Apiumhub
JUNE 22, 2022
We are delighted to announce the release of our new book “ Software Architecture Metrics: Case Studies to Improve the Quality of Your Architecture ”. Global Software Architecture Summit for meeting all these software architects, who push me forward and who generate interesting discussions. ”- book authors.
Apiumhub
AUGUST 30, 2018
Let’s continue with our series of TDD articles, in the first part we looked at the theory behind the TDD and Unit Testing. In this second part, TDD First Cycle , we begin to develop our application, an application of notes where a user can write notes and everything that comes to our mind. TDD First Cycle.
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Apiumhub
SEPTEMBER 19, 2018
Last month we talked about TDD example in software development ( part 1 ) and TDD first cycle ( part 2 ). In this new TDD and primitive obsession article, we will focus on removing duplication and reinforcing the constructors of our entities, something key to have a robust system. TDD: primitive obsession. other.id; } }.
Apiumhub
AUGUST 16, 2018
After a while thinking about what type of TDD article to write about and, since there are many of them and very good theoretical ones (written by influencers in the world of software development), I have chosen to develop a mini-project while explaining the key points of the development of the application, basically giving you a TDD example.
Apiumhub
JUNE 14, 2022
It created and leads the community of Software Architecture in Barcelona, organizing meetups, workshops and hosting the GSAS (Global Software Architecture Summit ). Our core is Software Architecture, this is what we are famous for! Case Study: Matchmycolor (Swiss Based Company).
Apiumhub
OCTOBER 10, 2018
On September 29th – 30th, we were sponsoring Software Crafters Barcelona 2018 , where we also had a chance to give an opening speech and workshop on MVP & FRP for a controlerless architecture. The final goal of learning TDD is not to be a test expert. Microservices vs Monolithic architecture. Why Kotlin ? .
Apiumhub
OCTOBER 16, 2018
The flexible architecture of TensorFlow makes it easy for developers to implement computations on one or more GPUs or CPUs by using a single API. It provides a flexible architecture for scalable distributed training, and is extensible enough to run on a wide range of hardware configurations. TDD: first cycle ( part 2 ).
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