Why Machine Learning in Software Engineering #3: The Future
There are many opportunities for Machine Learning in Software Engineering: testing, product management, processes… It might even set a sustainable pace!
Recent Posts
Why Machine Learning in Software Engineering #2: An Experiment
A Machine Learning in Software Engineering intern identified critical tests to run. He also confirmed the open-closed principle, modular code, and small-comm...
Why Machine Learning in Software Engineering #1: A World of Experts
It’s the opinions of experts that drive Software Engineering! Models, like Big O, would lead to more fact-based discussions and better decisions.
TO DO list or Mind Map for programming
Maintaining a TO DO list or a Mind Map for programming task has many benefits. It improves collaboration, our decisions and our vision of what’s left to do.
Does Programming equal Refactoring?
This infographics presents how TCR increases the share of refactoring in TDD. But Refactoring is already most of our daily work! We’d better learn it serious...
How to play planning poker… Badass Mode!
Planning poker and story points often turn into a power struggle where everyone loses. Here are 2 winning strategies for how to play planning poker as dev te...
Scrum with component teams leads to Waterfall Agile!
This infographic presents the perils of Scrum with component teams. It pushes organizations back in Waterfall Agile, late deliveries and non-sustainable work.
Too busy to prioritize?
This infographic presents how the lack of prioritization triggers a vicious circle of bloated organizations, late deliveries, and a non-sustainable pace