Machine Learning in Software Testing
Attention for Bug Predictions
Bug Report Classifier with LSTM on Keras
Learning to LSTM
My Pandas Cheat Sheet
Investigating ROC/AUC
Executive Summary ROC and AUC are terms that often come up in machine learning, in relation to evaluating models. In this post, I try examine what ROC curves actually are, how they are calculated, what is a threshold in ROC curve, and how it impacts the classification if you change it. The results show that […]
Read More Investigating ROC/AUCPoW vs PoS. Whut?
Recently I have tried to understand blockchains and how they actually work. It seems the internet is full of high-level descriptions that always stop before actually explaining how the different blockchain variants really work. What is proof-of-work in practice, and what does proof-of-stake actually mean? What actually happens when you deploy a blockchain node in […]
Read More PoW vs PoS. Whut?Predicting issue categories on Github
Practical examples of applying machine learning seem to be a bit difficult to find. So I tried to create one for a presentation I was doing on testing and data analytics. I made a review of works in the area, and just chose one for illustrate. This one tries to predict a target category to […]
Read More Predicting issue categories on GithubPorting Naivecoin tutorial to Golang (first parts)
Recently I got interested in blockchains, and how do they work in practice. Found a nice tutorial called Naivecoin: a tutorial for building a cryptocurrency. There is also a nice book on the topic called Mastering Bitcoin: Programming the Open Blockchain. Had to get that too, didn’t I. So to get a better understanding of […]
Read More Porting Naivecoin tutorial to Golang (first parts)
Random experiments in software engineering 