Automated Testing Buyer's Guide

Automated Testing A GUIDE FOR BUYERS

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April 2021

SD Times

Buyers Guide

Automated testing is a must in CI/CD pipelines

BY JAKUB LEWKOWICZ

A

s the software development industry has seen unprecedented levels of digital transformation, the demand for automated testing in the CI/CD pipeline has taken on greater urgency, especially at the early stages.

Also, new advancements in AI are helping developers with some of the biggest challenges in testing: test creation, maintenance and many of the manual tasks. Many companies have noticed, and are spending more on their automated testing initiatives.

Strong testing practices have gotten to be so important that they’ve become “the main differentiator between companies that are successful and those that aren’t,” according to Guy Arieli, the QA CTO at Digital.ai.

When companies are out looking for an automated testing solution, they’re primarily looking for one that will increase the quality of their releases,

increase the speed at which they can be done, and the one that’s most cost-efficient. A common approach among enterprise customers is to seek out a vendor that satisfies the majority of their needs while integrating into their CI/CD pipelines.

“We see customers want a unified solution. You don’t want to be using disparate tools for end-to -end testing of different types of clients,” said Dan Belcher, the co-founder of mabl.

“Increasingly they’re pushing us to add value to those end-to-end tests with insight around things like performance and visual correctness and other kinds of attributes of quality, because they’re trying to move from pure quality assurance like ‘did I break this core feature?’ to quality engineering: Is the feature better than it was before? Is it faster? Is it more accessible? Is it visually appealing?”

Chris Haggan, the product management lead at HCL OneTest, said it’s more than just getting the solution with

the most features. It’s also about supporting users with the tools that they already have and seeing if it’s a right fit with the overall approach the development organization is taking. Another issue is whether the organization has enough resources to deal with adding testing solutions to the mix since they can add complexity.

Where to start?

To start with their automated initiatives, organizations need to build quality into the application earlier, as quality has become a core functional necessity and testing early on is a key part of that.

“We see people all the time that want to fully automate everything in weeks.

Yes of course that is technically possible but it takes time to evaluate what’s important to test, how solutions fit into your CI/CD chain and who generates test data and so on,” according to Kevin Surace, the co-founder and CTO of Appvance. “While no one wants to hear continued on page 4 >

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it, the best automation strategy is one that is laid out over a year,” Surace added.

Building in quality comes down to both the culture of the organization and in executing deep code analysis, as well as deep reliability and security at the earliest stages. “If you put it at the end, you really can’t kind of accelerate your delivery. You’re always kind of running

into a bottleneck at the end of the process,” said Mark Lambert, the vice president of Strategic Initiatives at Parasoft.

This has led to continuous quality and continuous compliance as aspects that need to be tested in the CI/CD pipeline.

Mabl’s Belcher said that as more expansive automated testing becomes available, his one concern is that it will create a test sprawl in which it’s so easy to create end-to-end tests and get the coverage that you want in place that perhaps teams will become more complacent about testing.

“Just because it’s easy doesn’t mean it’s right,” Belcher said. “They have to put more thought into, you know, are these tests accomplishing the objectives that I set out? Are we doing only what is necessary? Are we thinking about the data? Do we have the right environments? And there’s a lot, a lot more than just the capability to add lots of requests. We keep score by the quality of what’s in production.”

Organizations also need to prioritize

those tests that need to be automated first to avoid getting overwhelmed.

“What I want to achieve is not more and more tests. What I actually want is as few tests as I possibly can because that will minimize the maintenance effort, and still get the kind of risk coverage that I’m looking for,” said Gartner senior director Joachim Herschmann, who is on the App Design and Development team.

In the past, what used to happen is that the organization used to say “we’ll recruit the developer and we’ll do the R&D and then when we need to test it, we’ll send it to India and then it will be tested there,” but now organizations realize that this has to be at the core of your R&D organization, Digital.ai’s Arieli explained.

Now as developers are starting to get more and more involved in quality, the notion of building quality as part of the application started to take hold.

“So developers have to think about how do I engender unit testing and more and more of it and when you reach the total extreme of it and you’re totally mature, they start thinking of automation,” said Anand Sundaram, the SVP of Products, UI, Device Cloud and Performance Testing at SmartBear Software.

Security and performance testing After quality, there are other aspects of the application for which automated testing can be leveraged: security and performance testing of your APIs and

microservices at the developer level before everything comes in for integration testing or the entire application comes together.

“We’ve accepted that test automation is valuable, deep code analysis is valuable and now we’re actually starting to say the same thing around security; how can we embed security in each stage so that we can build security into the pipeline,” Parasoft’s Lambert said.

Now, testers are trying to apply the same methods that they used for testing quality to security.

So that means deep code analysis to identify potential runtime exceptions that could go uncaught. As they’re moving up the stack, they’re looking to leverage unit testing for fuzzing of the underlying code and seeing how they can utilize API tests for API security testing. Developers can start to build quality and security by taking advantage of those earliest-stage validation techniques, Lambert explained.

While automated testing has received widespread recognition as a must for today’s software development environments, there are many challenges that organizations face when trying to set up effective testing strategies in their CI/CD pipelines.

At the bottom of the testing pyramid, the struggle with unit testing is that there isn’t a lot of visibility and it’s difficult to understand how much it actually covers. On top of that is the service component testing usually driven by an API. At the top of the pyramid is system and UI testing, which can be the most challenging.

Implementing all of these levels of testing can be a challenge, especially for legacy systems, since these aspects of testing were not initially accounted for when the applications were created, Digital.ai’s Arieli added.

Another challenge in implementing automated testing is finding the staff with the appropriate skill set. Testing complex enterprise applications requires business domain expertise.

Also, maintaining test scripts makes it difficult to achieve continuous test automation — as automation requires continued on page 7 >

Digital.ai Continuous Testing for mobile & web applications Digital.ai Continuous Testing (formerly Experitest) enables enterprises to increase release velocity while providing their customers with satisfying, error-free experiences across all devices and browsers. Digital.ai Continuous Testing seamlessly integrates with best-in-class tools throughout the DevOps pipeline and allows organizations to scale testing coverage without compromising web or mobile app quality.

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teams to ensure that testing doesn’t become a bottleneck. Therefore, tests must be designed in a way that minimizes disruption to the continuous testing process. The goal is for test automation teams to build robust and reusable test scripts that don’t require constant attention and maintenance, according to Clinton Sprauve, the director of Product Marketing at Tricentis.

Organizations also need to find a way to manage and track test automation efforts across multiple tools through observability and analytics.

“There is a challenge to testing in the sense that we need to do it more frequently, we need to do it for more complex applications, and we need to do it at a higher scale. This is not feasible without automation, so test automation is a must,” Gartner’s Herschmann said.

AI and observability in automated testing With value being a core tenet of DevOps, managers have to be able to see how each decision impacts the user experience, the revenue and entire business performance as a whole. This is why testing providers are looking to create more intelligent means of testing that can provide analytics.

Intelligent testing can be a combination of data analytics, smart heuristics and algorithms, machine learning and anything that analyzes data in real time and makes decisions or recommendations that then help solve the problem.

Developers can then use that need to have instant feedback of where exactly the problem occurred and move much more quickly.

Observability is needed in the pipeline because it gives testers a clue as to where exactly the problem is, when the problem occurred and then alerts the tester. In addition to observability, automated testing solutions have also created ways to help developers with many of the pain points around testing and to speed up the process.

“At the beginning of Agile, when you start talking about quarterly releases, you could still kind of fake it, right? You could still handle quality. You would have minimal amount of time to do all

of your regression testing and so forth, but you could build that into a schedule and make it work. When you move to CI/CD where change is continuous and disruptive you need to find new solutions,” mabl’s Belcher said. “And so for a few years, as an industry, we turned to, well, let’s just make us another thing that the developers have to worry about and have them write tests that do endto-end validation. But the problem with

that is that those tests relied on stability of the very thing that was changing constantly.”

“Now we realize well, maybe actually you don’t need these scripts and you can use the power of cloud computing and data analysis and machine learning and AI to make it so that it’s really simple to create the tests and then rely on the system to adapt to the change automatically rather than people needing to go in and update scripts every time you make a small change,” Belcher added.

The infusion of AI into these automated testing solutions has helped around aspects such as checking on quality, test maintenance and figuring out how to create the tests.

When you go from version one to version two, AI can help by having a system update itself and carry on without involving the developers having to go in and fix a load of things.

Also, machine learning becomes particularly important around performance testing and performance test result analysis to extract information from huge amounts of data and then help the users understand where there’s a performance problem and how to correlate that to some of the metrics that one gets from observability tools for example, HCL’s Haggan explained.

And the infusion of AI won’t mean

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that QA and dev teams get replaced, but rather their work will be augmented to work in tandem with more advanced tooling. AI can also relieve them of the majority of script writing and maintenance as a machine literally creates thousands of tests in minutes.

“But the impact is profound. I’d say in virtually every case over years now, AI tests found critical bugs that the standard manual or automated tests would have never found,” Surace said.

Another big trend in the automated testing space is around low code and codeless capabilities so that domain experts can build their desktop automation and know what goals they are trying to achieve with them.

Automation solutions before were very developer-centric, but vendors now are seeking to democratize capabilities to others in an organization and also to companies that don’t have the personnel or resources to do the largescale shift left methodologies that were invented in organization like a Google, Facebook, Amazon where there are unlimited resources, according to Digital.ai’s Arieli.

Next: API and mobile testing Parasoft’s Lambert said there is increased interest in testing in the API layer for a few reasons.

One is that API tests are quicker to run, and setting them up to be continuous tests at the API level rather than the UI level is easier and there’s less maintenance associated with it. API tests can be run more efficient because you don’t have to have all the browsers and you can execute in parallel.

Another reason is that they’re easier to debug and diagnose because they’re closer to the code.

Also, it’s easier for developers to reexecute those tests within their environment and it becomes a great communication mechanism between the test role and the developer role.

This new adoption for end-to-end testing is in the API space both for companies that offer APIs as products or for companies that have integrated API-based services into their applicacontinued on page 13 >

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How does your company help customers with their automated testing initiatives?

Kevin Surace, CEO and co-founder of Appvance Appvance makes a platform called Appvance IQ, or AIQ for short. The platform is all-encompassing — web, API and native mobile, functional, compatibility, performance, load, security tests.

It becomes a centerpiece of your quality initiative.

We break test creation into two buckets.

• Low code/no code ML-driven Test Designer • AI-based Autonomous Testing TEST DESIGNER – In Test Designer, you have a world class rapid script creator. It creates scripts at UX and API levels for every user flow. And, its compatible with every major UI library like React and Angular. We see people create base-level scripts their first day 20X faster than writing in Selenium. Test Designer alone garners 300% productivity improvement across the QA effort (dev or QA engineers).

AUTONOMOUS TESTING – AI-based Autonomous Testing is 4 years old and augments specific use cases. You simply train an AI engine to act in certain ways with your web or mobile apps.

Once it has learned what is important to you, it builds a baseline of your application and then on each new build it will look for bugs, differences, issues, failed validations. It is data driven, or it creates its own data, generating thousands of tests by itself in minutes. In addition, it’s able to simulate the flows of real user activities. Everyone who is using this says it’s a game changer for quality. Find up to 10X more bugs with 98% less effort.

Guy Arieli, QA CTO, Digital.ai Digital.ai Continuous Testing (formerly Experitest) enables organizations to increase release velocity while providing their customers with satisfying, error-free experiences across all devices and browsers.

With Digital.ai Continuous Testing, users can test their mobile apps remotely from their browsers across 2,000+ real iOS and Android devices, emulators, and simulators hosted in Digital.ai’s global data centers. Manual testing features full device control, and large-scale automated testing is easily created and run using these cloud-based devices.

Automated and live cross-browser testing capabilities are offered for testing web applications remotely with secure manual interactions. Perform large-scale parallel test execution across real desktop browsers of any type and version.

Digital.ai Continuous Testing also seamlessly integrates with best-in-class tools throughout the DevOps pipeline. The hassles around managing resources like Appium, Selenium, XCUI, Espresso, and Cyprus are removed, and your QA and testing teams can work comfortably and efficiently using the tools they are already most familiar with.

Once your web or mobile app is fully developed, Digital.ai’s Performance Monitoring tool helps you analyze performance by simulating different servers, measuring transaction duration, and speed index.

Digital.ai’s Accessibility Testing Cloud features real devices and browsers with full voice, talkback, and gesture support to help ensure that you deliver accessible web and application experiences for people with disabilities. Using the Appium integration, you can even automate your accessibility testing for faster compliance with all international web accessibility standards.

Finally, Digital.ai Test Analytics comes with a complete, consolidated view of the test execution results using advanced testing analytics with AI. Cloud managers can then use the customized dashboards to improve the test automation quality and ensure that scripts are stable.

Learn more about how Digital.ai helps make digital transformation deliver business value with automated testing and more at www.digital.ai

Chris Haggan, Product Management Lead, HCL OneTest HCL OneTest supports a DevOps testing approach with UI testing, API testing, performance testing, data fabrication, and service virtualization. The solution is designed to automate and run tests early and more frequently to discover errors faster.

HCL OneTest helps with the connections and dependencies between services and components to help plan integration test continued on page 10 >

Zephyr

TestComplete

ReadyAPI

CrossBrowserTesting + more

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< continued from page 8 strategies. With features like system modelling providing the overall visibility of the system under test architectures to help derive more comprehensive and cohesive tests.

Covering the complete test landscape, from mainframe to mobile, HCL OneTest also includes HCL OneTest Embedded for testing microcontrollers and validating standards conformance, e.g., MISRA-C. Recent additions to the HCL OneTest platform include cloudnative technologies that offer users a solution, which is both secure and offers discoverability of tests to enable simple re-use and collaboration. As an open platform, HCL OneTest enables users to bring existing open-source tests e.g. Postman, JMeter, into a single execution environment, retaining the investment in open-source tests, whilst adding value with HCL OneTest’s robust reporting and integrated script management.

As part of HCL Software DevOps, HCL OneTest supports a DevOps deployment life cycle through a wide range of integrations. With the increase in value stream management focus for many clients, being able to collaborate with all parts of the delivery life cycle through HCL Accelerate provides the complete transparency teams need.

Dan Belcher, Co-founder at mabl At mabl, we’re focused on solving an essential challenge: enabling software teams to innovate quickly while meeting high customer expectations for quality. In other words - to build useful things faster with fewer mistakes. Mabl is the simplest, most capable intelligent test automation solution on the market that’s designed to give software testers a centralized platform for endto-end testing Mabl’s low-code interface for test creation and maintenance requires up to 80% less effort than alternatives, improving collaboration and reducing the programming expertise required to write and maintain automated tests. Our auto-healing capabilities harness the power of AI and machine learning to automatically detect changes throughout the UI and update tests accordingly, significantly reducing the burden of test maintenance.

The mabl desktop app also enables users to run browser, API, and local web tests in the cloud or locally through a single unified experience. Rather than worry about recreating a clean testing environment in a new browser every time they start a new test, the mabl app automatically opens a fresh browser, reducing the risk of faulty tests and allowing testers to move faster.

Mabl offers integrations with Slack, Jira, and Postman that make it easy to integrate automated testing into existing workflows, including shift-left initiatives that bring developers into the testing strategy. Additional integrations with tools like Segment allow testers to align automated testing with actual user journeys, making it easier to connect testing success to business success.

Quality professionals are quickly taking on a new — and critical — role in the enterprise as the keepers of product quality. To do so,

they need solutions that enable them to automate routine tasks, embrace a data-driven testing strategy, and focus their talents on high-level quality initiatives. Mabl is the only endto-end test automation solution designed to meet that challenge.

Mark Lambert, Vice President of Strategic Initiatives at Parasoft According to a recent Forrester survey, quality continues to be a priority and the primary metric for measuring the success of software deliveries.

With the continued pressure to release software faster and with fewer defects, it’s not just about speed — it’s about delivering quality at speed.

Managers must ask themselves if they are confident in the quality of the applications being delivered by their teams. Continuous quality is a must for every organization to efficiently reduce the risk of costly operational outages and to accelerate time-to-market.

A critical element to reaching your quality targets is a scalable and maintainable automated testing strategy. When automated tests can be easily created and maintained, your team can focus on the overall quality of the application and verify the use cases, rather than the test scripts themselves. Parasoft solutions leverage artificial intelligence (AI) to enable rapid test creation, self-healing, smart test execution, and other capabilities that streamline your test automation workflows.

A leader in the "Forrester Wave: Continuous Functional Test Automation Suites 2020" report, Parasoft provides a complete and integrated quality suite. From deep code analysis for security and reliability, through unit, API, and UI test automation, to performance testing and service virtualization, which enable verification of nonfunctional business requirements, Parasoft helps you build quality into your software development process.

“Parasoft’s continuous testing shines in API testing, service virtualization and integration testing, and the combined automation context,” Forrester wrote in its Wave report. According to the report, if you are “looking for a genuine partner in testing, with strong and long-living roots in the testing space and complex technical systems to test, [you] should take a serious look at Parasoft.”

Learn how Parasoft helps increase confidence and accelerate delivery of reliable, secure, and compliant software. www.parasoft.com

Anand Sundaram, SVP Products, UI, Device Cloud and Performance Testing at SmartBear Software SmartBear’s mission for over 10 years, making us leaders in this space, has been to meet organizations where they are and help them achieve quality. We help primarily in three journeys, serving everyone from manual testers to developers.

First, we help those moving from manual testing to automacontinued on page 13 >

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tions and they then need to test the functionality of those APIs. Now, teams are getting quality engineering involved in work around API testing and validation for the first time, whereas historically, that’s been strictly left to the developers, mabl’s Belcher said.

There is also a lot of opportunity for API testing because, for example, server changes can be rapidly tested there, as well as microservices, Appvance’s Surace added. Highly data driven API tests will give teams tremendous information about a new server build in a few minutes.

However, there are challenges that come up with API testing including the biggest challenge of them all: creating a test scenario that’s realistic.

“So developers will deliver you a bunch of APIs and an OpenAPI doc.

That’s great. I know what each of the APIs are, but I don’t know how they are

used and I have to now figure out how to chain them together. I need to figure out the payloads. I need to figure out what the data value is.” Lambert said.

“With AI, we analyze how the tests are being operated, how the UI has changed, and then we can dynamically heal the tests at runtime, as well as optimize execution, and provide feedback to the development team quicker.”

As organizations move more towards an API-centric development model and microservices balloon the complexity of the ecosystem, service virtualization can help to map out the test environment and help with plugging in internal or external dependencies, which are otherwise constraints within a test environment.

Vendors have also recognized the increase in demand for mobile and that doesn’t just span phones but also smart TVs, tablets and also the growing embedded devices industry.

“People get very focused on user

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interfaces and performance testing and API testing, but actually there’s a whole other piece of this, which is IoT and how does that fit into the whole story as well and actually be able to test that code running on the device itself, which is what a lot of these customers have to have,” said Viktor Krantz, a senior product manager at HCL Software.

Highly regulated industries that are increasingly using embedded devices such as the medical, avionics, rail and automotive industries have special requirements that emphasize the importance of testing compliance.

The avionics industry for example requires that companies develop and test a device that will then last for 40 years. “If there’s any problem with that device 39 years later, it has to be done in the exact same version of the tool that you created 39 years ago, and test it with a tool from 39 years ago. And that’s literally a work lifetime,” Krantz said. “So it’s a crazy industry. z

Clinton Sprauve, Director of Product Marketing at Tricentis

< continued from page 10 tion. Next, our tools help organizations accelerate by scaling automation as they embrace Agile techniques with CI. Then, we help organizations as they shift left and shift right to release, manage, secure, and improve quickly in a DevOps/NoOps context. Our products cover the most critical aspects of quality across the product development life cycle.

Our suite of Zephyr test management solutions enables teams to deliver quality software, resulting in tighter collaboration, endto-end visibility, and faster releases. We have tools that enable you to easily create, manage, and execute automated API and UI tests.

The ReadyAPI platform accelerates functional, security, and load testing of web services right inside your CI/CD pipeline, ensuring end-to-end quality for all your web services. Manual testers to automation engineers can use code or codeless test creation with TestComplete to ensure quality across every desktop, web, and mobile application, including enterprise applications. CrossBrowserTesting and BitBar give testers instant access to thousands of browsers, devices, and configurations to achieve the quality consumers demand.

A common thread that binds our products is the injection of AI/ML to advance test coverage, authoring, maintenance, execution, and collaboration. Our tools easily integrate with each other and with the ecosystem vendors you’re already using, so that we can be seamlessly embedded into your workflows.

Agile and DevOps have made Continuous Testing essential. Yet, software testing is still dominated by legacy tools and outdated processes— which don’t meet the needs of today’s digital transformation initiatives.

Also, enterprises today are still performing over 80% of their testing manually — mostly at the UI layer. As a result, testing occurs late in the software development life cycle, leading to high costs, inefficiency, and delayed innovation. With Tricentis Tosca, customers can achieve over 90% test automation and “shift left” testing much earlier in the software development life cycle.

One distinctive Tricentis innovation is Vision AI, a next-generation AI-driven test automation technology that allows teams to automate UI test cases independent of the underlying technology.

Through machine learning, Vision AI sees and steers any UI just like a human user, making your automation future proof and as adaptable as the human brain. If you can see it, Vision AI can automate it. This includes anything from an app using now-deprecated technologies to an app using emerging technologies, to apps you access remotely. You can even start building test automation from mockups or whiteboard drawings. This brings a new meaning to test-driven development.

Another key advantage of the Tricentis Continuous Testing platform is that it helps enterprise organizations break through the automation barrier. Companies take automation further by using our complete platform for continuous testing across their UIs, back end, and even their data. With an extensive set of integrated tools for designing, optimizing, and maintaining resilient automation, they achieve scalable, sustainable success. z

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A guide to automated testing providers n

FEATURED PROVIDERS n

n Appvance: Appvance is the inventor of AI-driven autonomous testing, which is revolutionizing the $120B software QA industry. The company’s patented platform, Appvance IQ, can generate its own tests, surfacing critical bugs in minutes with limited human involvement in web and mobile applications. AIQ empowers enterprises to improve the quality, performance and security of their most critical applications, while transforming the efficiency and output of their testing teams and lowering QA costs. n Digital.ai: Digital.ai Continuous Testing (formerly Experitest) enables organizations to reduce risk and provide their customers satisfying, error-free experiences — across all devices and browsers. Digital.ai Continuous Testing provides expansive test coverage across 2000+ real mobile devices and web browsers, and seamlessly integrates with best-in-class tools throughout the DevOps/DevSecOps pipeline so developers can get test results faster and fix defects earlier in the process, allowing them to deliver secure, high-quality applications at-speed and at-scale. Learn more at www.digital.ai/continuous-testing n HCL Software: HCL Software is a division of HCL Technologies (HCL). HCL Software develops, markets, sells, and supports over 20 product families with particular focus on Customer Experience, Digital Solutions, Secure DevOps, and Security & Automation. Its mission is to drive ultimate customer success of their IT investments through relentless innovation of our software products. n Mabl: Mabl is the leading intelligent test automation platform built for CI/CD. It’s the only SaaS solution that tightly integrates automated end-to-end testing into the entire development life cycle. With mabl creating, executing, and maintaining reliable tests has never been easier, allowing software teams to increase test coverage, speed up development and improve application quality. To learn more about mabl, visit mabl.com. n Parasoft: Parasoft helps organizations continuously deliver quality software with its market-proven, integrated suite of automated software testing tools. Supporting the embedded, enterprise, and IoT markets, Parasoft’s technologies reduce the time, effort, and cost of delivering secure, reliable, and compliant software by integrating everything from deep code analysis and unit testing to web UI and API testing, plus service virtualization and complete code coverage, into the delivery pipeline. Bringing all this together, Parasoft’s award winning reporting and analytics dashboard delivers a centralized view of quality enabling organizations to deliver with confidence and succeed in today’s most strategic ecosystems and development initiatives — security, safety-critical, Agile, DevOps, and continuous testing. n SmartBear: At SmartBear, we focus on your one priority that never changes: quality. Our tools are built to streamline your process while seamlessly working with your existing products. Whether it’s TestComplete, Swagger, Cucumber, ReadyAPI, Zephyr, or one of our other tools, we span test automation, API life cycle, collaboration, performance testing, test management, and more. They’re easy to try, buy, and integrate, and are used by 15 million developers, testers, and operations engineers at 24,000+ organizations. n Tricentis: Tricentis Tosca, the #1 continuous test automation platform, accelerates testing with a script-less, AI-based, no-code approach for end-to-end test automation. With support for over 160+ technologies and enterprise applications, Tosca provides resilient test automation for any use case.

n Applitools is built to test all the elements that appear on a screen with just one line of code. Using Visual AI, you can automatically verify that your web or mobile app functions and appears correctly across all devices, all browsers and all screen sizes. Applitools automatically validates the look and feel and user experience of your apps and sites. It is designed to integrate with your existing tests rather than requiring you to create new tests or learn a new test automation language. Validate entire application pages at a time with a single line of code.

We support all major test automation frameworks and programming languages covering web, mobile, and desktop apps. n Eggplant (acquired by Keysight Technologies) Eggplant Digital Automation Intelligence (DAI) is the first AI-driven test automation solution with unique capabilities that make the testing process faster and easier. With DAI you can automate up to 80% of activities including test-case design, test execution, and results analysis. This allows teams to rapidly accelerate testing and integrate with DevOps at speed. n HPE Software’s automated testing solutions simplify software testing within fast moving Agile teams and for Continuous Integration scenarios. Integrated with DevOps tools and ALM solutions, HPE automated testing solutions keep quality at the center of today’s modern applications and hybrid infrastructures. n IBM: Quality is essential and the combination of automated testing and service virtualization from IBM Rational Test Workbench allows teams to assess their software throughout their delivery life cycle. IBM has a market leading solution for the continuous testing of end-to-end scenarios covering mobile, cloud, cognitive, mainframe and more. n Micro Focus: Accelerate test automation with one intelligent functional testing tool for web, mobile, API and enterprise apps. AI-powered intelligent test automation reduces functional test creation time continued on page 17 >

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Can Autonomous Testing Change Your QA Trajectory?

With AppvanceIQ, the answer is YES. AppvanceIQ can be trained one time and then learn changes from each build while

surfacing critical issues. AIQ augments

your existing tests by increasing application

coverage to near 100%. The world’s largest enterprises depend on AIQ daily to look for millions of potential issues, all with

little human intervention.

• Perfect for developers, QA engineers and even manual testers

• Identify API, UI and JS issues (end to end and API level)

• Web & native mobile – Salesforce, ServiceNow, SAP, Workday etc.

• Highlight performance issues within minutes of a new build

• Surface critical bugs in minutes with limited human intervention

• Flag changes between builds – missing features or defective server requests

• Augment your current tests to achieve near 100% application coverage

• Compare mobile user flow timings (with 33ms accuracy), even against competitive apps

Are you ready to change your trajectory?

Request a technical consultation today at https://appvance.ai/get-demo

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< continued from page 14 and maintenance while boosting test coverage and resiliency. Users can test both the front-end functionality and back-end service parts of an application to increase test coverage across the UI and API. n Microsoft’s Visual Studio helps developers create, manage, and run unit tests by offering the Microsoft unit test framework or one of several third-party and opensource frameworks. The company provides a specialized tool set for testers that delivers an integrated experience starting from Agile planning to test and release management, on-premises or in the cloud. n Mobile Labs (acquired by Kobiton) Mobile Labs remains the leading supplier of in-house mobile device clouds that connect remote, shared devices to Global 2000 mobile web, gaming, and app engineering teams. Its patented GigaFox is offered on-premises or hosted, and solves mobile device sharing and management challenges during development, debugging, manual testing, and automated testing. A pre-installed and pre-configured Appium server provides “instant on” Appium test automation. n NowSecure is the mobile app security software company trusted by the world’s most demanding organizations. Through the industry’s most advanced static, dynamic, behavioral and interactive mobile app security testing on real Android and iOS devices, NowSecure identifies the broadest array of security threats, compliance gaps and privacy issues in custom-developed, commercial, and business-critical mobile apps. NowSecure customers can choose automated software on-premises or in the cloud, expert professional penetration testing and

April 2021

SD Times

managed services, or a combination of all as needed. NowSecure offers the fastest path to deeper mobile app security and privacy testing and certification.

more efficient in functional, performance and load testing, improving test coverage and reducing the number of bugs that slip into production.

n Orasi is a leading provider of software testing services, utilizing test management, test automation, enterprise testing, Continuous Delivery, monitoring, and mobile testing technology.

n Sauce Labs provides the world’s largest cloud-based platform for automated testing of web and mobile applications.

Optimized for use in CI and CD environments, and built with an emphasis on security, reliability and scalability, users can run tests written in any language or framework using Selenium or Appium, both widely adopted open-source standards for automating browser and mobile application functionality.

n Perfecto: Users can pair their favorite frameworks with Perfecto to automate advanced testing capabilities, like GPS, device conditions, audio injection, and more. It also includes full integration into the CI/CD pipeline, continuous testing improves efficiencies across all of DevOps. With Perfecto’s cloud-based solution, you can boost test coverage for fewer escaped defects while accelerating testing. n ProdPerfect is an autonomous, end-toend (E2E) regression testing solution that continuously identifies, builds and evolves E2E test suites via data-driven, machine-led analysis of live user behavior data. It addresses critical test coverage gaps, eliminates long test suite runtimes and costly bugs in production, and removes the QA burden that consumes massive engineering resources. ProdPerfect was founded in January 2018 by startup veterans Dan Widing (CEO), Erik Fogg (CRO), and Wilson Funkhouser (Head of Data Science). n Progress: Telerik Test Studio is a test automation solution that helps teams be

n Synopsys: A powerful and highly configurable test automation flow provides seamless integration of all Synopsys TestMAX capabilities. Early validation of complex DFT logic is supported through full RTL integration while maintaining physical, timing and power awareness through direct links into the Synopsys Fusion Design Platform. n SOASTA’s Digital Performance Management (DPM) Platform enables measurement, testing and improvement of digital performance. It includes five technologies: TouchTest mobile functional test automation; mPulse real user monitoring (RUM); the CloudTest platform for continuous load testing; Digital Operation Center (DOC) for a unified view of contextual intelligence accessible from any device; and Data Science Workbench, simplifying analysis of current and historical web and mobile user performance data. n testRigor helps organizations dramatically reduce time spent on test maintenance, improve test stability, and dramatically improve the speed of test creation.

This is achieved through its support of "plain English" language that allows users to describe how to find elements on the screen and what to do with those elements from the end-user's perspective.

People creating tests on their system build 2,000+ tests per year per person.

On top of it, testRigor helps teams deploy their analytics library in production that will make systems automatically produce tests reflecting the most frequently used end-to-end flows from production. z

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