White Papers

We’ve just released a new e-book that’s a practical guide to help you figure out if your team is ready to dive into the AI wave in software testing.

In this article, we’ll explore the advantages of automated testing and how it can improve test accuracy, debunking any myths that may be associated with it. So, let’s take a deep dive into the world of automated testing and discover how it can revolutionize your testing process.

The software testing market is ever growing with plethora of solutions on offer but the real questions remains: what is being tested and what is being automated in terms of the application. Enterprises are on constant look out for solutions which not only save effort and cost but also deliver optimized tests that can be automated. In this whitepaper, Conformiq and Qentinel highlight the right solution that will help with automating the thinking of the test case design and then automatically generating the test cases, test steps for direct automated test execution, ensuring E2E Test Automation.

There are multiple processes that have been and are being proposed for making functional test design faster than using traditional manual design techniques. It is primarily in conjunction with Agile development where these methods are getting the most attention. This paper is intended to provide more insight into these older developer test design methodologies, what they do and don’t deliver, and then to compare and contrast them with the newer Automated Test Design process as implemented by Conformiq.

Artificial Intelligence (AI) has become an important aspect of software testing today. With more and more focus on automation and Agile, adoption of newer technology will act as an advantage. AI and machine learning are typically centered on training software to understand input data versus output today (very similar to typing an input into a field and looking for an expected output). In this paper, we shall learn on how Conformiq is leveraging the technology and automatically generates test automation code and takes care of the impact of changes made to the reference model.

Test design is a separate task from test execution and is performed before executing the tests against the system. Conformiq powered e2e test automation platform remains one of the key differentiators to most of its partner’s traditional automation approaches. This exemplifies “Shrink IT spend and Grow Digital” strategies to its customers and helps them achieve speed with quality. Hexaware is focused on delivering similar benefits and value to its testing customers worldwide through deployment of the integrated e2e testing process described in this paper.

To most engineers the term MBT, for Model Based Testing, usually means using graphical models to be the basis for test generation. While this doesn’t hold true for all the different tools, for those that it does, the usability, capability, and benefits vary widely between them. Many tools model the test flows or even the test cases themselves by having the user think of the application flows. Let us take a detailed approach to understand the better tool with right homework and comparison because these tools are very different “under the hood”.

Experimental evidence and practical experience reveal that it is extremely difficult to create sufficient and proper test data for the design of test cases that comprehensively covers the software logic for any non-trivial software system. This becomes a major part of test design that takes significant effort, experience and skill to excel manually. Conformiq has changed the scenario! Data design can now be automated to dramatically improve test design efficiency and coverage.

Artificial Intelligence or AI is intelligence exhibited by a machine. The term AI is applied when a machine mimics a cognitive function such as learning and problem solving. AI is making all sorts of headlines lately and the recent innovation around AI has made it a hot topic especially in the media. The media focus has primarily been around Machine Learning (ML for short) and quite often the terms AI and ML are used interchangeably. However, AI research is actually much more than “just” Machine Learning and in fact the central problems in AI research include things such as:

• reasoning,
• planning,
• knowledge,
• learning and
• natural language processing

In this article we will, on a very abstract and high level, walk through the core of the Conformiq test generation technology and describe how the results of AI research have been applied with great success in the Conformiq automated test design software.

In the New Age, testing is not just about automating test design, or any other single part of the testing process. Instead, it’s about automating how the tests are derived and designed in the first place, as well as how tests are managed and executed. It’s about transparency, visibility and control. It’s about speed and turnaround time. It’s about seamless integration; bringing tools and processes together. It’s Conformiq 360○ Test Automation.