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:
- 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...(more)
Software complexity is increasing exponentially. Yet even today, an uncomfortably large part of testing in the industry is carried out entirely manually: test design, test execution and management of test assets. Conformiq 360○ Test Automation is transforming the testing process with unprecedented state-of-the-art technology. With Conformiq next-generation testing solutions, test design and testing efforts are significantly reduced, while testing quality is increased...(more)
It should come as no surprise that the numbers of platforms and device types are more varied now than ever before. Customers continue to demand the latest devices, features and functionality, as well as increased mobility and accessibility. With the proliferation of mobile and portable device platforms and the Internet of Things, the workload of developers, and especially testers, has greatly increased. Naturally, there is a growing demand for more efficient and cost-effective testing across all platforms...(more)
The number of software applications, customer service portals, device types, and platforms has reached an all-time high. The need for reliable and efficient testing methods is more critical than ever before. Testing complexity and requirements are growing exponentially. Yet, many of today’s testing environments continue to use test design and
test execution methods, dating back 20 years or even more… (more)
How automatic is your automated test design process? There are three primary methods used in automated test design tools. They all deliver improvements in the test design process, but there are significant engine differences that you should fully understand prior to selecting your tools. In this paper we will compare and contrast these methods and discuss the limitations and benefits from each... (more)
Interest towards model-based testing (MBT) has increased quite significantly over the last few years as testing has started to reach the limits of traditional test design approaches. At the same time, industry experts in fields such as financial services, retail, insurance, banking, telecommunications, and web-based services have started to see and understand the benefits that applying MBT has to the quality assurance function and the continued relevance and success of their businesses.… (more)
Test design techniques are used to identify the test scenarios through which the test cases are created. Different testing goals will need to employ different test design algorithms. The more algorithms that are available to the test designer, the more effective and complete the testing can be... (more)
With today’s continually evolving digital business landscape, enterprises are increasingly turning to Agile approaches to speed up development and to address the growing consumer demands for innovation. Unfortunately, Agile is often unable to deliver on its promise of early, aggressive, and continuous testing, because many of the testing approaches being used today are insufficient to get the job done. In this paper, we will explore some of the popular alternatives to traditional manual testing, including those being used to improve the speed of functional test design…(more)
Bluetooth is an ubiquitous, open wireless technology standard for exchanging data over short distances. A standard originally created by Ericsson and now managed by the Bluetooth Special Interest Group, Bluetooth has become an indispensable part of the global digital communications fabric. Implementations of Bluetooth are hardware-based and subject to stringent quality requirements. Because of their nature, recalling… (more)
Conformiq Designer is a commercial tool for model driven testing. It derives tests automatically from behavioral system models. The derived tests are black-box tests by nature, which means that they depend on the model and the interfaces of the system under test, but not on the internal structure (e.g. the source code) of the implementation. This whitepaper explores the technical implementation of Conformiq Designer, historical and experimental… (more)
All MBT tools provide some measure of efficiency gain in the test design process. How much benefit, both for initial and recurring test design, is probably the key issue that should be understood when selecting a Model Based Testing tool. Unfortunately for those doing the selecting, the engine core doing the processing is the most difficult to really understand. It controls the robustness of the test design, user flexibility, and most of the test design efficiency but… (more)
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.
However, test design speed up is not the equivalent of improved test design productivity because there are other aspects necessary for overall improvement in the project’s testing process. Even in Agile programs, the focus must be on improving the overall project’s testing process, not just faster test design.
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.