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Archive for the ‘Automation’ Category

Important tip: How to raise bugs automatically

In Automation, Tools on August 5, 2017 at 8:03 am

Congratulations! you just automated a suite of end to end tests for your application.  You run these tests for every build, look at the reports and everyone is happy.  Really?

The report contains failed tests too.  You need to raise bugs for that.  What does that involve?

  1. A suitable title
  2. Steps involved to reproduce the bug
  3. Provide information on: OS, Architecture, Browser version, Application Version, CPU information, Memory usage, Disk Usage, CPU usage
  4. Expected Results, Actual results, Screenshots, Logs

Test processes can be inundating  and exasperating for many testers leading to loss of motivation in Testing.  This is a hidden risk.

The aftermath of automated test execution is one such process. However help is at hand when you use the AutomatedBugRaiser

 

 

 

 

 

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Are we headed towards Prediction Driven Development?

In Automation, Machine Learning, Prediction on December 2, 2016 at 12:49 pm

In a recent tweet about Sanity Testing,  I started thinking about certain Machine Learning tools in the market which seem to predict defects for various change requests submitted.

Now assuming that this defect prediction tool “actually works”,  it would become extremely useful to conduct an extended Sanity (in the least).  This would lead to major issues caused by the change requests to be resolved even before it gets to the hands of a tester, thereby saving money and time.  Changes keep happening up-to the last minute of a Product release, and this could well be another way to develop Software.

Quick Tip: Anomaly Detection to build trust with Customers

In Automation, Bills, Invoices, Machine Learning on November 21, 2016 at 4:05 pm

In a recent incident, one of my friends took his old vehicle for servicing.  Among other things, a small bulb was replaced and the bill for just that part was a whopping Rs 300/-.  The explanation given to him was that the bulb costs Rs.150/- and the labor was Rs. 150/-. Whereas the same would cost nearly half the price a few months ago. Courtesy a history of maintaining invoices, he was able to question the prices.

He was also at the receiving end for some of his other bills, when he saw some extra charges which were never charged in his earlier bills (which he had maintained).  It was later found out, that these were some “errors”.   I wonder how many people would really do all this.

For people who do not store so many bills/invoices and keep track of unusual deviations in them.  They could be ripped off.

Solution: In these days of digital records (including bills and invoices), a machine learning algorithm called Anomaly Detection could help.  A company could basically spot the outliers or anomalies and strive to eliminate them thereby building trust with their customers.  For the customers, they could benefit if certain flags are reported in their bills whenever a large variation in prices is seen in their invoices for many billing products.

Some bills, payslips etc, could contain breakups of various categories, and any missing category or additional categories can also be flagged.

All in all, a win win for both Customers and Businesses

 

Quick Tip: Machine Learning can help improve your Customer Service

In Automation, Customer Service, Machine Learning on November 1, 2016 at 5:51 am

In an email to the customer support team of  a well known electronics company, I had asked a simple question before placing an order.  The question was, if one of their products was compatible with a specific OS.  The response from their customer support took about 4 days.  In response to it, I asked them if there were any drivers available.  The response,  “We will let you know when it’s available” took 4 more days. I had already placed an order after looking at some online posts regarding it’s compatibility.  I believe such simple queries can be addressed in their “Automated Response System”.  A typical response could be a set of recommended links (using Machine Learning) which could suggest what customers are saying, or pointing to certain solutions that have been suggested on the net.  Of course they can absolve themselves of any guarantees, if they really do not have a clue (which I doubt).  Oh! and did I mention the product worked fine without any drivers?  Please feel free to leave a comment.

Are we headed towards Image driven Automation – using Sikuli ?

In Automation on March 6, 2014 at 5:11 pm

What do you do when your application has tons of UI issues?
Apart form the other issues, regressing on the UI issues can definitely be a pain, especially the clerical stuff that involves comparing 2 images (one from your app to the one in your UI design document). So why not use a tool that can be used exclusively on interfaces? The answer is a tool called Sikuli (www.sikuli.org). Although I have just started using it, I found this tool interesting because it can capture images of GUI elements of an application on your desktop, and gives you the option of locating other elements down to the exact pixel count as might be specified in your UI document.
Additionally you could also use it to test web applications by just using the link in a slide.  For beginners in automation this could be fun, if you want to customize your tests you may have to learn Python.  We have had Data driven automation, we have had Keyword Driven automation and we are probably on our way towards Image driven automation with Sikuli and moreover its free of cost.  There are lots of cool stuff you can do with Sikuli and it’s headed in the right direction.

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