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RPA In Quality Engineering – All You Need To Know

RPA In Quality Engineering – All You Need To Know

All You Need to Know About RPA In Quality Engineering

Robotic Process Automation (RPA) and test automation can look quite similar from outside but when you start implementing both for test automation services, you will have a lot to compare, contrast and synergize on. RPA is leveraged to efficiently automate redundant and repetitive tasks that are rule-based and time-consuming. It is used to optimize the business process for more accuracy and efficiency.

Here are some of the common benefits of RPA:

  • Ability to automate tasks and use them 24/7
  • Bring on the efficiency of several human hands, hence increasing the productivity of an organization
  • Easily scale per requirements

RPA has become popular in a very short span of time due to its ability to efficiently interact with current test frameworks and fit seamlessly with existing workflows. However, RPA is not specifically a test automation tool and it cannot be implemented easily to automate any functionality or business process.

Here are some notable differences between RPA and test automation.

1. Working Layer

RPA: RPA is capable of mimicking user actions. It can easily make decisions to perform various actions after the learning phase of the robot is over.

Test Automation: Test automation works specifically on the data layer and is unable to mimic user actions. It can only execute the instructions given through a program.

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Also Read: Software Test Automation – Cornerstone of Improving Testing Efficiency

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2. Technical Skills

RPA: With RPA, test engineers are not required to have advanced programming skills. They are not burdened to remember language syntax. The automation workflow can be created easily as a flowchart diagram. You just need to put emphasis on the functionality under automation.

Test Automation: Test engineers are expected to have advanced programming skills to create automated test cases. However, the level of programming skills depends largely on the type of automation tool you are using. You are also required to remember syntax language. This is ofcourse changing with how sophisticated test frameworks are evolving to be but an automation engineer who has programming expertise will have an edge over others.

3. Domain Expertise

RPA: QA engineers leveraging RPA need to have in-depth domain knowledge as there is no separate professional working to define specific processes and scripting them as well.

Test Automation: Test engineers require extensive domain knowledge of the functionality to perform tests. In a normal scenario, manual testers define automation scenarios and test automation engineers write scripts for the test.

4. Complex Cases

RPA: With its capability to mimic human actions, RPA has a lesser dependency on the architecture of the entire system under test.

Test Automation: With programming language challenges and limitations, it is cumbersome to automate complex cases.

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Also Read: Top Five Tips To Effective Test Automation

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5. Design Time

RPA: Being process-driven, RPA requires lesser time to implement. You can easily define processes through its drag and drop feature as a flow chart.

Test Automation: It requires a moderate amount of time that includes a feasibility study and test design.

6. Scalability

RPA: QA engineers can leverage RPA for digital quality assurance to easily scale the test to any level. You get the flexibility to deploy thousands of virtual machines without any hassle.

Test Automation: Multiple programming techniques are leveraged to achieve desired scalability or parallel execution. You need to have physical machines that have the large processing power to conduct tests on a large scale.

7. Maintenance

RPA: Being on cloud, RPA is extremely simple and requires no maintenance. You can easily update any business workflow with the RPA.

Test Automation: Maintenance could become costlier due to changes in multiple scripts triggered by changes in a particular module.

With current capabilities, RPA is best used for enterprise applications and platforms. It is also a capable option to supplement functional workflows and test data management. Here are some other worth noting advantages of RPA:

  • Easy to learn and implement
  • Efficiently handles API, Backend, and Database flows
  • With a small learning curve, manual test engineers can also easily leverage the efficiency of RPA
  • Capable of handling majority of the application aspects including web, front end, application and mobile
  • Easily consumes and processes data from various source including ETL, XML, and PDFs to develop an advantageous workflow for efficient test management

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Also Read: Top 7 Software Testing Trends to Watch out in 2020

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However, RPA is not perfect for test automation services and comes with its own set of shortcomings. These include:

  • It is not a developer-friendly tool and hence, not fit for constantly evolving workflows and user interfaces
  • A developer is always needed to take make the test environment more complex
  • It is not capable of ensuring end-to-end execution of all the automated tests from the user perspective
  • Unit testing is not possible hence shift left is also not possible
  • Test engineers can’t use community editions for commercial purposes hence, need to pay expensive licensing fees for RPA tools
  • It takes time to build automated test cases through RPA tools
  • Bots come with expensive maintenance costs

With the above-mentioned shortcomings, RPA is not a foolproof solution for test automation. Developers desire below-mentioned capabilities in an RPA tool to reduce dependency on traditional test automation methods.

  • RPA tools need to:
    1. become more developer-friendly to build highly customizable workflows
    2. support behavior and acceptance-test driven
    3. enable QA professionals to trace tasks/test cases throughout the software development lifecycle (SDLC)
    4. allow running lean tests for virtualization, mocking, test data and environment control amongst others

RPA has emerged as an efficient tool for test automation, however, there are still several areas it needs to address to become a foolproof test automation services’ solution. At present, QA teams can leverage the mix of both RPA and traditional test automation to achieve optimum QA results. For instance, RPA can be leveraged for test automation data dependency for workflow and bots built for process automation can be reused for automation tests.

For more in-depth information about RPA in test automation, you can check out QA InfoTech’s webinar on RPA & Test Automation: Compare, Contrast & Gauge Effectiveness in Quality Engineering by Minesh Upadhyaya (Chief Operating Officer) and Ramandeep Singh (Associate Vice President – Test Automation and Research Lab).

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Established in 2003, with less than five testing experts, QA InfoTech has grown leaps and bounds with three QA Centers of Excellence globally; two of which are located in the hub of IT activity in India, Noida, and the other, our affiliate QA InfoTech Inc Michigan USA. In 2010 and 2011, QA InfoTech has been ranked in the top 100 places to work for in India.