Category: Business

18 Dec 2018

Basics of Testing in DevOps

In DevOps, the organization responds in a more agile manner to changing business requirements. In this concept, systems engineers, release engineers, DBAs, network engineers, and security professionals in the “Ops” branch seamlessly integrate with developers, QA, business analysts, and product engineers in the “Dev” branch into a single value IT entity.

There are four basic continuous processes in DevOps:

  • Continuous Integration
  • Continuous Delivery
  • Continuous Testing
  • Continuous Monitoring

In DevOps, testing is not at the end of the release cycle — it is now brought into the mainstream/beginning of development cycles. Developers and system engineers get the code in the right environment for Continuous Integration and Continuous Delivery and those stakeholders enable Continuous Testing and Continuous Monitoring processes in which QA engineers then validates that the team  has built the right application, by seeing and testing if it functions and performs as designed.

DevOps is not a methodology or a suite of tools but it is a concept to dismiss the barriers between Dev and Ops in order to meet the need for shorter and more frequent delivery timelines.

Agile and DevOps

Organizations have embraced Agile as a response to rapidly changing requirements and DevOps as a response to the demand for speed.

DevOps involves practices, rules, processes, and tools that help to integrate development and operation activities to reduce the time from development to operations. DevOps has become a widely accepted solution for organizations which are looking at ways to shorten the software lifecycles from development to delivery and operation.

The adoption of both Agile and DevOps helps the teams to develop and deliver quality software faster, which in turn is also known as “Quality of Speed”. This adoption has gained much interest over the past five years and continues to intensify in the coming years too.

09 Sep 2018

Can there be one solution for test automation of UI and middleware applications?

Having pre-built and pre-configured native connectors for most environments, for real time integration testing can be a high demanding functionality for any test automation framework. Built in functionality to monitor the server utilization charts in real time. Real-time performance monitoring through interactive charts and graphs. Finding the performance root cause quickly via innovative connectors at component level. To be build QA lab that can be intuitive to a functional tester and provide higher management with testing metrics is key to success.

Build automation and empower manual testing team and business users to automate complex workflow testing all Script-less. Build regression testing and automatic notifications using simple configuration interface is what the testing industry is demanding in today’s distributed highly changing application landscape.

On-Demand cloud-ready performance testing can make speed to market a reality. Scale and scale down with cloud VMs provides pay as you go option which can be economical and flexible to a company to run performance on-demand anytime unattended.

The only way to build quality into the system is to continuously test along with build and deploy in DevOps and Continuous Integration model.

09 Mar 2018

Test Environments and Data

The rapid growth of the Internet of Things (IoT) (see top IoT devices here) means more software systems are operating in numerous different environments. This places a challenge for the testing teams to ensure the right level of test coverage. Indeed, the lack of test environments and data is a top challenge when applying to test in agile projects.

We will see growth in offering and using cloud-based and containerized test environments. The application of AI/ML to generate test data and the growth of data projects are some solutions for the lack of test data.

21 Aug 2015

Artificial Intelligence for Testing

Far far away, behind the word mountains, far from the countries Vokalia and Consonantia, there live the blind texts. Separated they live in Bookmarksgrove right at the coast of the Semantics, a large language ocean. A small river named Duden flows by their place and supplies it with the necessary regelialia. It is a paradisematic country, in which roasted parts of sentences fly into your mouth.

The Big Oxmox advised her not to do so, because there were thousands of bad Commas, wild Question Marks and devious Semikoli, but the Little Blind Text didn’t listen. She packed her seven versalia, put her initial into the belt and made herself on the way.

Although applying the artificial intelligence and machine learning (AI/ML) approaches to address the challenges in software testing is not new in the software research community, the recent advancements in AI/ML with a large amount of data available pose new opportunities to apply AI/ML in testing.

However, the application of AI/ML in testing is still in the early stages. Organizations will find ways to optimize their testing practices in AI/ML.

AI/ML algorithms are developed to generate better test cases, test scripts, test data, and reports. Predictive models would help to make decisions about where, what, and when to test. Smart analytics and visualization support the teams to detect faults, to understand test coverage, areas of high risk, etc.

We hope to see more applications of AI/ML in addressing problems such as quality prediction, test case prioritization, fault classification and assignment in the upcoming years.

21 Aug 2015

Services Test Automation

Decoupling the client and server is a current trend in designing both Web and mobile applications.

API and services are reused in more than one application or component. These changes, in turn, require the teams to test API and services independent from the application using them.

When API and services are used across client applications and components, testing them is more effective and efficient than testing the client. The trend is that the need for API and services test automation continues to increase, possibly outpacing that of the functionality used by the end-users on user interfaces.

Having the right process, tool and solution for API automation test are more critical than ever. Therefore, it is worth your effort in learning the best API Testing Tools for your testing projects.