This proposal aims to as the name implies bring more structure to concurrent programming. This will be done by treating related tasks that are running in different threads as a single unit. Thus making it easier for us to manage the state, and also keep an eye on what’s happening.

Note: we won’t be diving into the synchronized keyword, or the Lock interfaces which offer additional capabilities compared to synchronized. But they’re certainly also worth looking into, but which flavour of lock fits best depends on your thread safety & performance requirements.

cross-posted from: https://programming.dev/post/5838448

I came across this semi-randomly by using Search Marginalia to find information on functional programming courses.

I also very much enjoyed the two articles referenced in the footnotes.

In this blog, I’ll outline why learning and mastering Spring Boot in 2023 is a worthwhile endeavor, even though there may be a few differing opinions. I’ll also explore how Spring Boot compares to other backend technologies and alternative Java frameworks.

Will Amper kill Maven and Gradle?

Tests can run assertions on your code but also reveal important insights about how your application really works.

Automated testing will assuredly go down in the annals of software development history as one of these industry-changing trends. Although few actually fully adhere to TDD discipline (I am in awe of those that do, just to be clear), most developers make sure to prioritize and include testing in their dev cycle. It took some time, but once the benefits of tests finally sunk into the collective developer psyche, tests successfully evolved from a chore, an inevitable victim of procrastination, to an important area of investment in your personal dev cycle.

Deceptively, the phrase ‘automated testing’ includes a wide gamut of testing techniques and methodologies. From unit tests, often just an echo of your coding assumptions, to integration tests, user-acceptable end-to-end testing, load testing, and more. In fact, early on developers were plagued by hard questions with no definitive answers around exactly that topic: ‘how much’ and ‘what’ exactly should be tested. How do you know you’ve tested enough?

An easy non-obtrusive way to collect data about your dockerized app without changing your existing docker-compose.yml or docker files.

Saved you a click:

• JaCoCo for test coverage,
• PMD for static code analysis
• SpotBugs (successor of FindBugs) for linting and enforce coding style/best practices,
• japicmp to check semantic versioning
• codecov and checkstyle.

Advances in the java programming language, version 16 and newer, slashed a million lines of code from my codebase. Maintaining my programs became easier overnight, due to this 1 secret trick: Records. 
Unfortunately version 16 was not LTS, so I had to wait until this year's release of version 21, which is LTS. 
 Go read the linked article. It explains Java Records in a very approachable manner.