Lambdas & Stream Pipelines

What you'll walk away with

Explain the language and JVM behavior behind Lambdas & Stream Pipelines
Test normal, boundary, invalid, and failure cases
Write maintainable and testable Java

Intermediate stream operations are lazy; the terminal operation starts the single-use pipeline.

Build a Complete Mental Model

A stream is not a data structure but a lazy, single-use processing pipeline over a source. Prefer stateless non-interfering operations, minimize side effects, and do not use parallel streams without measurement and correctness analysis.

Apply It in Real Java

Transform a collection with filter, map, and collect, proving the source is unchanged and work stays lazy until a terminal operation.

After This Lesson

Explain the contract and runtime behavior of Lambdas & Stream Pipelines
Compile and run an original example
Automate a boundary or failure test

java

import java.util.List;

class Main {
    public static void main(String[] args) {
        List<String> names = List.of("ada", "grace", "linus");
        List<String> result = names.stream()
            .filter(name -> name.length() >= 5)
            .map(String::toUpperCase)
            .toList();
        System.out.println(result);
    }
}

You should see

[GRACE, LINUS]

Try It Yourself

Transform a collection with filter, map, and collect, proving the source is unchanged and work stays lazy until a terminal operation.

Common Mistake

Reusing a consumed stream or mutating shared state in forEach while assuming parallel safety.

Java Stream API — Oracle

Easy traps

Reusing a consumed stream or mutating shared state in forEach while assuming parallel safety.
Assuming one sample output proves null, boundary, resource, and concurrency behavior are all correct.

Hands-on Exercise

Transform a collection with filter, map, and collect, proving the source is unchanged and work stays lazy until a terminal operation.

You'll know it worked when: [GRACE, LINUS]