Code generation via machine learning
Commercial compiler implementors have to produce compilers that are capable of being used on a typical developer computer. A whole bunch of optimization techniques were known for years but could not be...
View ArticleSuccess does not require understanding
I took part in the second Data Science London Hackathon last weekend (also my second hackathon) and it was a very different experience compared to the first hackathon. Once again Carlos and his team...
View ArticleNever too experienced to make a basic mistake
I was one of the 170 or so people at the Data Science hackathon in London over the weekend. As always this was well run by Carlos and his team who kept us fed, watered and connected to the Internet....
View ArticleMachine learning in SE research is a bigger train wreck than I imagined
I am at the CREST Workshop on Predictive Modelling for Software Engineering this week. Magne Jørgensen, who virtually single handed continues to move software cost estimation research forward,...
View ArticleFinding the gold nugget papers in software engineering research
Academic research projects are like startups in that most fail to make any return on their investment (e.g., the tax payer does not get any money back) and a few pay for themselves and all the...
View ArticleFacebook’s Big Code Summit
I was at Facebook’s first Big Code Summit on Monday and Tuesday (I say the first, because I hope there is another one next year). The talks all involved machine learning (to be expected, given the Big...
View ArticleThe Algorithmic Accountability Act of 2019
The Algorithmic Accountability Act of 2019 has been introduced to the US congress for consideration. The Act applies to “person, partnership, or corporation” with “greater than $50,000,000 … annual...
View ArticleLearning useful stuff from the Reliability chapter of my book
What useful, practical things might professional software developers learn from my evidence-based software engineering book? Once the book is officially released I need to have good answers to this...
View ArticleSoftware effort estimation is mostly fake research
Effort estimation is an important component of any project, software or otherwise. While effort estimation is something that everybody in industry is involved with on a regular basis, it is a niche...
View ArticleClik here to view.
Growth in FLOPs used to train ML models
AI (a.k.a. machine learning) is a compute intensive activity, with the performance of trained models being dependent on the quantity of compute used to train the model. Given the ongoing history of...
View Article
