – Why should businesses consider chatbots?

This article is contributed to Mantra Labs by Dorian Martin. Dorian is an established blogger and content writer for business, career, education, marketing, academics, and more.


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The antiquated commodity of Financial ‘Coverage & Protection’ is getting a new make-over.  Conventional epigrams like ‘Insurance is sold and not bought’ are becoming passé. Customers are now more open than ever before to buying insurance as opposed to being sold by an agent.  The industry itself is witnessing an accelerated digitalization momentum on the backs of 4G, Augmented Reality, and Artificial Intelligence-based technologies like Machine Learning & NLP.

As new technologies and consumer habits keep evolving, so are insurance business models. The reality for many insurance carriers is that they still don’t understand their customers with great accuracy and detail, which is where intermediaries like agents and distributors still hold incredible market power.

On the other hand, distribution channels are turning hybrid, which is forcing carriers to be proficient in their entire channel mix. Customer expectations for 2020 will begin to reflect more simplicity and transparency in their mobility & speed of service delivery.

A recently published Gartner Hype Cycle highlights 29 new and emerging technologies that are bound for greater business impact, that will ultimately dissolve into the fabric of Insurance.

For 2020 and beyond, newer technologies are emerging along with older but more progressively maturing ones creating a wider stream of opportunities for businesses.


Irrespective of the technology application adopted by insurers — real, actionable insights is the name of the game. Without it, there can be no long term gains. Forrester research explains “Those that are truly insights-driven businesses will steal $1.2 trillion per annum from their less-informed peers by 2020”.

Based on the major trends identified in the Hype Cycle, 5 of the most near-term disruptive technologies and their use cases, are profiled below.

  1. Emotion AI
    Emotion Artificial Intelligence (AI) is purported to detect insurance fraud based on the audio analysis of the caller. This means that an AI system can decisively measure, understand, simulate and react to human emotions in a natural way.

    F0r Insurers, sentiment and tone analysis captured from chatbots fitted with emotional intelligence can reveal deeper insights into the buying propensity of an individual while also understanding the reasons influencing that decision.


Autonomous cars can also sensors, cameras or mics that relay information over the cloud that can be translated into insights concerning the emotional state of the driver, the driving experience of the other passengers, and even the safety level within the vehicle.

Gartner estimates that at least 10% of personal devices will have emotion AI capabilities, either on-device or via the cloud by 2022. Devices with emotion AI capacity is currently around 1%.

  1. Augmented Intelligence
    Augmented Intelligence is all about process intelligence. Widely touted as the ‘future of decision-making’, this technology involves a blend of data, analytics and AI working in parallel with human judgement. If Scripting is rules based automation, then ‘Augmenting’ is engagement and decision oriented.

    This manifests today for most insurance carriers as an automated back-office task, but over the next few years, this technology will be found in almost all internal and customer facing operations. Insurers can potentially offer personalised services based on the client’s individual capacity and exposure to risk — creating opportunities for cross/up-selling.

Source: Gartner Data Analytics Trends for 2019

For instance, Online Identity Verification is an example of a real-time application that not only enhances human’s decision making ability, but also requires human intervention in only highly critical cases. The Global value from Augmented AI Tools will touch $4 Trillion by 2022.

  1. AR Cloud
    The AR Cloud is simply put a real-time 3D map of an environment, overlayed onto the real World. Through this, experiences and information can be shared without being tied down to a specific location. Placing virtual content using real world coordinates with associated meta-data can be instantly shared and accessed from any device.

    For insurers, there is a wide range of opportunities to entice shopping customers on an AR-Cloud based platform by presenting personalized insurance products relevant to the items they are considering buying.

    The AR ecosystem will be a great way to explain insurance plans to customers, provide training and guidance for employees, assist in real-time damage estimation, improve the quality of ‘moment-of-truth’ engagements. This affords modern insurance products to co-exist seamlessly along the buying journey.

  2. Personification
    Personification is a technology that is wholly dependent on speech and interaction. Through this, people can anthropomorphize themselves and create avatars that can form complex relationships. The Virtual Reality-based concept will be the next way of communicating and forming new interactions.

    VR Applications such as  accident recreation, customer education and live risk assessment, can help insurers lower costs for its customers and personalise the experience.

    Brands have already begun working their way into this space, because as they see it — if younger generations are going to invariably use this technology for longer portions of their day for work, productivity, research, entertainment, even role-playing games, they will shop and buy this way too.

  3. Flying Autonomous Vehicles and Light Cargo Drones
    Although this technology is only a decade away from being commercially realized, the non-flying form is about to make its greatest impact since its original conception. Regulations are the biggest obstacle to the technology taking off, while its functionality continues to improve.

    The Transportation & Logistics ecosystem is on the brink of a complete shift, which will create a demand for a wide array of insurance related products and services that covers autonomous vehicles and cargo delivery using light drones.

While automation continues to bridge the gaps, InsurTechs and Insurance Carriers will need to embrace ahead of the curve and adopt newer strategies to drive sustainable growth.

Mantra Labs is an InsurTech100 company solving complex front & back-office processes for the Digital Insurer. To know more about our products & solutions, drop us a line at


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