The Role of Artificial Intelligence in Software Development and Testing


According to Garter, artificial intelligence will be omnipresent in all spheres of technology and will successfully make its presence prominent among the top investment priority. The post The Role of Artificial Intelligence in Software Development and Testing appeared first on Kovair Blog. Application Lifecycle Management Technologies Test Management AI Artificial Intelligence Integrated Test Management Software development Test Automation

Dynatrace named a Leader in the Forrester Wave™: Artificial Intelligence for IT Operations (AIOps) report


We are excited to announce that Dynatrace has been named a Leader in the Forrester Wave™: Artificial Intelligence for IT Operations (AIOps), 2020 report. Other strengths include microservices, transaction, and customer experience (CX) monitoring, and intelligent analytics.


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How Artificial Intelligence Can Help Software Testing?


Artificial intelligence is currently being used in an array of sectors, from processing natural language to analyzing facial expressions, and more. However, it’s also important to understand that the capability of artificial intelligence is constantly evolving. For example, Alexa and Siri were once considered state-of-the-art, … The post How Artificial Intelligence Can Help Software Testing?

How Application of Artificial Intelligence is Transforming Business


What is Artificial Intelligence? Artificial intelligence works on the principle of human intelligence. Artificial Narrow Intelligence. Almost all artificial machines built to date fall under this category. Artificial General Intelligence. Also known as Strong AI, the evolution of Artificial Intelligence in this stage would be such that machines possess the ability to think, act and make decisions just like humans.

Modern approaches to observability and monitoring for multicloud environments


To identify those that matter most and make them visible to the relevant teams requires a modern observability platform with automation and artificial intelligence (AI) at the core. Turning raw data into actionable business intelligence. AI-driven software intelligence.

The future of software testing: Machine learning to the rescue

TechBeacon Testing

App Dev & Testing, Testing, Test Automation, Predictive Analytics, Quality Assurance (QA), Shift-left, Artificial Intelligence (AI), Machine LearningThe last decade has seen a relentless push to deliver software faster.

How AI improves microservices testing automation

TechBeacon Testing

Organizations that adopt artificial intelligence (AI) in testing of microservices-based applications gain better accuracy, faster results, and greater operational efficiency. App Dev & Testing, Testing, Test Automation, Microservices, Artificial Intelligence (AI), Test Automation

Testing AI-based apps? Think like a human

TechBeacon Testing

Your testing of software that includes artificial intelligence (AI) components will be more sophisticated and robust if you just think in human terms. App Dev & Testing, Testing, Artificial Intelligence (AI), Machine Learning, Predictive Analytics, Special Coverage: TSQA 2020 Conference

The Broken Promise of Test Automation: Why Are We Still Hand-Cranking Tests?


devops performance machine learning artificial intelligence test automation qa quality assurance continuous testing intelligent testingRemember when test automation was being peddled as a silver bullet for testing bugbears? Of course, those vendors really meant test execution automation. Automating test execution was going to increase coverage, minimize testing time, and overall reduce the amount of money being spent on testing. It would even butter your toast in the morning.

Is Quality With Speed Really Possible in Software Testing?


Moving Intelligently in Competitive Times. software testing continuous delivery continuous integration artificial intelligence (ai) agile coding automated feedback solutionLiving in competitive times, it is very important for the applications to be as sophisticated and accurate as can be. There is no margin for any sort of gaps.

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AI in testing: 13 essential resources for QA pros

TechBeacon Testing

App Dev & Testing, Testing, Artificial Intelligence (AI), Test AutomationWhat if you could make software testing simple? What if it could be done without all the conversations, questions, defect reports, and metrics?

Modern Dev Teams Are More Efficient Than Ever: Quality Engineering Should Be Too!


This XKCD cartoon captures life: devops performance testing automation artificial intelligence developer qa and software testing qa and testing development teamsEarlier in my career (though it seems like yesterday), product teams I was a part of did everything “on-prem”, and angst-ridden code compiles took place every few months. We’d burn down bugs using manual QA and push to production after several long nights before taking a long nap and doing it all again next quarter.

How I Ran 100 UI Tests in Just 20 Seconds


technology testing app development test automation artifical intelligence user interface test automation tools ai artificial intelligence visual testingApplitools Visual AI then grabs a screenshot of each page, compares it to its baseline screenshot, and determines visual differences and the root cause unpinning them. In less than a minute, your cross-browser testing is done and your developers have what they need to fix any visual bugs.

How Do You Catch More Bugs In Your End-To-End Tests?


testing test automation code test bugs artificial intelligence (ai) hackathon end to end testing code maintenance test codeHow much is it worth to catch more bugs early in your product release process? Depending on where you are in your release process, you might be writing unit or systems tests. But, you need to run end-to-end tests to prove behavior, and quality engineers require a high degree of skill to write end-to-end tests successfully.

AI in testing: What it is, and why it matters

TechBeacon Testing

App Dev & Testing, Testing, Artificial Intelligence (AI), Test Automation, LookbookAI in testing is becoming mainstream. Some 21% of IT leaders surveyed said they are putting AI trials or proofs of concept in place, according to the 2019-2020 World Quality Report. Speaking to longer-term trends, only 2% of respondents said AI has no part in their future plans.

Test automation tools: Top trends and challenges for 2020

TechBeacon Testing

App Dev & Testing, Testing, Test Automation, Artificial Intelligence (AI), Robotic Process Automation (RPA), DevOps SecurityTest automation tools have been steadily evolving—a trend that shows no sign of slowing down in the coming year. Several key advances to watch for over the next 12 months should make life easier for test automation engineers, consultants and tool vendors say, while others to watch out for are only likely to add confusion.

Advancing Application Performance with NVMe Storage, Part 1


This has given rise to a completely new set of computing workloads for Machine Learning which drives Artificial Intelligence applications. performance machine learning ai artificial intelligence nvme parallel computing high performance workloadWith big data on the rise and data algorithms advancing, the ways in which technology has been applied to real-world challenges have grown more automated and autonomous.

Rise of the machines: The coming AI/testing singularity

TechBeacon Testing

Artificial intelligence (AI) is the next exponential technology trend, and it's knocking on your front door. App Dev & Testing, Testing, Artificial Intelligence (AI), Machine Learning, Special Coverage: STAREAST Conference 2019, Test Automation

How to Use AI for Software Testing


Technologies Test Management AI Artificial Intelligence Continuous Testing Multiple Testing Tools Software developmentTechnology is ever-changing and evolving with every passing day. Something new comes up which improves the overall performance of a software. A lot of improvements. The post How to Use AI for Software Testing appeared first on Kovair Blog.

STAREAST preview: 3 testing trends to watch

TechBeacon Testing

App Dev & Testing, Testing, Application Testing, Artificial Intelligence (AI Alan Page, who wrote How We Test at Microsoft and hosts a podcast about testing, once famously observed that testing, as a field, seemed stagnant. He proved his point by reviewing the sessions from a conference and showing how they were interesting today—even though that conference had taken place 10 years earlier.

Perhaps Consciousness is Just Human Observability?

Adrian Cockcroft

This is different to the question of whether we can figure out how to create artificial intelligence, as I don’t think intelligence is a prerequisite for consciousness, its an attribute of more sophisticated conscious systems that allows us to interact with and view the internal model more directly than observing the raw behavior of the system. It’s possible for a human to be unconscious or asleep, without losing intelligence in the process.

5 Best Techniques for Automated Testing


Even in a new survey, 84% of participants stated that they think the implementation of Artificial Intelligence can provide them with a competitive advantage over competitors. New technologies and techniques are shaping the future at the same pace.

Misconceptions of the Automated Testing Debunked


With artificial intelligence quickly gaining traction, total automation sounds like an inevitable reality. Recently, automated software testing has been widely identified as a game-changer for software projects. Yet those jumping to conclusions gave birth to more common misconceptions related to the way automated testing is applied today. Myth 1: Automation Isn't About Cost-Efficiency. At the starting point, automated testing does require considerable investment.

Quality Sense Podcast With Júlio de Lima - Using ML to Understand Performance Test Results


In this Quality Sense episode, Federico Toledo has a chat with Júlio de Lima , an engineer at Capco, who recently completed his master’s degree in Electrical Engineering and Computing (Artificial Intelligence) and also co-founded GaroaQA , a meetup group with four locations across Brazil and over 2,000 members.

Will AI Perform Testing?


Many testers often wonder whether AI (Artificial intelligence) will threaten their existence in the future. This topic becomes even more important in the context of today’s tech-driven world where a huge number of software companies are steadily adopting high-end technologies like AI and ML. In this post, we’ve tried to find out will AI be … The post Will AI Perform Testing? appeared first on QA Mentor Blog. Software Testing

The best software testing conferences of 2019

TechBeacon Testing

Some may see testing as a fairly boring and static set of practices, but the leaders in this space know that it is a vibrant discipline that is constantly improving every year, thanks to exciting new techniques made possible by better automation tools and artificial intelligence.

Web Testing Challenges Testers Will Encounter in 2019


And software testing is being forced to be reinvented every day due to the introduction of new technologies like artificial intelligence, virtualization, and predictive analysis. With the introduction of the agile methodology and transformation into the digital world, the software development lifecycle is changing rapidly and increasing the need for better software testing capabilities.

Advancing Application Performance with NVMe Storage, Part 3


Financial Analytics – Financial services and financial technology (FinTech) are increasingly turning to automation and artificial intelligence to fuel their decision making processes for investments. NVMe Storage Use Cases. NVMe storage's strong performance, combined with the capacity and data availability benefits of shared NVMe storage over local SSD, makes it a strong solution for AI/ML infrastructures of any size. There are several AI/ML focused use cases to highlight.

The best software QA and testing conferences of 2020

TechBeacon Testing

Some may see testing as a fairly boring and static set of practices, but leaders in this space know it is a vibrant discipline that is constantly improving every year, thanks to exciting new techniques made possible by better automation tools and artificial intelligence.

Using Dynatrace to master the 5 pillars of the AWS Well-Architected Framework (Part 1)


To bring higher-quality information to Well-Architected Reviews and to establish a strategic advanced observability solution to support the Well-Architected Framework 5-pillars, Dynatrace offers a fully automated, software intelligence platform powered by Artificial Intelligence.

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G2 users rate Dynatrace number 1 in observability


This latest G2 user rating follows a steady cadence of recent industry recognition for Dynatrace, including: Named a leader in The Forrester Wave™: Artificial Intelligence for IT Operations, 2020. Dynatrace news.

The journey to modern manufacturing with AWS

All Things Distributed

From the Internet of Things (IoT) to Artificial Intelligence (AI) and task automation to predictive maintenance technology, the advancements in this space are creating a world of new opportunity. One of the most rewarding parts of my job is getting to watch different industries implement new technologies that improve and transform business operations. Manufacturing, in particular, has always captivated my attention in this respect.

Ensuring Performance, Efficiency, and Scalability of Digital Transformation

Alex Podelko

Marrying Artificial Intelligence and Automation to Drive Operational Efficiencies by Priyanka Arora, Asha Somayajula, Subarna Gaine, Mastercard. – Application of Artificial Intelligence to operations – as done at Mastercard. The CMG Impact conference (February 10-12, 2020 in Las Vegas) is coming.

AI-powered DNS request tracking extends infrastructure observability for high quality network traffic


The Dynatrace Software Intelligence Platform gives you a complete Infrastructure Monitoring solution for the monitoring of cloud platforms and virtual infrastructure, along with log monitoring and AIOps. Dynatrace news.

Gartner: Observability drives the future of cloud monitoring for DevOps and SREs


This is why the report frames artificial intelligence for IT operations (AIOps) as a crucial enabler of observability within today’s massive cloud-native architectures that increasingly rely on microservices and containerized environments. Dynatrace news.

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AWS re:Invent 2020 talks related to sustainability

Adrian Cockcroft

Fighting wildfire with artificial intelligence ZWL201 ?—?Scaling Photo taken by Adrian?—?Orange Orange mid-day sky at San Gregorio Beach?—?smoky smoky from wildfires I’ve recently become involved with the new Linux Foundation Open Source Climate Finance organization ( OS-Climate ).

What is APM?


The Dynatrace Software Intelligence Platform provides all-in-one advanced observability. With intelligence into user sessions, including Real User Monitoring and Session Replay , you can connect experiences to business outcomes like conversions, revenue and KPI’s. Artificial intelligence for IT operations (AIOps): AIOps platforms combine big data and machine learning functionality to support IT operations. Dynatrace news.

Why you need Dynatrace on Azure Workloads


While it may seem that Azure Monitor and Dynatrace are in the same space of collecting metrics, the way Dynatrace adds automation and intelligence to the data elevates Dynatrace away from the Application Performance Monitoring/Gen2 monitoring pack. Operations: Responsible for ensuring flawless performance of the overall applications they support requires real-time, contextual data, powered by built-in Artificial Intelligence to avoid war rooms. Dynatrace news.

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Could intellectual debt derail your journey to the autonomous cloud?


One of the fundamental differences between machine learning systems and the artificial intelligence (AI) at the core of the Dynatrace Software Intelligence Platform is the method of analysis. Dynatrace news. In part one, we began our discussion about intellectual debt by pointing out how machine learning systems contribute to the widening gap between what works and our understanding of why it works.

How I jumped from software testing to data science

TechBeacon Testing

Today, I even build artificial intelligence (AI) models for recommender systems, chatbots, and cutting-edge privacy protection algorithms. My journey from testing into data science was pretty straightforward. First, I learned how to break software, then to monitor production services for regressions, and finally to build models to optimize user experience.

CIO research: Cloud complexity of growing concern


Our research revealed that many organizations – 88% of CIOs to be precise – believe that the use of artificial intelligence (AI) will be paramount to IT’s ability to overcome this increasing complexity, and management of IT performance problems. Dynatrace news. My favorite slide, that I used in nearly every one of my presentations, is a simple statement; “You have one of the hardest jobs in the world.”.

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Top 5 Must-Have Features of Regression Testing Automation Tools


Testsigma’s Artificial Intelligence is smart enough to locate the elements precisely even with the changes made in the attribute and automatically modify the change made in the source code to prevent the failure of the tests.

Digital Business Analytics: Accelerating your dashboard journey


With advancements in artificial intelligence (AI), machine learning and self-healing, one begins to wonder if dashboards are even needed anymore. Dynatrace news.