Test early, test often! Test early, test often! If you’ve ever attended a Software Engineering 101 class you will have heard this phrase drilled into your brain. Why? Because the earlier and more often you do your software testing, the less bugs persist in your code through to production.
Machine Learning as a Service (MLaaS) is a relatively new type of platform offered in the cloud. These are cloud services designed to help build, train, and then run predictive models incorporating machine learning (ML). ML can be handy for any organisation, whether it’s in accurately predicting sales data for the next month in a small business, through to a large enterprise building a custom chatbot for customer service.
One of the key pillars of Agile is trusting teams to self-organise. In practice, this often looks like teams picking their own tools to use. While it might sound like a scary, messy concept, if you have good talent they’ll be motivated to stay organised and on track with whatever solution they choose - or roll over to a better one when they find it.
Software development is an ever-evolving field. What was cutting edge five years ago is now standard or surpassed by something even faster, more effective, or more feature-rich. One of the changes that the field has undergone in recent years is swapping over development, test, and deployment software environments to the cloud.
Creating a digital roadmap for your business should be a key priority as we head into 2020 and beyond. If you haven’t yet started the digital transformation process, then it’s about time you begin the journey.
Productivity in software development is typically tricky to measure. Is it how fast your team are doing something? It has been proven time and again that lines of code is a poor measure; are the number of modules an indicator? The degree of module reuse within a project, or from previous projects?
Fixed price contracts can be rather tricky in a Scrum environment. Classic software development and Agile software development are very different from one another, and things that work in one environment don’t necessarily work in another.