This just in from Luis Espinal of MJUG:

http://www.easyb.org/

The EasyB syntax for writing stories and specifications is a lot more succinct than the one provided by Specs, the Scala BDD framework (at least when looked upon from a 10K foot view)
It also got me to think why TDD and BDD is not so common with plain Java. Java's atrocious verbosity makes it very hard to write tests and specs. At least superficially, it looks like a pleasure to use EasyB to write specs for Java and Scala programs.

Regards,

Luis Espinal
===
Scala appeals to developers because it's a functional language and not as verbose as most languages. You can see examples of another functional language, Clojure, in Contest Town. Eric Lavigne wrote an instant runoff election and a Wari program using Clojure.
An interesting discussion is going on in the MJUG mailing list. Thoughts?

Views: 36

Happy 10th year, JCertif!

Notes

Welcome to Codetown!

Codetown is a social network. It's got blogs, forums, groups, personal pages and more! You might think of Codetown as a funky camper van with lots of compartments for your stuff and a great multimedia system, too! Best of all, Codetown has room for all of your friends.

When you create a profile for yourself you get a personal page automatically. That's where you can be creative and do your own thing. People who want to get to know you will click on your name or picture and…
Continue

Created by Michael Levin Dec 18, 2008 at 6:56pm. Last updated by Michael Levin May 4, 2018.

Looking for Jobs or Staff?

Check out the Codetown Jobs group.

 

Enjoy the site? Support Codetown with your donation.



InfoQ Reading List

Netflix Migrates to Amazon Aurora: 75% Performance Boost and 28% Cost Reduction

Netflix consolidated its relational databases onto Amazon Aurora, cutting costs by 28% and boosting performance by up to 75%. The move from self-managed PostgreSQL reduced operational toil, improving latency for critical apps. This mirrors migrations by Samsung and Panasonic, though benchmarks suggest alternatives like Timescale may suit specific workloads better.

By Mark Silvester

TornadoVM 2.0 Brings Automatic GPU Acceleration and LLM support to Java

The TornadoVM project recently reached version 2.0, a major milestone for the open-source project that aims to provide a heterogeneous hardware runtime for Java. The project automatically accelerates Java programs on multi-core CPUs, GPUs, and FPGAs. This release is likely to be of particular interest to teams developing LLM solutions on the JVM.

By Ben Evans

Transformers v5 Introduces a More Modular and Interoperable Core

Hugging Face has released the first candidate for Transformers v5, marking a significant evolution from v4 five years ago. The library has grown from a specialized model toolkit to a critical resource in AI development, achieving over three million installations daily and more than 1.2 billion total installs.

By Robert Krzaczyński

Meta's Optimization Platform Ax 1.0 Streamlines LLM and System Optimization

Now stable, Ax is an open-source platform from Meta designed to help researchers and engineers apply machine learning to complex, resource-intensive experimentation. Over the past several years, Meta has used Ax to improve AI models, accelerate machine learning research, tune production infrastructure, and more.

By Sergio De Simone

Lyft Rearchitects ML Platform with Hybrid AWS SageMaker-Kubernetes Approach

Lyft has rearchitected its machine learning platform LyftLearn into a hybrid system, moving offline workloads to AWS SageMaker while retaining Kubernetes for online model serving. Its decision to choose managed services where operational complexity was highest, while maintaining custom infrastructure where control mattered most, offers a pragmatic alternative to unified platform strategies.

By Eran Stiller

© 2025   Created by Michael Levin.   Powered by

Badges  |  Report an Issue  |  Terms of Service