Reading:
Bridging Development Gaps with AI-Augmented Contract Testing

Bridging Development Gaps with AI-Augmented Contract Testing

Matt Fellows
Updated
Bridging Development Gaps with AI-Augmented Contract Testing

Hello and welcome to Part 3 of our PactFlow AI-Automation Blog Series.

In Part 1, we explored the challenges of contract testing and its limitations. Part 2 made the case for generative AI and examined current solutions like GitHub’s CoPilot.

Now, in this final installment, I'm excited to present our vision for the future of AI-augmented contract testing and to officially launch our open beta.

We left off discussing some of the challenges and limitations of existing AI solutions built by some of the largest and most well-funded companies on Earth. So, a logical question to ask is: why us?

Why Us?

Great question. To answer it, we need to first explain our perspective on AI—how we see it affecting our customers, the software industry, and how we plan to integrate it into PactFlow. While you can find a high-level overview on our AI page, let us dive a little deeper into our position.

Our Position on AI

At SmartBear, we see AI as transformative—not just for our customers, but for the software industry. Generative AI tools like ChatGPT and CoPilot have demonstrated the potential to dramatically enhance efficiency, accelerate learning, and offer valuable insights that were previously difficult to uncover.

But there is one core principle we hold onto: Our approach to AI is a human-centered one - it will augment and empower our developers, testers, and engineers, giving them the freedom and time to focus on the complex, creative, and rewarding tasks that deserve their ingenuity.

We expect the most innovative solutions to complex problems in software development intersect at the intelligent use of modern technologies, and the creativity and beauty of human craftsmanship.

As discussed in part 2, we believe in the benefits of test-driven development (TDD) and the strains it places on software design and quality. This can be in tension with some of the capabilities of AI to rapidly produce working software.

For example, no AI tool today can fully comprehend the complexities of a production incident at 3 a.m., much less communicate with stakeholders and customers. This is important because the quality (e.g., readability) of software being debugged at 3 a.m. matters.

Our AI should, therefore, also support human decision-making, not replace it.

Lastly, there is nothing more important than our customers' trust. We take this responsibility seriously when it comes to AI, including being proactive about AI ethics and embedding responsible practices in every phase of our product lifecycle.

What About PactFlow?

The future of large language models (LLMs) and AI innovation is clear: they will continue to get more powerful, faster, and cost-effective. But here’s where our unique expertise shines—these tools will still rely on foundational knowledge, whether it’s understanding HTTP clients like curl, working with specifications like OpenAPI, or using libraries like Pact.

PactFlow is at the epicenter of the contract testing industry. Our team has been shaping the contract testing ecosystem for years, and we’re continuing to guide its evolution. Our fingerprints are already visible in today's generation of AI platforms (as an example, I've noticed how OpenAI and Anthropic generally choose to use chai assertions and mocha when creating Pact JS tests, and this is unlikely to be a coincidence if you look at my GitHub activity).

So, we'll continue to bet on the future of Pact and contract testing - just as we've always done.

But this still doesn't answer why we should build an AI-based solution. The answer lies in what our customers want from us. Our customers simply want to make API integration testing as easy, reliable, cheap, and fun as it can be.

The simplest answer, then, is that AI is only a means to an end – that end being a delightful product experience.

Our product experience must encompass more than just creating or updating contract tests - it should make it easy to create better and more precise contract tests, to identify gaps in test coverage, to help debug failures, to use the latest APIs and libraries, to gain insight into the system, and much more.

PactFlow is the global leader in contract testing - who is better positioned to guide AI to contract testing nirvana?

Introducing PactFlow’s AI-Augmented Contract Testing 🚀

Today, I'm thrilled to announce the launch of our AI-augmented contract testing solution, now available in open beta.

Our latest test generation capability featuring HaloAI uses generative AI to help users quickly generate Pact tests. By leveraging data from source code, OpenAPI descriptions, or HTTP traffic captures, it dramatically reduces the time and effort involved in creating and maintaining contract tests.

For a demonstration, check out a walkthrough of the key features here:

Next Steps?

PactFlow’s AI-augmented contract testing is available across all plans during the beta phase starting today. If you’re ready to try it out, head over to our documentation to get started.

This is just the beginning – stay tuned as we continue to invest in this new direction.

Unpacking GenAI’s Role in Contract Testing
14 September 2024

Unpacking GenAI’s Role in Contract Testing

Part 2 – We examine how Generative AI could automate parts of contract testing, while acknowledging its current limitations. We discuss the technology’s potential and challenges, emphasizing the need for smarter automation solutions to effectively tackle API testing complexities.

5 min read

The Case for Contract Testing: Cutting Through API Integration Complexity
28 August 2024

The Case for Contract Testing: Cutting Through API Integration Complexity

Part 1 – We explore how contract testing can be applied to simplify the complexities of traditional API integration testing. We recognize common barriers, like the learning curve and test maintenance, and introduce the idea of leveraging Generative AI to address these challenges.

9 min read

arrow-up icon