Codeless Automation

Recently when we were hit by a query from a start-up firm looking for TAAS, we gratefully acknowledge them. But when they replied asking us – We do not follow Agile, would codeless automation fit our strategy? At that very moment, we thought of coming up with this post –

Codeless Automation

The Myth or Reality – Is Codeless Automation Dependent on Agile?

Not Really! Codeless Testing or Codeless Automation may be the buzzword in modern times, but it existed even a decade back. I remember working for one of the service firms almost 12 years back, where I used to work on a much simpler programming language of C++ [developed in-house], the same concepts of OOP were repackaged to create functions and libraries, which were easy in coding [more like plain English] and debugging.

Codeless Automation is on similar lines with plain English now being replaced by intuitive user interface[UI]. Input your test data, play and record the test steps and compare the actual and expected result in a visual form.

Talking about Agile, people need quick results, speedy solutions and shorter Time-to-market, hence Agile is the need of the hour. And when things like codeless, virtualization or microservices surface, individuals tend to believe they are tightly coupled with Agile. However, most of these frameworks are independent of the strategy used.

Let’s try to explore if the dependency exists between the two concepts?

Use Case – To Prove Codeless Automation is Independent of Agile Methodology

We would be using the Probability Theory in which the two events are independent if the occurrence of one does not affect the likelihood of the occurrence of the other.

Scenario – A bunch of new features are added to the existing product and need to be QA tested.
Pre-requisites For Codeless Automation, we at CloudQA follow these pre-requisites.
  1. HTML5 compliant web application with
    1. Finalized UI design or less frequently changing UI design
    2. Some features ready for functional testing
If Codeless Automation is dependent on a methodology, a change will not help us in achieving the desired results so, let’s assume that we changed the methodology to
Waterfall Model On following this approach, we can –
  1. Satisfy the prerequisites – YES
  2. Get test cases automated via codeless automation – YES
V-Model On following this approach, we can –
  1. Satisfy the prerequisites – YES
  2. Get test cases automated via codeless automation – YES
Agile Methodology On following this approach, we can –
  1. Satisfy the prerequisites – YES
  2. Get test cases automated via codeless automation – YES

Methodology or framework are mere concept to build the software, while some languages may be built for specific ideas, it does not give them a dependency factor. On similar lines, Codeless Automation and Agile are two concepts that could be adopted for better results and better quality, with the fact that they could still be executed independently.

References
#1 #2

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Test Data Management Tools

While availing Testing-as-a-service[TaaS], benefits like Cost Reduction and Revenue Optimization seemed obvious but did you double check if the package is inclusive of Test Data Management? With Big Data the buzzword these days, we often sideline the test data management, in fact, experts believe that an effective Test Data Management could increase the quality of the product.

CloudQA being the pioneers in offering Testing-as-a-service[TaaS] stress on why Test Data Management is an integral part of your Testing-as-a-service[TaaS].

Test Data Management Tools

Boost TaaS with Test Data Management[TDM]

Before moving on “How to prepare/manage your test data” let’s look at the challenges faced by a QA/tester in test data management.

The Challenges faced by a QA/tester in test data management

What Test data  is needed?

What is test data? For a numeric field fill in the value as 12345 and for a string ABCDE. Most of the test results do show such kind of screenshot where data was put in randomly. While testers argue that they were not performing data testing hence data could be random, experts believe each test case to mimic the real-life scenario. Simply, many testers are unclear on the experimental data to be used for a scenario in many cases.

Test Data Need Better Simulation, Masking, and Periodic Refresh

Put yourself in a financial trader/broker shoes, would he be able to make decisions based on simulated data? Or when the feed is delayed by 30 secs? That’s what happens for a tester/QA who tries to test a real-life scenario but fails may be because data is just the sample data or few weeks old or is given to you with a delay. Most of the testing teams would agree, that test data is close to real but NOT REAL!

Database Structuring, Relations, Keys, and linking is ambiguous to testers

A tester is well-aware of the full functionality, environment needs but very few know how and which tables get updated when hitting the submit button. What are the primary or unique keys in a table that could not be overridden? What’s linking of the data? Does submission of a record update multiple tables or just one? Ignorant on these issues, testers often override the data from backend to test a scenario or delete data leading in data getting corrupted.

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Best Practices for Test Data Management[TDM]

With “Known Problem Area” let’s look at the Best Practices to structure the test data in a systematic way that enhances productivity and boost the quality of the product.

Know Your Data

Know your data, whether it is a numeric field or alphanumeric in nature, which tables it gets stored. When it moves to the upstream system, does it change its name or nature? What are its limitations, what are the rules? Know all about your data.

Masking the Sensitive Data

While real data could be fun to test, it also comes with responsibility. Hence many corporates and enterprises to maintain compliance and regulations need to mask sensitive information. Just for example if your system gets the data with a delay of 30 secs, and a trader has placed a buy order of large quantity it would be wise to mask the orderid, stock and quantity to ensure confidentiality of the order.

No Data Manipulation

Avoid altering data from the backend to test a specific scenario. That may result in a specific test as pass but may corrupt the database with interlinking or relational tables.

Automate Comparison

Quick automation to compare the expected and actual results could be a faster way to point out inconsistencies and data anomalies.

Schedule a Periodic Refresh of Test Data

Make sure to establish a process and get a regular refresh of test data, which leads to enhanced testing efficiencies and streamlined testing process. Test Data management is integral to TaaS as with Test Data Management, increase testing speed by up to 25% and cut the cost to 5-10%. The perfect balance of Quality vs. Cost. Isn’t it?

References:
#1    #2    #3    #4    #5    #6

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Testing As A Service

As companies rush to meet the ever-evolving, customer focused, multi-interface, and technologically complex solutions, software quality and time to market becomes a critical need. One quickly realizes that software testing plays an important role in the growth of any company offering such solutions. However surging costs, high-security environments, and software sourcing variability has made the software testing function challenging.

Testing As A Service

In such an environment, it is important to assess and implement the right methodologies to achieve scale, minimize costs and offer improved services. Testing-as-a-Service (TaaS) is considered a viable testing model by many organizations to achieve reduced costs and improved service for their IT test requirements.

TaaS does this by outsourcing testing activities associated with some of a company’s business activities to a service provider rather than using their own employees/resources. By using a consumption-based pay model, there is less risk and investment on the part of the organization.

TaaS can be used for various QA activities, such as:

1. Functional testing
2. Load / Stress testing
3. Performance and Benchmark testing
4. Regression testing

Advantages of TaaS over traditional testing

1. Scalable model via public cloud – utilize computing power, disk space, memory as per current requirements but have the ability to ramp up on demand very quickly
2. Costs – Pay for what you use. No need to own your own infrastructure. No capital costs incurred.
3. Licensing benefits – Operating system (OS), test tools, hardware, application licenses are managed by the cloud.
4. Standardization – Centralized test environment with a standard set of tools and processes will ensure repeatability, efficiency and quality results

Besides self-service SaaS-based subscription model for automated testing, CloudQA also offers Testing as a Service for companies that do not have the bandwidth to carry on this essential step in their agile development process. Customers do not have to worry about any software licensing, infrastructure, expensive testing resource or steep learning curve for the testing tool & processes. Instead they can focus on developing their own software which is their area of competency.

Why CloudQA?

CloudQA has an established framework for delivering enterprise-ready testing and providing clients with the ability to take advantage of paying for what they need, when they need it, rather than investing in expensive tool sets and experts.

1. Center of Excellence – You will interact with a group of people that promote collaboration, employ software testing best practices with both tools and techniques
2. Process – We employ industry best practices and methodologies that will result in higher productivity and you will get more bang for your buck
3. Governance – We offer relationship management, QA Project management, and a centralized test environment, with standardized software library and test suites. We also provide a self-service portal which cuts downtime required to provision test environments.
4. Infrastructure – We own the automation software and even have an offshore facility for providing a cost-effective, highly scalable, and fast automated test solution

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