Problem Statement:

As part of SDLC process:

  1. Is your product quality impacted due to a smaller number of QA resources available in the team?
  2. Are you waiting for QA resources to certify your code every time when you deploy? Is this impacting your product lead time (Speed to Market)?
  3. Is your Product delivery timelines are impacted due to last minute defects identified?
  4. Do you have your QA resources only in one location, but you want to “follow-the-sun” approach for Software delivery across multiple locations?
  5. Do you have manual testers who are not skilled in programming, but you want them to execute automated test scripts w/o any training efforts and automation setup?
  6. Would you like your team more agile and cross functional with Delivery?
  7. Would you like to increase your QA team’s productivity while they invest more time in script development rather than script execution?

If answer is ‘Yes’ for above questions, "Zero touch automation" is the solution for above challenges that we have been facing part of SDLC.

Solution: Zero touch automation with cutting-edge technologies

In this session, I will cover how we solved this problem using innovative solutions, Cutting-edge technologies like NLP (Natural language processing), AI & Cloud solutions.

You will learn how AI, NLP integrated with core automation components to achieve Zero touch automation.

This solution is not just revolutionary, it is paradigm shift in test automation to get results to your email with detailed analysis of failure categorization with recommended actions to users.

I will also cover how E2E automation will be driven with decisions taken by machines based on what user is looking for . There is no manual intervention in this process. NLP and AI play key role to help machines to take decisions.

We will also cover how we empowered developer/release manager/any team member/Manager to trigger the scripts from their cell phone and get the detailed execution report without having any automation software installed in their computer or Phone.

We will be demonstrating how the request will be initiated from User, understand the need from user using NLP & AI , Fetching the code from bitbucket to select appropriate automation scripts , running them on Selenoid/docker server , storing results to MongoDB , receiving email with test results and Failure analysis.

What is the value of zero touch automation?

  1. Enable speed to market: Now that Developers does not need to wait for QA resource, Changes can be certified quickly and ready to push to production. Lead time will be significantly reduced.
  2. Increase quality: Now that test automation is easy and it can run multiple times in each environment, most of the defects will be uncovered and addressed before code goes to production.
  3. Ease of test execution: Test execution will be very easy, no automation or framework setup required from user side. Test execution can be done 24*7.
  4. Productivity: Increase QA team’s Productivity to focus more on script development rather than focusing on script execution and failure analysis .
 
 

Outline/Structure of the Demonstration

  1. Questions to audience -2 mins
  2. What is Zero touch automation? 3 mins
  3. Introduction to NLP (Natural language processing) & AI (Artificial intelligence) - 5 mins
  4. Flow of end to end Test execution using NLP and AI -15 mins
  5. Demo -10 mins
  6. Value of Zero touch automation - 5 mins
  7. Q&A - 5 mins

Learning Outcome

1. Audience will learn to implement zero touch automation applying emerging technologies and innovative approaches .

2. Audience will learn how to apply NLP, AI to test automation life cycle.

3. Audience will understand how Zero touch automation can help reduce the Speed to market and increase the quality.

4. Audience will learn skills to integrate Selenoid/docker with NLP and AI Technologies .

Target Audience

Anyone who has SDLC knowledge and working part of development /QA team & Leadership team

Prerequisites for Attendees

Attendees should have knowledge and experience in SDLC process.

schedule Submitted 5 months ago

Public Feedback

comment Suggest improvements to the Speaker
  • Robin Gupta
    By Robin Gupta  ~  3 months ago
    reply Reply
    • As the speaker would be touching upon topics pertaining to NLP and AI, does the audience need to know any of the deep learning basics (CNN, RNNs etc..)? Also, does the 45 minute demonstration justify the content, in terms of QnA, Technical walkthrough and presentation. 
    • Srinivasu gangam
      By Srinivasu gangam  ~  3 months ago
      reply Reply

      Thank you Robin for your time in reviewing this proposal. Here are my answers to your questions. 

      1. Audience does not need to know deep learning concepts . As long as audience aware of SDLC process would be good enough. I will covering "introduction to NLP & AI"  for 5 mins as i mentioned in Outline/structure of this proposal. This will help audience to connect to further demonstration and follow through. 

      2.  Yes, 45 mins is good time to cover content and technical walkthrough followed by Demonstration and Q&A. I presented same topic  in my office couple of times within 45 mins almost similar to same outline/structure . 

      • Pooja Shah
        By Pooja Shah  ~  1 month ago
        reply Reply

        Hi Srinivasu, 

        Thanks for proposing this nice talk. Could you please help us with the 2nd query from Robin in the last message

        - Low level architecture in the draft slides or github repo for reference? 
        - And does the talk and demonstration planned shows "how can I go implement too", showcase of code snippets preferably?

        Every bit of information helps. Kindly please have a tab on https://confengine.com/selenium-conf-2020/timeline

        In general, an idea from experience: the demo if live, should also be having recording for making sure the internet or some other logistic issues do not hamper. 

        • Srinivasu gangam
          By Srinivasu gangam  ~  2 months ago
          reply Reply

          Hi Pooja, 

          Here are my inline answers for your questions. 

          - Low level architecture in the draft slides or github repo for reference? 

          Answer from Srini: I have slides ready with me on the low level architecture , I will check with my  organization's  legal/security team and  share this accordingly.  but here is what i can describe on high level . 

          1. Users of this framework will be instructing to perform certain tasks like what scenarios to be executed, in which environment, what application etc.. 
          2. NLP/AI component will use step1 information to process and determine which component need to be alerted and what action to be performed for user. 
          3. Action will be performed by Jenkins/MongoDB/JIRA component-based NLP/AI component instructions. 
          4. Results will be stored in MongoDB and email will be sent to User with required results.  

          Hope this information helps. Please let me know if you need any additional information. 

          Thank you for your suggestion to have recorded version of Demo as alternate option if any issues with logistics . I do agree with you and we did  learnt lesson and applied the same in our demos.  

           

          • Pooja Shah
            By Pooja Shah  ~  1 month ago
            reply Reply

            thank you

      • Robin Gupta
        By Robin Gupta  ~  3 months ago
        reply Reply

        Thanks for the response.

        Also, can you please highlight the exact usage of NLP in the Zero touch automation framework?

        And the low level architecture or github repo for reference?

        • Srinivasu gangam
          By Srinivasu gangam  ~  1 month ago
          reply Reply

          Hi Robin, here are my inline answers for your questions. 

          Also, can you please highlight the exact usage of NLP in the Zero touch automation framework?

          Answer from Srini : Users will be giving various instructions to automation framework to perform their daily automation needs including what application, what level of regression,  which environment etc.. in free text form (Natural English language). NLP will use these texts and determine what action that framework should be taken and which component of framework to take care of user needs. 

          And the low level architecture or github repo for reference?

          Answer from Srini: I have slides ready with me on the low level architecture , I will check with my  organization's  legal/security team and  share this accordingly. 

    • Raghu Tammina
      By Raghu Tammina  ~  3 months ago
      reply Reply

      Hi Robin,

      In  my opinion, considering most of the users in our using latest gadgets, they can easily connect with this topic. I did explored a bit in this area of what industry is doing using various chat and voice bot . Looks interesting and in future it can be scaled easily by adding more scenarios.

  • Mahesh Kodakandla
    By Mahesh Kodakandla  ~  3 months ago
    reply Reply

    I like these aspects of the submission, and they should be retained:

    Also topic seems to be interesting and provide a good value to the business.

    • ...

    I think the submission could be improved by:

    • ...
  • VENKAT VADLAMUDI
    By VENKAT VADLAMUDI  ~  4 months ago
    reply Reply

    Srini - this is an excellent proposal, with real benefits for any IT development and testing shop. Has the potential to speed up time to market with minimal human intervention. Good Luck !!

    • Srinivasu gangam
      By Srinivasu gangam  ~  4 months ago
      reply Reply

      Thank you Venkat for your feedback. 


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    Intermediate

    A key requirement for successful test automation is to get past the brittle or fragile nature of test scripts. Any Selenium (or Appium) developer has encountered the dreaded "NoSuchElement Exception". A locator that worked yesterday may fail today. What's a test engineer to do?

    Fortunately the field of AI provides promising solutions and allows for the creation of self-healing tests. Tests that can find elements across all environments. Tests that can learn from "human-in-the-loop" intervention and work perfectly thereafter. Imagine automated tests that "just work"!

    This session will look at how to apply the latest in AI and Machine Learning technologies to improve your test scripts. With the plethora of new open source AI libraries made available by companies such as Google, the ability to leverage AI in your applications is more accessible than ever.

    This session will be a primer on AI technologies and how they can be utilized for perfect test automation.

  • Liked Srinivasu gangam
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    Srinivasu gangam - Test case Generator with Optimized coverage - Orthogonal Array Testing Strategy (OATS)

    Srinivasu gangam
    Srinivasu gangam
    Sr Manager
    Cotiviti India
    schedule 4 months ago
    Sold Out!
    45 Mins
    Case Study
    Beginner
    1. Are you Confident about your test coverage?
    2. Do you have millions of permutations and combinations to be covered in testing?
    3. is automation the solution to cover million combinations?
    4. why can not my system decide what test cases to be executed to give complete test coverage?
    5. As part of CI/CD , instead of executing same test cases irrespective changes going in, would you like to execute more appropriate test cases ?

    I will be presenting quick demo on statistical approach and strategy which can help us to generate appropriate number of test cases automatically based on the impacted areas and business metrics . Let me share an example below.

    Let’s say we are testing any eCommerce application Flipcart or amazon. We will have to cover multiple combinations like different categories of items, different payment types, shipping types, Promotions, user types etc.. . I will use little bit of sets theory here.

    Let us take below 5 sets as an example. Assume that there is new payment type is getting introduced as “Paypal” as enhancement. If we need to make sure this new payment type is working with all products, all shipments types , all user types etc… we will have to cover all permutations and combinations which is nothing but Cartesian product of all these sets. The Cartesian product of below 5 sets is - 6*3*2*4*3 =432 test cases.

    Do we really need to execute 432 test cases just for one new payment type ? we just need to execute 24 test case to give confident test coverage .This can be done with OATS tool which is developed with intelligence with Business user Metrics + Orthogonal array testing approach ( OATS) approach . OATS tool will generate required number of test cases with simple input and one click .

    There are 2 key areas of input that we consider before we generate optimized tests.

    1. Business user metrics - Example : if you look at the below payment set , we would like to know what % of customers using each payment type in overall successful transactions. let us assume 60% Credit card payments , 20 % paytm and 20% rest of payment types . These metrics will help tool to give more weightage to Credit card test cases over other payment types. This make sense because we need to focus more on the areas our end users are using.

    2. Impacted areas: let us take an example that there is new payment type (AmazonPay) is getting introduced as en enhancement. We should give more weightage to payment set and make sure all existing payment types are tested with different combinations.

    Set1 - PAYMENT = { Cash, Credit card , Paytm , AmazonPay, Debit card}- # elements - 6

    Set2 – SHIPPING – {Shiptoday, Prime Shipping, ship Tomorrow}-# elements - 3

    Set3 – USER TYPE - { Guest User , Logged in user }-# elements - 2

    Set4 – PRODUCT TYPE – {Electronics, Groceries, Books , Stationary}- # elements - 4

    Set5 – PROMO TYPE – { Promo1 , Promo2 , Promo3}-# elements – 3

    I will be covering how this can be done in detail during presentation along with Tool Demo which was built in with an intelligence using sets theory . you will get an answer on why only 24 test cases are good enough instead of 432 test cases for the change new payment type got introduced.

    Advantages :

    1. Optimized coverage with less test cases

    2. Tester will be confident about test coverage

    3. This tool output can be integrated with Selenium key word driven framework . All this happens during run time w/o manual intervention.

    4. This strategy is good fit for automation testing .

    5. if any combinations are invalid to test, those combinations will be excluded while generating tests.

    6. There are tools in the market to provide statistics about untested code (Ex: JaCoCO ). These statistics can be used as input for OATS tool. We have not done this yet.

    Limitations:

    1. We have seen great value (reduced bug escape) applying this strategy to automated tests. However there is limitation in applying the same strategy to manual exploratory , Adhoc testing.

    2. We have not tried this strategy for performance testing yet.

    3. There are corner scenarios where human can only think will not be covered by this tool . These scenarios to be appended to generated test cases .

  • Liked Nishil Patel
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    Nishil Patel - Tesbo : An Awesome Test Automation Framework with Plain English Text But not BDD

    Nishil Patel
    Nishil Patel
    Founder
    QAble
    schedule 4 months ago
    Sold Out!
    45 Mins
    Demonstration
    Beginner

    Tesbo is a hybrid Test Framework built top on the Selenium which allows you to use the plain English language to define the test which helps you to reduce the development and maintenance time and efforts. sounds similar to the BDD framework (i.e. Cucumber, Specflow, Gauge, etc...) ??? But No It Isn't... It's much better than Cucumber.

    In this session, we will look into why we have developed Tesbo and how it will reduce the development and maintenance times of web and mobile test script.

    This session will focus on the

    • Introduction of Tesbo
    • Advantages of Tesbo
    • Feature description
    • Test Development and Execution demo
    • Future plans for Tesbo