Software Testing Poker, Playwright Studio, FinTech AI Test Automation and more

What does poker have to do with software testing?

Have you seen the new open-source Playwright Studio framework?

How can you use AI to help with Fintech testing?

Find out in this edition of the Test Guild New Shows Newsletter for the week of Aug25. So, grab your favorite cup of coffee or tea, and let's do this.

Poker in Software Testing

A recent analysis compares three major approaches to requirements-based software testing: path coverage through models, pair-wise testing, and cause-effect graphing.

The study, conducted by Richard Bender of Bender RBT Inc., evaluates these methods based on criteria such as ambiguity elimination, logical consistency verification, and defect observability.

The research finds that cause-effect graphing emerges as the most effective and efficient method. This approach, adapted from hardware testing techniques, focuses on the observability of defects and produces a smaller set of tests with higher coverage compared to other methods.

Cause-effect graphing addresses key challenges in software testing, including poor requirements quality, the impossibility of exhaustive testing, and the need to propagate defects to observable points. The method also proves beneficial for agile development projects, supporting techniques like Acceptance Test Driven Development.

In contrast, path coverage and pair-wise testing methods show limitations in areas such as handling ambiguities, identifying implicit requirements, and ensuring defect observability.

?Key Takeaways

1. Consider adopting cause-effect graphing for more effective and efficient testing.
2. Focus on defect observability when designing test cases.
3. Use testing methods that can handle ambiguities and implicit requirements.
4. Ensure your testing approach is compatible with agile development practices.

Selenium grid

Selenium has announced the introduction of multi-architecture Docker images for Selenium Grid. The update enables wider compatibility and efficient testing processes across different hardware architectures, including ARM and x86.

Simplicity and accessibility are driving forces behind this enhancement. Teams using varying hardware architectures can now streamline their testing workflow without compatibility issues. By leveraging Docker's containerization, Selenium ensures that these diverse systems can maintain consistent testing environments.

Many testers are excited about this feature since it helps to make cross-platform testing more seamless than ever.

The update is expected to save companies both time and resources by simplifying the setup and execution of test environments.

Playwright Studio

Ashish Ghosh let me know that ING has officially open-sourced its in-house automated testing framework Playwright Studio INGenius, after four years of development. The framework, which integrates multiple open-source libraries, is designed to enhance business assurance testing, covering everything from browser and API testing to database and file validations.

By open-sourcing INGenius, ING aims to foster collaboration within the quality assurance community, driving innovation and empowering both engineers and business users globally. The company invites the community to contribute to and improve the framework, reflecting ING's commitment to quality, reliability, and collaborative development.

Built with the goal of bringing business users closer to engineers.

Kane AI

I had the opening welcome session at TestMu last week and found out there that LambdaTest, has introduced Kane, a new AI-powered feature designed to significantly enhance the efficiency and accuracy of software testing.

The introduction of Kane AI assistant aims to streamline the testing process by leveraging artificial intelligence to identify and resolve potential bugs and issues faster than traditional methods. This advancement promises to deliver more reliable results and enable developers and testers to maintain high standards of quality in their software products.

Kane utilizes machine learning algorithms to analyze historical testing data, predict potential problem areas, and suggest areas of improvement. By doing so, it reduces the amount of manual effort required by software testers and shortens the testing cycles. This integration of AI in software testing is expected to lead to faster release cycles and increased productivity within development teams.

Webinar of the Week

Speaking of AI you don’t want to miss the webinar I’m running all about AI Testing in Fintech & Beyond.

If you miss it you can register after the fact to watch the instant replay now.

Join us for a live demo where the AI capabilities in fintech testing will be showcased, demonstrating how AI can revolutionize the speed and effectiveness of software deployment in the fintech industry.

We covered:

• ?AI in Fintech Testing: The crucial role AI plays in improving the efficiency and accuracy of testing fintech software.
• Integrating AI in Development Cycles: Best practices for embedding AI within your fintech software development cycle to enhance operational efficiency.
• Transforming Business Impact: Insights into how AI-driven testing can elevate the ROI and competitive advantage of your fintech software releases.

Follow the Money Segment Opkey

I also found out that Opkey, a company specializing in AI-based ERP testing platforms, has secured $47 million in a Series C funding round. Opkey’s platform automates ERP testing processes to increase efficiency and reliability for its clients, which include several Fortune 500 companies.

CEO Punit Goyal highlights that the funding will be utilized to enhance the platform's capabilities, expand the engineering team, and accelerate global market reach.

Software testers should note that the rise in AI-based testing platforms such as Opkey signifies a growing trend towards automation in ERP testing. This trend offers the potential to significantly reduce manual testing efforts and enhance overall test accuracy. As a result, testers should consider upskilling in AI and automation tools to stay current with industry advancements.

Enhancing Quality in Product Management

In a recent blog post on LinkedIn, Millan Kaul emphasizes the critical role that quality assurance (QA) plays in the product development lifecycle. He points out that product failures can be drastically reduced by integrating comprehensive QA processes from the very beginning. By advocating for a collaborative approach, Millan underscores the benefits of involving QA teams early in the development process to catch potential issues before they escalate.

Millan outlines several strategies for improving overall product quality. This includes advocating for a culture of continuous quality improvement, adopting agile methodologies, and leveraging automation tools to streamline repetitive tasks. Additionally, he stresses the importance of fostering clear communication channels among product management, development, and QA teams to ensure alignment and shared understanding of quality goals.

Software testers should note the importance of early involvement in the product development cycle. By being proactive, they can help identify and resolve issues before they become costly problem. Testers are encouraged to work closely with development and product management teams to ensure their insights are factored into decision-making processes.

?Artillery 2.0.20 Release

In the latest update from Artillery, version 2.0.20 has been announced, bringing with it notable enhancements and fixes that aim to improve load testing workflows. The Artillery team has implemented performance improvements across the system, especially focusing on better support for AWS Lambda and HTTP requests.

This release introduces asynchronous HTTP request support for more efficient performance and resource usage. Additionally, various bug fixes have been addressed to enhance stability and reliability in load testing scenarios. Users will also notice updated documentation aimed at making the tool easier to use and more accessible to new users.

The key takeaway is the introduction of asynchronous HTTP request support, which significantly boosts load testing capabilities. By effectively handling concurrent requests, testers can expect more accurate simulations of real-world traffic and better performance insights.

DevOps AI-powered chatbot assistant

Kubiya, a startup in the DevOps domain with an AI-powered chatbot assistant, has successfully secured $6 million in seed funding. The fresh capital will help Kubiya launch its innovative AI platform broadly in the market.

The Kubiya platform aims to streamline DevOps operations by enabling engineers to interact with infrastructure and operations via a conversational assistant, thereby reducing manual tasks and enhancing productivity. This technology integrates with existing DevOps tools, allowing seamless communication and execution of operations.

The AI assistant, designed to simplify traditional DevOps workflows, can automate routine tasks, mitigating the need for substantial human intervention. This platform promises to lower the barrier for entry into the DevOps field, making it more accessible to smaller teams without extensive resources.

?To learn more also check out my podcast interview all about it from last year.

That's a Wrap

So that's it for this Test Guild News Show Newsletter edition.

Make sure to subscribe to never miss another episode.

I'm Joe Colantonio, and my mission is to help you succeed in creating end-to-end full-stack DevSecOps automation awesomeness.

As always, test everything and keep the good.

Cheers!

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