The benchmark creates an array in the old generation (by being big enough) and stores an object (allocated in the new generation). This triggers the GC barrier for every writes. Something rare in real application.

The G1 barrier before Java 26 is slow because:

- the GC barrier and some GC threads do concurrent operations on the same memory zone (the card table)

- the barrier is big (a lot of assembler instructions) so it also troubles the loop unrolling optimization performed by JITs

Parallel GC has a simple barrier and do not care about latency (no GC check inside the loop).

The barrier implementation of G1GC was changed in Java 26, so update your Java runtime version and move on.

I think this is similar to the way Kotlin implements coroutine.

I believe Kotlin goes to the extra miles to also capture parts of the stack frames when creating the Continuation object so even when the runtime resume the continuation, the exceptions thrown later get the "correct" stack trace (not the one that shows that you come from a call through a MethodHandle).

You can interrupt a blocking IO operation with either interrupt() or close().

https://docs.oracle.com/en/java/javase/25/docs/api/java.base...

see https://victorwynne.com/dhh/

I do not know how this is called.

The other solution is to stack allocate and pass a pointer but as i said, unlike in C#, i do not think it's possible to do that in Java.

In Go, you can stack allocate but when you send a pointer (that escapes), the compiler will heap allocate the object.

For me, a struct in C/C# can be modified and is passed by copy while a value class can not be modified and is passed by value.

I do not think you can do stack allocation in Java.

So I do not understand why it's a surprise that minimizing the pause time requires more memory. Is it because there is no knob to set either the max pause time or the max memory ?

  > For example, rather than proposing one single concrete JIT implementation,
  > it may make more sense for the PEP to describe a JIT infrastructure that
  > can support multiple implementation strategies.
  > Since many different and promising JIT tracing approaches continue to be proposed,
  > we believe the infrastructure should make it easy to experiment with and evaluate
  > those approaches within CPython rather than be highly coupled with a single strategy.

You need stackful coroutine (like goroutine) for that.

https://www.wsj.com/articles/BL-TEB-2031

A hand-written recursive descent parser is something you do later when you start to industrialize your code, to get better error messages, make the parser incremental, etc.

Bison/ANTLR are code generators, they do not fit well in that model.

In the article, the example with the switch works because it switches on the class of the instance.

When inline is used on a parameter, it instructs the compiler to inline the expression at the call site. If the expression is substantial, this creates considerable work for the JIT compiler.

Requesting inlining at the compiler level (as opposed to letting the JIT handle it) is risky unless you can guarantee that a later compiler phase will simplify the inlined code.

There's an important behavioral difference between Scala 2 and 3: in 2, @inline was merely a suggestion to the compiler, whereas in 3, the compiler unconditionally applies the inline keyword. Consequently, directly replacing @inline with inline when migrating from 2 to 3 is a mistake.

https://github.com/CRaC/

    record AppVersion(int major, int minor, int patch) implements Comparable {
      public static AppVersion of(String version) {
        var array = Arrays.copyOf(Arrays.stream(version.split("\\.")).mapToInt(Integer::parseInt).toArray(), 3);
        return new AppVersion(array[0], array[1], array[2]);
      }

      public int compareTo(AppVersion other) {
        return Comparator.comparingInt(AppVersion::major)
            .thenComparingInt(AppVersion::minor)
            .thenComparingInt(AppVersion::patch)
            .compare(this, other);
      }

      public String toString() {
        return "%d.%d.%d".formatted(major, minor, patch);
      }
    }

For me, this is where lies the design flaw, trying to support both inheritance and be immutability at the same time.

https://en.wikipedia.org/wiki/Alleged_Libyan_financing_in_th...

  https://quickstarts.snowflake.com/guide/getting-started-with-cortex-aisql/index.html