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Tag: SmartBear

SmartBear Tightens Integration Between AI Coding and Testing Tools

SmartBear this week revealed it is narrowing the divide between coding and testing by integrating its platform with artificial intelligence (AI) coding tools.

Sheryl Koenigsberg, senior vice president of product marketing at SmartBear, said integrations with AI coding tools from Anthropic, Atlassian, GitHub, and Amazon Web Services (AWS) will make it simpler for application developers to test code without having to exit the tools they use to create code.

Specific capabilities added to the SmartBear portfolio include a SmartBear Model Context Protocol (MCP) server for GitHub and connectors to ReadyAPI and Swagger for developers using Claude Code from Anthropic.

The overall goal is to reduce the level of friction that application developers might encounter as the volume of code being generated using AI coding tools continues to exponentially increase, said Koenigsberg. In the absence of that testing, the amount of technical debt that software engineering teams are accruing will soon become unsustainable, she added.

Mitch Ashley, vice president and practice lead for software lifecycle engineering at the Futurum Group, said the integrations provided by SmartBear pull testing inside the integrated development environment (IDE) where AI assistants generate code. That approach makes it possible to validate code at the cadence that code is now being created, he added.

Verification that sits outside the agent loop will otherwise accumulate as verification debt, noted Ashley.

While software engineering teams have been trying to shift more responsibility for testing further left for years, the need for application developers to test code before checking it into a DevOps pipeline has become more pressing. It’s not likely that shifting more responsibility for testing further left is going to eliminate the need for dedicated testing teams, but it should substantially reduce the number of issues that conspire to slow down the pace of application development.

It’s not clear how many DevOps teams are revisiting testing in the AI era, but a recent Futurum Group survey finds well over a third of organizations (37%) have adopted AI-assisted testing. In the absence of that testing, many of the return on investment (ROI) benefits provided by AI are negated if too much of the code being created winds up being rejected before being included in a build.

The challenge is that application developers today lack the context needed to review the code created by AI coding tools. As such, the need for AI tools to surface issues in code has become crucial at a time when developers are being asked to read massive amounts of code they personally did not create. Much of that code, in addition to containing any number of vulnerabilities, also tends to be more verbose than the code that humans would create.

The thing that DevOps teams need to remember is that asking an AI coding tool to test its own code is essentially asking it to grade its own homework. Software engineers need to make sure the AI agent that reviews code is based on a different large language model (LLM).

Regardless of the approach to testing AI code, the one thing that is certain is that shipping code faster doesn’t result in better software being deployed without testing.

July 16, 2026
SmartBear Adds Computer Vision Capability to Testing Platform

SmartBear this week extended its ability to apply artificial intelligence to application testing with the addition of a computer vision capability that can be used to detect objects in applications.

Prashant Mohan, vice president of product at SmartBear, said the company’s TestComplete platform now combines computer vision and optical character recognition to help automate the testing of highly visual applications such as CAD/CAM applications that have 3D components.

Historically, those types of applications relied heavily on manual testing processes that created a bottleneck that slowed the rate at which more complex applications could be deployed, he added. Computer vision capabilities, in effect, now allow machines to visualize these applications in the same way that humans see them, noted Mohan.

As a result, the SmartBear platform is now able to test how an application is supposed to behave, rather than how its underlying code is supposed to function. That not only makes tests more resilient to subtle application changes, it also serves to make them easier to maintain because DevOps teams can automate regression tests to keep pace with application changes without having to revise code, said Mohan.

As the pace at which these applications are being constructed accelerates in the age of AI, the need to apply computer vision to test them is becoming that much more pressing, said Mohan. The challenge is providing that capability within the context of a platform that is already being used to test a wide range of other classes of applications, he added.

Mitch Ashley, vice president and practice lead for software lifecycle engineering at the Futurum Group, said as AI compresses how fast applications get built, regression suites anchored to code structure accumulate maintenance debt with every release. Perception-based verification narrows that gap, but the harder problem is folding it into a platform already testing many other application classes, he added.

A recent Futurum Group survey finds well over a third of organizations (37%) have adopted AI-assisted testing, a percentage that should steadily increase as various forms of AI are incorporated into automated testing platforms.

In the meantime, DevOps teams should revisit workflows because more untested code is finding its way into production environments than most DevOps teams would care to admit. As it becomes simpler to both create and run tests, there increasingly becomes fewer valid reasons for not running those tests. After all, one issue discovered in production can negate return on investment (ROI) that a DevOps team might have delivered using AI tools to write code faster.

Of course, not two DevOps teams have the exact same level of maturity. There are a few organizations that have dedicated teams that religiously test every line of code, while others assume individual developers have taken on that responsibility. While developers should test their code to some degree, there is always going to be a need for third-party validation. No developer is going to understand all the possible permutations of a potential vulnerability in their code. The issue, as always, is determining how best to strike the right balance.

June 4, 2026
SmartBear Extends Scope of API Lifecycle Management Ambitions

SmartBear today added capabilities to its platform for designing and managing application programming interfaces (APIs) that make it easier to both keep track of them and detect drift.

A revamped Swagger Catalog, in addition to providing a unified view of APIs, also makes it possible to govern them.

At the same time, SmartBear is adding Swagger Contract Testing with drift detection that verifies the API is behaving as specified in a contract.

Additionally, SmartBear later this quarter plans to revamp its API editor along with artificial intelligence (AI) tools for generating APIs, a context-aware ability to create documentation, Spectral-based governance enforcement, a Model Context Protocol (MCP) Server and expanded multi-protocol support, including OpenAPI 3.1. AsyncAPI 3.0, and GraphQL.

Laura Kennedy, director of product management for SmartBear, said both additions extend the API lifecycle management capabilities of the company’s platform.

For example, Swagger Catalog combines centralized visibility, automated governance and policy enforcement that spans API design to the runtime environment, noted Kennedy.

Swagger Contract Testing with drift detection continuously verifies that real API behavior matches OpenAPI contracts to ensure that business logic in the API hasn’t been modified, she added.

API lifecycle management issues are coming to a head now more than ever because AI agents are dependent on them to access data. The challenge is that not only are there more types of APIs than ever, but they are also being updated more regularly after being initially deployed. As a result, there is a much greater chance that an API is likely to have been misconfigured.

More challenging still, it is also more likely that as the pace of application development accelerates, it becomes more likely that a rogue API will have been deployed that no one in IT is aware exists. In the absence of any visibility, it’s also probable that the API is fundamentally insecure.

Finally, there are also zombie APIs that, after being created, are no longer being updated and maintained. Those APIs then become prime targets for cybercriminals looking to exploit any API weakness they can discover.

It’s not clear to what degree software engineering teams are proactively managing APIs. However, as the sheer number of API strewn across the enterprise only continues to increase, it’s only a matter of time before the issue is forced.

In the meantime, DevSecOps teams especially should be at the forefront of creating an inventory of APIs. While the bulk of APIs tend to be internally facing, it’s not uncommon for an API that no one ever thought would be exposed to the internet to have, for one unexplained reason or another, been made accessible.

Ideally, APIs should be just one more software artifact to be managed and secured within the context of a larger DevOps workflow. The challenge, as always, is finding a way to keep track of who created which API for what business purpose. Any API that exists without that level of credible explanation warrants immediate further investigation.

April 15, 2026
AI Is Forcing a Rethink of Software Testing and QA

SmartBear vice president of AI and architecture Fitz Nowlan explains why maintaining software integrity in the age of artificial intelligence requires organizations to double down on testing and quality assurance. He discusses how AI-driven development increases risk and why stronger QA practices are essential for reliable software delivery.

Nowlan argues that AI-driven development increases risk in a few ways. More code gets produced, more quickly, which means more surface area for defects and more opportunity for issues to slip into production. He also notes that relying on traditional, manually authored testing approaches can’t keep up with the churn created by AI-generated code. As a result, organizations need to “double down” on testing and quality assurance, and they need to modernize how QA is done.

A central theme of the conversation is the rise of AI-powered QA. Nowlan explains why the same wave of automation transforming software creation must also transform test management, test execution, and even test authoring. He points to functional specifications—requirements and definitions of correctness—as the source of truth that can guide both what gets built and what gets tested, especially as roles blend across development, QA, DevOps, and product management.

The discussion also tackles a common concern: can you use AI to test AI-written code without “letting the fox guard the henhouse”? Nowlan says the key isn’t necessarily a different model, but a different structure—separating the frameworks and prompts used for QA from those used for building features, and expanding validation beyond just code to include operational signals like latency and system behavior.

Finally, Nowlan looks ahead to “vibe coding” and citizen development, where prompts and specs matter as much as source code. His message: speed is great, but reliability still wins—and in an AI-driven world, stronger QA practices are the only way to maintain software integrity.

January 22, 2026
SmartBear Adds More Generative AI Testing Tools to Platform

SmartBear this week extended its efforts to bring generative artificial intelligence (AI) to its test automation portfolio to include test data and application programming interface (API) contracts.

This latest addition to the SmartBear HaloAI family of generative AI tools automates a set of manual tasks as part of a larger effort to reduce the labor required to test applications, by leveraging foundational large language models originally developed by Open AI.

Dan Faulkner, chief product officer at SmartBear, said the company has been working toward mastering techniques such as retrieval-augmented generation (RAG) to enable developers to use natural language to automatically create valid tests based on data collected via its platform. The goal is to increase the level of determinism that can be applied to testing using a generative AI platform that, by definition, provides a probabilistic approach to generating content and now synthetic data for testing, he noted.

SmartBear earlier this year acquired Reflect, a provider of a no-code testing platform for web applications that leverages generative AI, to jumpstart its efforts.

The AI Test Data Generation for the company’s TestComplete platform will be available in beta next month. AI-augmented contract testing for its PactFlow platform will be beta-tested from July through August. SmartBear last month added an AI tool for generating API tests that eliminates the need for developers to write and debug scripts.

In general, the usage of natural language will make application testing more accessible to application stakeholders who wish to participate in the application testing process, noted Faulkner.

Generative AI should also make it simpler to strike the right balance between shifting some testing responsibilities further left toward developers when appropriate and running tests that would be better suited to being conducted by DevOps engineers, he added.

Ultimately, organizations should be able to shift responsibility to testing both further left and right to improve the overall quality of the applications they deploy, noted Faulkner.

It’s still early days so far as the adoption of generative AI is concerned. However, it won’t be long before these tools are pervasively employed to not only generate code but also automate DevOps workflows. The next major challenge will be orchestrating all the AI assistants optimized to perform specific tasks, such as testing APIs that will soon be embedded into those workflows.

In the meantime, DevOps teams will need to determine to what degree they can extend their existing workflows in ways that incorporate AI assistants versus opting to replace their existing platforms. Regardless of approach, DevOps engineers will soon find they have access to a range of AI assistants trained to automate specific tasks that they will need to asynchronously orchestrate at very stages of a pipeline to enable organizations to deploy more software faster.

The challenge is the amount of software an organization deploys within the next few years is likely to far exceed the software they might have deployed in the past decade. The less that software is tested before being deployed, however, the more likely it becomes DevOps engineers will find themselves spending more time than ever troubleshooting applications long after they have been initially deployed.

June 21, 2024
SmartBear Acquires Reflect to Gain Generative AI-Based Testing Tool

SmartBear this week revealed it has acquired Reflect, a provider of a no-code testing platform for web applications that leverages generative artificial intelligence to create and execute tests.

Madhup Mishra, senior vice president of product marketing at SmartBear, said the platform Reflect created will initially be incorporated into the company’s existing Test Hub platform before Reflect’s generative AI capabilities are added to other platforms.

Reflect provides access to a natural language interface to create tests using multiple large language models (LLMs) that it is designed to invoke. It can also understand the intent of a test to understand what elements to test regardless of whether, for example, a button has been moved from one part of a user interface to another, said Mishra. Test step definitions, once approved, can also be automatically executed using scripts generated by the platform.

SmartBear has no plans to build its own LLMs, said Mishra. Rather, the company is focusing its efforts on providing the tools and prompt engineering techniques needed to effectively operationalize them, he added.

Reflect is the tenth acquisition SmartBear has made as part of an effort to provide lightweight hubs to address testing, the building of application programming interfaces (APIs) and analysis of application performance and user experience. Last year, the company acquired Stoplight to gain API governance capabilities.

Rather than building a single integrated platform, the company is focused on providing access to lightweight hubs that are simpler to invoke, deploy and maintain, said Mishra. The overall goal is to meet IT teams where they are versus requiring them to adopt any entirely new monolithic platform that requires organizations to rip and replace every tool they already have in place, he said.

There is little doubt at this point that generative AI will have a profound impact on application testing in a way that should ultimately improve the quality of the applications. As the time required to create tests drops, more tests will be run. Today, it’s all too common for tests not to be conducted as thoroughly as they should be simply because either a developer lacked the expertise to create one or, with a delivery deadline looming, they simply ran out of time.

Naturally, the rise of generative AI will also change how testing processes are managed. It’s not clear how far left generative AI will push responsibility for testing applications, but as more tests are created and run, they will need to be integrated into DevOps workflows.

Of course, testing is only one element of a DevOps workflow that is about to be transformed by generative AI. DevOps teams should already be identifying manual tasks that can be automated using generative AI as part of an effort to further automate workflows that, despite commitments to automation, still require too much time to execute and manage. Once identified, DevOps teams can then get a head start on redefining roles and responsibilities as generative AI is increasingly operationalized across those workflows.

January 26, 2024
SmartBear to Acquire Stoplight to Advance API Governance

SmartBear announced today it plans to acquire Stoplight, a provider of tools for editing and governing application programming interfaces (APIs).

Sean Butler, vice president of product management for SmartBear, said the deal, once finalized, will add a set of complementary tools and open source software that extends the core API catalog platform that SmartBear provides to manage APIs. The open source software provided by Stoplight includes Prism, an HTTP mock server that emulates API behavior; Spectral, an API style guide enforcer and linter; and Elements, an API Documentation tool.

The governance capabilities are especially critical as organizations begin to deploy hundreds, even thousands, of APIs that are used to integrate the microservices that are at the core of modern cloud-native applications, noted Butler.

As those applications are deployed, the management of APIs is naturally becoming more challenging. Organizations, for example, might have a different set of rules for APIs that are externally facing than they do for internal APIs. However, it’s not uncommon for internal APIs to be made externally facing without updating them when a new use case is discovered.

SmartBear is advocating a “design first” approach to the building of APIs that ultimately serves to make them simpler to manage, said Butler. In fact, good governance provides the foundation upon which API security can be achieved and maintained at a time when the number of cyberattacks seeking to exfiltrate data via API endpoints is starting to increase, noted Butler.

Unfortunately, too many developers are still prone to building and deploying rogue APIs, many of which turn into zombie APIs that developers forget to remove long after the function they were designed to enable is no longer required.

It’s not clear how many organizations are adopting a design-first approach to building APIs before they write application code, but as more APIs are deployed, the way IT is managed is rapidly changing. Application services are essentially becoming more disposable, so long as the APIs used to expose them to other applications remain stable. In fact, it’s now only a matter of time before most organizations fully appreciate the degree to which their entire IT strategy now revolves around their APIs.

The challenge is that it’s not always clear who within an IT organization is responsible for API management. Although an API is created by a developer, that developer eventually moves on to other projects. Therefore, responsibility for managing and updating APIs often winds up shifting to DevOps teams that were not part of the API development process.

One way or another, the management of APIs will need to improve once legislation that holds organizations more accountable for how data is managed becomes law. The issue that many organizations will soon discover as they move to address those requirements is: A general lack of visibility into both the number of APIs they have and, just as importantly, how they are being employed.

Hopefully, advances in artificial intelligence (AI) will one day soon make it simpler to manage APIs. In the meantime, however, a modicum of governance applied today should go a long way to preventing a problem that otherwise is all but inevitable.

August 22, 2023
SmartBear Acquires Pactflow Delivering First Key Milestone in Defining Next Generation API Development Platform 

Acquisition of Pactflow contract testing platform to ensure standardization and governance for APIs and microservices as SmartBear defines API dev lifecycle 

Somerville, MA, April 5, 2022 – SmartBear, a leading provider of software development and quality tools, announced today that it is entering into a definitive agreement with DiUS, an Australian technology consultancy, to acquire the leading global contract testing collaboration platform, Pactflow, advancing their next-generation API development platform.

The addition of Pactflow and its companion open source project, Pact, within the SmartBear API Developer Platform solves the complex challenges of testing microservices and API integrations that companies face as they accelerate cloud-native application development and digital initiatives. This next-generation platform solution allows organizations to deliver the enhanced digital experience that their customers have come to expect.

“We are thrilled to add Pactflow and open source software, Pact, to the SmartBear API Development Platform, providing developers with a critical emerging capability to speed up API development and deliver high-quality services,” said Frank Roe, CEO of SmartBear. “As organizations move quickly to digitally transform, SmartBear, with the addition of Pactflow, will drive even greater value to our customers, ensuring we continue to meet organizations wherever they are in their software development and API journey.”

“We could not be more excited to join the SmartBear team,” said Matt Fellows, co-founder of Pactflow. “There is a great synergy with the multi-protocol approach SmartBear has taken with their API tools and Pactflow’s contract testing, especially where customers are driving for more integrity in their microservices architectures. This, coupled with our joint commitment to open source, positions SmartBear and Pactflow customers well for the future.”

“Organizations are asking for a platform that supports the complete API lifecycle in a seamless, multi-protocol developer experience,” said Dan Faulkner, Chief Product Officer at SmartBear. “The addition of Pactflow contract testing capabilities represents a key milestone in our vision to deliver that platform, all with a focus on reusability and accelerated time-to-market through the CI/CD pipeline.”

Thousands of teams use SmartBear API lifecycle solutions to manage and bring high-quality applications to market faster. The addition of Pactflow to the SmartBear API Developer Platform builds on the growing utilization of SwaggerHub, Swagger OSS, and ReadyAPI, providing developers with a common UX to design or discover existing APIs, standardize, virtualize, and test, regardless of protocol.

The next-generation platform will be closely tailored to developer workflows, adding efficiencies while simultaneously allowing greater standardization and governance. The offering will initially integrate the company’s existing API developer toolkit while rapidly extending capabilities to comprehensively support and enhance deliverables and handoffs across the API lifecycle.

For more information on SmartBear and its API Lifecycle Management solutions, visit: https://smartbear.com/blog/the-smartbear-api-platform/

About DiUS

DiUS is an Australian technology consultancy with leading capabilities in digital transformation and product development. Our 150+ people across Australia and New Zealand leverage specialist expertise in cloud, data, application development, experience design, Internet of Things, and Machine Learning. We develop innovative solutions for startups and enterprises to solve difficult problems, get new ideas to market or disrupt traditional business models and build our own startup businesses to solve problems in a really new way. Visit us at www.dius.com.au.

About SmartBear
At SmartBear, we focus on your one priority that never changes: quality. We know delivering quality software over and over is complicated. So our tools are built to streamline your DevOps processes while seamlessly working with the products you use – and will use. Whether it’s TestComplete, Swagger, Cucumber, ReadyAPI, Zephyr, Bugsnag, or one of our other tools, we span from test automation, API lifecycle, collaboration, performance testing, test management, app stability and error monitoring, and more. Whichever you need, they’re easy to try, easy to buy, and easy to integrate. We’re used by 16 million developers, testers, and operations engineers at 32,000+ organizations – including world-renowned innovators like Adobe, JetBlue, FedEx, and Microsoft. Wherever you’re going, we’ll help you get there. Learn more at smartbear.com, or follow us on LinkedIn, Twitter, or Facebook.

April 5, 2022
SmartBear Expands API Design Enabling Developers to Work in Popular Java IDE

SwaggerHub plug-in for IntelliJ IDEA extends leading API lifecycle development platform to backend Java developers.

Somerville, MA, June 15, 2021 — SmartBear, a leading provider of software development and quality tools, has released a new plug-in for SwaggerHub API design to support IntelliJ IDEA, the popular Java-based integrated developer environment (IDE). API developers familiar with IntelliJ IDEA now have ready access to the OpenAPI compliant SwaggerHub API design platform to create, organize, and document APIs. The new IntelliJ IDEA plug-in expands the growing list of options for API designers offered with SwaggerHub, including the Microsoft VS Code extension, the SwaggerHub Code Editor, SwaggerHub Visual Editor, and SwaggerHub CLI Tool.

“Our goal is to meet API developers where they work with familiar tools that make them more productive across the entire API development lifecycle,” said Brian Downey, Senior Vice President, API Lifecycle at SmartBear. “With IntelliJ IDEA, we have added support for an IDE which extends popularity to more than 4 million Java developers.”

IntelliJ IDEA, developed by JetBrains, is an IDE written in Java for developers largely focused on server-side development. It includes several features to maximize developer productivity, including intelligent coding assistance and ergonomic design. While IntelliJ IDEA is an IDE for Java, it also supports a large variety of other languages such as SQL, JPQL, HTML, and JavaScript, to name a few. JetBrains is a global software vendor specializing in the creation of intelligent, productivity-enhancing tools for software developers and teams.

“In many ways, we share a common vision with SmartBear to make it easy for developers to take care of quality during all the stages of development,” said Brian Noll, Vice President of Sales and Partnerships, JetBrains Americas. “We recognize the value SwaggerHub delivers for enabling developer collaboration and API standardization and welcome their participation in our IntelliJ marketplace.”

IntelliJ IDEA already embeds OpenAPI capabilities for developers who want to consume APIs into their applications. The SwaggerHub plug-in for IntelliJ IDEA targets API providers who are designing APIs and want to enable their developers with a collaboration platform to reinforce design consistency and quality.

The new IntelliJ plug-in for SwaggerHub API Design by SmartBear enables API designers to view and edit their APIs and Domains directly from within the development environment. Key features include:

View and Navigate definitions from your SwaggerHub Organizations

Edit and Save API definitions via IntelliJ IDEA to SwaggerHub

Create new APIs or Domains from scratch or using a template

Delete API definitions by version or the entire definition

Create new versions of your API definitions and set defaults

Auto mocking allows for quick API definition testing

Validate your APIs against the OpenAPI/Swagger specification

Privacy makes API version public/private to change visibility

To learn more about the new SwaggerHub plug-in for IntelliJ IDEA or download a copy, go to the JetBrains Marketplace.

For more information on SwaggerHub, visit: https://swagger.io/tools/swaggerhub/.

About SmartBear
At SmartBear, we focus on your one priority that never changes: quality. We know delivering quality software over and over is complicated. So our tools are built to streamline your process while seamlessly working with the products you use – and will use. Whether it’s TestComplete, Swagger, Cucumber, ReadyAPI, Zephyr, Bugsnag, or one of our other tools, we span from test automation, API lifecycle, collaboration, performance testing, test management, and more. Whichever you need, they’re easy to try, easy to buy, and easy to integrate. We’re used by 15 million developers, testers, and operations engineers at over 24,000 organizations – including world-renowned innovators like Adobe, JetBlue, FedEx, and Microsoft. Wherever you’re going, we’ll help you get there. Learn more at smartbear.com, or follow us on LinkedIn, Twitter, or Facebook.

June 15, 2021
SmartBear Adds Enterprise-grade Application Stability and Error Monitoring with Acquisition of Bugsnag

Bugsnag will join the SmartBear portfolio of quality tools including TestComplete, ReadyAPI, Zephyr, SwaggerHub, CrossBrowserTesting, and BitBar

SOMERVILLE, Mass. and SAN FRANCISCO — April 28, 2021 — SmartBear, a leading provider of software development and quality tools, today announced it has entered into a definitive agreement to acquire application stability management pioneer, Bugsnag.

Bugsnag’s best-in-class, full-stack stability and error monitoring technology is leveraged by industry leaders like Airbnb, Slack, Lyft, and more than 6,000 organizations that prioritize application stability and health in order to continuously deliver high quality software. The addition of Bugsnag further bolsters an award-winning SmartBear offering that supports quality-first initiatives across every aspect of software delivery.

“We are thrilled to add Bugsnag to our portfolio of market-leading solutions,” said Frank Roe, CEO of SmartBear. “SmartBear solutions cover the critical areas of design, development, test management and automation, and Bugsnag adds app stability in production environments to our full span of SDLC coverage. This addition amplifies our rapid growth we’ve seen over the past few years and solidifies the position of SmartBear as the first choice for millions of developers and software teams around the globe.”

“We’re incredibly excited for this new chapter for our company because with the backing of SmartBear we will be able to continue to address the soaring demand for stable, high quality applications,” said James Smith, co-founder and CEO of Bugsnag. “Bugsnag and SmartBear share a common mission to help software teams accelerate the delivery of high quality software, so this coming together is a no-brainer for us and our customers.”

“An accelerated shift to DevOps, among other existing digital transformation initiatives, has really taken off over the past year,” said Vineeta Puranik, SVP of Engineering at SmartBear. “Those shifts require testing to be performed earlier and by developers alongside testers. Bugsnag empowers development teams to make data-driven decisions around app quality, and the solution’s ease of use and seamless integrations make it a perfect fit for the SmartBear portfolio.”

The acquisition comes after record, double-digit growth for SmartBear last year as well as the company securing a significant investment from Vista Equity Partners in October. Vista is an investor alongside Francisco Partners, which acquired SmartBear in 2017.

The transaction is subject to customary closing conditions.

About Bugsnag

Bugsnag is a pioneer in application stability management. We make error monitoring actionable and help enterprises and small businesses stabilize, prioritize and fix bugs. As a full stack solution, we are recognized for our best-in-class support for mobile applications. Bugsnag empowers software development, client observability and release management teams to make data-driven decisions on when to build features versus fix bugs.

Organizations experience significant ROI due to faster innovation led by developer efficiencies and improved customer experiences. We process over 1 billion crash reports every day from applications worldwide and more than 6,000 industry leading brands including Airbnb, Slack, Pinterest, Lyft, Yelp and Pandora use Bugsnag as their daily dashboard. Based in San Francisco, Bugsnag is backed by GV (Google Ventures), Benchmark Capital and Matrix Partners. For more information, visit www.bugsnag.com.

About SmartBear
At SmartBear, we focus on your one priority that never changes: quality. We know delivering quality software over and over is complicated. So our tools are built to streamline your process while seamlessly working with the products you use – and will use. Whether it’s TestComplete, Swagger, Cucumber, ReadyAPI, Zephyr, or one of our other tools, we span from test automation, API design, collaboration, performance testing, test management, and more. Whichever you need, they’re easy to try, easy to buy, and easy to integrate. We’re used by 15 million developers, testers, and operations engineers at 24,000+ organizations – including world-renowned innovators like Adobe, JetBlue, FedEx, and Microsoft. Wherever you’re going, we’ll help you get there. Learn more at smartbear.com, or follow us on LinkedIn, Twitter, or Facebook.

All trademarks recognized.

April 28, 2021