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Testing Machine Learning: Insight and Experience from Using Simulators to Test Trained Functionality
When testing machine learning systems, we must apply existing test processes and methods differently. Machine Learning applications consist of a few lines of code, with complex networks of weighted data points that form the implementation. The data used in training is where the functionality is ultimately defined, and that is where you will find your issues and bugs.
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Proven Solutions to Five Test Automation Issues
Automated testing is often blocked due to some well-known issues, especially in a microservices architecture. API and service simulators can eliminate five common issues that block test automation.
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Velocity and Better Metrics: Q&A with Doc Norton
Velocity is not good for predictions or diagnostics, argued Doc Norton at Experience Agile 2019. It's a lagging indicator of a complex system which is too volatile to know what our future performance will be; it isn’t stable enough to be used reliably. We can use Monte Carlo simulation for forecasting, and cumulative flow diagrams to track work, see changes in scope, and spot bottlenecks.
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Using Java to Orchestrate Robot Swarms
Ocado Technology uses state-of-the-art robotics to power highly automated fulfillment centres. To orchestrate the robot swarms and maximise every bit of efficiency from the warehouses, they've developed a control system analogous to an air traffic control system. This article covers decisions regarding the language, development principles, and architecture choices.
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Open Source Robotics: Getting Started with Gazebo and ROS 2
An introduction to Gazebo, a powerful robot simulator that calculates physics, generates sensor data and provides convenient interfaces, and ROS 2, the latest version of the Robot Operating System, which offers familiar tools and capabilities, while expanding to new use cases. Both are open source and used by academia and industry alike.
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Simulation-Based Embedded Agile Development
In this article, authors discuss how simulation-centric development can improve product quality, reduce cost, and deliver reliable working code. They talk about using simulation as an integral part of the development process, to be utilized continuously throughout the product development life cycle.