Today’s software release methodology involves multiple aspects of the SDLC: planning, scheduling, and managing a software build through the stages of developing, testing, deploying, and supporting the release. Release automation, as well as methodologies like Agile development, continuous delivery, and DevOps have greatly contributed to the evolution of release management. It is a core function … continue reading
Tricentis has announced its vision for the next-generation of AI-powered test automation. Vision AI is a test design and automation solution which allows organizations to address the needs brought about by the increasing prevalence of cloud-native and enterprise application platforms, according to the company. Vision AI is also now the core technology that will power … continue reading
Google shared its full perspective on supporting developers’ ability to choose how they distribute their apps through multiple app stores on different platforms, ensuring equal treatment for all apps, and allowing developers to communicate with customers. The company explained it will be making changes in Android 12 next year to make it easier for people … continue reading
Applications and the environments they live in continue to become more complex. While shift-left testing helps improve app quality, alone it’s not enough to ensure quality as new frameworks and tools emerge. With Applitools AI-powered visual testing and monitoring platform, leading companies are improving app quality, accelerating delivery cycles and reducing the time it takes … continue reading
OpenAI says it is backlogged with a waitlist of prospective testers seeking to assess if the first private beta of its GPT-3 natural language programming (NLP) tool really can push the boundaries of artificial intelligence (AI). Since making the GPT-3 beta available in June as an API to those who go through OpenAI’s vetting process, … continue reading
Microsoft has revealed it is teaming up with OpenAI to exclusively license GPT-3. According to the company, this will further Microsoft’s goals to develop and deliver advanced AI solutions for customers, as well as create new solutions that harness the power of advanced natural language generation. GPT-3 is an autoregressive language model that outputs human-like … continue reading
Snyk is looking to bolster its security platform with the acquisition of DeepCode, a provider of real-time semantic code analysis. Through its AI-powered platform, DeepCode is able to assist developers with app quality and security. According to Snyk, the addition of DeepCode will add to its existing open-source security, container security and infrastructure as code … continue reading
Google has announced a new set of services aimed at simplifying Machine Learning Operations (MLOps) for data scientists and machine learning (ML) engineers. According to Google, companies are using machine learning to solve challenging problems, but machine learning systems can create unwanted technical debt if it is not managed well. Google noted that machine learning … continue reading
The latest integration of traces allows Instana users to drill down into profiles related to individual requests and user traces which require investigation. “Instana’s single-click direct path from individual traces directly to applicable process profiles makes it both easy and quick for users to get the information they need to identify CPU, Memory and Concurrency … continue reading
Process change is more about people than process. At least until processes can be fully automated. During the past decade, I have championed technology-led process improvement initiatives at over a dozen large companies. I have seen process improvement implemented successfully primarily when such initiatives were pursued with a healthy mix of technology and human understanding … continue reading
Artificial intelligence (AI) is a broad field that spans academic research with ambitions to create an artificial human brain (general AI) through to practical applications of deep learning (DL), a branch of machine learning (ML, itself the part of AI concerned with learning systems built on data rather than prepared rules). DL has many real-world … continue reading
A couple of years ago, there was a lot of hype about using AI and machine learning (ML) in testing, but not a lot to show for it. Today, there are many options that deliver important benefits, not the least of which are reducing the time and costs associated with testing. However, a hands-on evaluation … continue reading
