{"id":213,"date":"2022-07-04T12:37:03","date_gmt":"2022-07-04T12:37:03","guid":{"rendered":"https:\/\/techwyns.com\/tech\/?page_id=213"},"modified":"2022-07-04T12:43:08","modified_gmt":"2022-07-04T12:43:08","slug":"testing","status":"publish","type":"page","link":"https:\/\/techwyns.com\/tech\/testing\/","title":{"rendered":"Testing"},"content":{"rendered":"
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Quality Engineering & Testing for Digital Health Companies<\/h1>\n<\/div>\n<\/div>\n
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We do Quality Engineering for Wearables, Biosensors, and Companion Applications<\/p>\n<\/div>\n<\/div>\n

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Contact Us – 4253012760<\/span><\/span><\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n
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How We Help<\/h3>\n<\/div>\n<\/div>\n
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Digital Health Pioneers<\/h4>\n<\/div>\n<\/div>\n
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Set benchmarks for customer experience through mobile applications and hardware device testing & quality engineering services.<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/section>\n

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\"digital<\/figure>\n
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Digital Health Portal & Companion App Testing<\/h3>\n

Developing a user-friendly regulatory compliant websites, portals, and health app requires considerable consideration. Our team develops & executes test plans for our client apps<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n

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\"Firmware<\/figure>\n
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Firmware & Embedded Testing<\/h3>\n

Our engineering team develops destructive and non-destructive custom test plans and test beds to put your devices to the test, including battery utilization monitoring, sensor testing, and communication & connectivity testing<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n

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\"Compliance<\/figure>\n
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Compliance Testing<\/h3>\n

We make sure your project meets or exceeds regulatory compliance standards, including FDA, HIPAA, HITECH, ADA, CCPA, GDPR, PIPEDA and AODA<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n

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\"device<\/figure>\n
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Device Lab<\/h3>\n

We maintain a state-of-the-art mobile device lab allowing our clients to test their wearables & mHealth companion apps across current smartphone devices from major manufacturers<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/section>\n

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Did You Know?<\/h3>\n<\/div>\n<\/div>\n
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SAMSUNG<\/b>,\u00a0GOOGLE<\/b>,\u00a0APPLE\u00a0<\/b>AND OTHER MOBILE PHONE MANUFACTURERS MANAGE BLUETOOTH CONNECTIVITY AND COMPANION APPS DIFFERENTLY. IT IS IMPORTANT TO TEST YOUR DEVICE ACROSS VARIOUS GENERATIONS OF SMARTPHONES TO ENSURE COMPATIBILITY.<\/p>\n<\/div>\n<\/div>\n

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Get In Touch<\/span><\/span><\/div>\n<\/div>\n<\/div>\n<\/div>\n
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Organizations that\u00a0adopt\u00a0artificial intelligence (AI) in testing of microservices-based applications gain better accuracy, faster results, and greater operational efficiency.<\/p>\n

AI and machine-learning technologies\u00a0have matured over the last\u00a0few years, and today\u00a0their application <\/a>in automated testing\u00a0can help in more ways than one. In fact, AI has redefined the way microservices-based applications are tested, especially when it comes to\u00a0canary testing.<\/p>\n

The introduction of AI in software testing\u00a0helps both developers and testers alike. It improves accuracy;\u00a0the same steps can be performed accurately every time they’re needed. Automated testing can increase both the depth and scope of your tests, resulting in more thorough\u00a0overall test coverage. You can also leverage AI to simulate a large number of users interacting with your application.<\/p>\n

Here’s how AI-enabled\u00a0automation can help you test as you\u00a0scale microservices-based applications, as well as the challenges you’ll face\u00a0and effective strategies you can adopt to overcome them.<\/p>\n

Why traditional testing strategies don’t work<\/h3>\n

Traditionally, when\u00a0creating\u00a0monolithic applications, you’d\u00a0test each unit of\u00a0code\u00a0with unit tests. As different components of the application are joined together, you typically\u00a0test your application using integration testing first and, usually, system testing, regression testing, and user acceptance testing follow.<\/p>\n

If the code passes all of these tests, the release\u00a0goes out.<\/p>\n

Testing microservices-based applications\u00a0is not an easy task and is not the same as testing monoliths; you must be aware of not only the service you are testing but also its dependencies\u2014the services that work with the services under test.<\/p>\n

Owing to the granular nature of microservices architecture, boundaries that were previously hidden in a traditional\u00a0application\u00a0are exposed. You might have several different teams spread across geographical distances working simultaneously on different services;\u00a0this makes coordination extremely challenging. It can be\u00a0difficult to find a particular time window to perform end-to-end testing of the application as a whole.<\/p>\n

The distributed nature of microservices-based development poses many challenges to\u00a0testing your application. These\u00a0include:<\/p>\n

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  • Availability:<\/strong>\u00a0Because of the distributed nature of microservices architecture, it is difficult to find a time when all microservices are available.<\/li>\n
  • Isolation:<\/strong>\u00a0Microservices are designed to work in isolation together with other loosely coupled services. This implies that you should be able to test every component in isolation as well as testing them together.<\/li>\n
  • Knowledge gap:<\/strong>\u00a0You should possess a strong knowledge of each microservice;\u00a0this would help you to write effective test cases.<\/li>\n
  • Data:<\/strong>\u00a0Each microservice can have its own copy of data. In other words,\u00a0each\u00a0can have its own copy of the database, which may be different from another microservice’s copy. As a result, data integrity poses a challenge.<\/li>\n
  • Transactionality:<\/strong>\u00a0Unlike with a monolith, where transactionality is often assured at the database level, implementing transactionality between different microservices is challenging, because a transaction can consist of various service calls spread across different servers.<\/li>\n<\/ul>\n

    Typically, a microservices-based application consists of several services, each of which can dynamically scale up if needed. There is also a risk of failure and the cost of fixing bugs or\u00a0issues after integration. Hence, you should have an effective test strategy in place for testing microservices-based applications.<\/p>\n

    How to build an effective testing strategy<\/h4>\n

    To build an automated\u00a0testing process for a microservices-based application, you should\u00a0follow the same best practices you would for any other type of testing:<\/p>\n

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    • \u00a0Understand the customer’s expectations as far as test automation is concerned.<\/li>\n
    • Set quality goals\u2014and adhere to them.<\/li>\n
    • Analyze the testing types that are right for you to achieve the goals.<\/li>\n
    • Write tests according to the test pyramid (i.e., considering that the cost of the tests increases as you move up the pyramid).<\/li>\n<\/ul>\n

      AI-driven test automation: Embrace innovation<\/h3>\n

      Today’s software testers can\u00a0take advantage of AI\u00a0for test creation, test execution, and data analysis by using natural-language processing and advanced modeling techniques.\u00a0AI-based sofware\u00a0testing can help\u00a0by increasing efficiency, facilitating faster releases, improving test accuracy and coverage, and allowing for easier test maintenance, particularly when it comes to managing your test data.<\/p>\n

      For efficient test maintenance, you need to\u00a0know\u00a0what is happening to your data\u00a0at the time of test creation. Inadequate data modeling is one reason\u00a0why test maintenance fails,\u00a0becoming\u00a0a bottleneck in your deployment pipeline. AI can help with efficient data modeling and with root-cause analysis.<\/p>\n

      Repeating tests manually each time the source code changes\u00a0can be time-consuming and costly. Once you create automated tests, you execute them\u00a0repeatedly and quickly with no additional cost.<\/p>\n

      Use AI for canary testing<\/h3>\n

      Canary testing\u00a0helps reduce risks by gradually rolling out the changes to a small group of users before presenting it\u00a0to a larger audience\u2014and it is particularly useful in the testing of microservices-based applications. In a typical\u00a0application, the changes to\u00a0microservices happen independently of one another, so those\u00a0microservices need to\u00a0be verified independently as well.<\/p>\n

      AI can help automate\u00a0canary testing of\u00a0microservices-based applications. You can take advantage of AI concepts such as deep\u00a0learning to identify the changes in the new code and the issues within\u00a0it.\u00a0AI can be used to compare the experience of the small group of users\u00a0with that of the existing users, and this can be done automatically;\u00a0you don’t need any human intervention in the loop.<\/p>\n

      Challenges in AI-based microservices testing<\/h3>\n

      AI-based testing does have some constraints. While you can automate functional and unit tests, it is quite difficult to automate integration tests, because of complexity.<\/p>\n

      Some of the other challenges in AI-based testing include the following:<\/p>\n

      Skills<\/h4>\n

      Testing microservices-based applications with an AI-based approach requires extensive technical expertise from testers, and is very different from what\u00a0manual or automation testers\u00a0are used to. Testers should be adept at how to use\u00a0AI-based tools specifically for\u00a0microservices-based applications.<\/p>\n

      Use cases<\/h4>\n

      Learn how\u00a0to determine the best use cases for using AI in microservices\u00a0test automation. One\u00a0is to use AI for\u00a0creating your\u00a0unit tests. You can take advantage of AI to perform static code analysis and determine the portions of code that are not covered by your unit tests.<\/p>\n

      You can also use AI to update unit tests as soon as the source code changes, as well as for\u00a0test creation, execution,\u00a0data analysis, and API testing in microservices-based applications.<\/p>\n

      AI can help you understand the patterns and relationships in\u00a0API calls and\u00a0come up with more advanced patterns and inputs for testing the API. You can leverage an AI-powered continuous testing process to more efficiently detect the controls that have changed.<\/p>\n

      AI-based testing can’t do everything<\/h3>\n

      AI-based test automation of microservices can\u00a0create more reliable tests, and in so doing\u00a0slash the time needed for test creation, maintenance, and analysis. Such tests can in turn be used to check the service-to-service communication, test communication paths, etc.<\/p>\n

      You can also\u00a0leverage deep-learning\u00a0models and other AI techniques to empower your team to build tests faster and\u00a0execute\u00a0them at scale in the cloud.<\/p>\n

      Adopting AI for\u00a0microservices\u00a0test automation is no\u00a0panacea. It won’t magically eliminate all problems associated with software testing. But it can help you make your software testing process smarter, more efficient, and faster\u2014and thereby deliver business value consistently.<\/p>\n<\/div>\n<\/div>\n<\/div>\n

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      .<\/h3>\n

      Quality Engineering Services<\/h3>\n<\/div>\n<\/div>\n
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      For Digital Health Companies<\/h4>\n<\/div>\n<\/div>\n
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      \"QE<\/figure>\n
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      QE Consulting<\/h3>\n

      We work with your existing Quality Assurance or Quality Engineering Partner to develop test strategies, identify requirements, and expected outcomes of quality engineering projects<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n

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      \"Functional<\/figure>\n
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      Functional Testing<\/h3>\n

      Make sure your project meets your deliverable goals by validating that all user requirements, functions and features meet specifications<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n

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      \"performance<\/figure>\n
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      Performance Testing<\/h3>\n

      Speed kills user experience and revenue opportunities fast. Users expect your app, device or platform to run quickly. We put your project under a stress test to make sure it can handle real-world scenarios and fringe use cases<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/section>\n

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      Test Automation<\/h3>\n

      We help our clients get to market faster using automated AI\/ML testing platforms designed to find critical application errors quickly, pushing requirements back to developers for resolution<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n

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      \"regression<\/figure>\n
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      Regression Testing<\/h3>\n

      New changes, updates and features can break your app or device. Regression tests existing functionality, features and user experience are maintained from version to version.<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n

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      Security Testing<\/h3>\n

      Developing regulatory-compliant solutions for digital health requires a lot of security considerations. We help make sure that your app, platform and wearable devices maintain the highest level of security while in use, in transit and in rest.<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/section>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/section>\n","protected":false},"excerpt":{"rendered":"

      Quality Engineering & Testing for Digital Health Companies We do Quality Engineering for Wearables, Biosensors, and Companion Applications Contact Us – 4253012760 How We Help Digital Health Pioneers Set benchmarks for customer experience through mobile applications and hardware device testing & quality engineering services. Digital Health Portal & Companion App Testing Developing a user-friendly regulatory […]<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"pagelayer_contact_templates":[],"_pagelayer_content":"","footnotes":""},"class_list":["post-213","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/techwyns.com\/tech\/wp-json\/wp\/v2\/pages\/213","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/techwyns.com\/tech\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/techwyns.com\/tech\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/techwyns.com\/tech\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/techwyns.com\/tech\/wp-json\/wp\/v2\/comments?post=213"}],"version-history":[{"count":4,"href":"https:\/\/techwyns.com\/tech\/wp-json\/wp\/v2\/pages\/213\/revisions"}],"predecessor-version":[{"id":218,"href":"https:\/\/techwyns.com\/tech\/wp-json\/wp\/v2\/pages\/213\/revisions\/218"}],"wp:attachment":[{"href":"https:\/\/techwyns.com\/tech\/wp-json\/wp\/v2\/media?parent=213"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}