Java Code Generation

Purpose

Generate correct, idiomatic Java implementations of algorithms, respecting Java conventions, generics, and professional file organization.

Critical: File Organization & Separation of Concerns

CRITICAL: Professional candidates organize code cleanly with clear separation.

Requirements:

1. One class per file - Never mix multiple implementations in one file
2. Descriptive filenames - Name matches class name exactly
3. Separate examples - Dedicated example/demo files for each variant
4. Logical grouping - Related functionality together, unrelated apart

Anti-patterns to AVOID:

• ❌ Multiple algorithm implementations in one file
• ❌ Generic names like Example.java for all demonstrations
• ❌ Mixing interface definitions with implementations
• ❌ Bundling unrelated functionality

Best practices:

• ✅ LinearScanIterator.java contains only LinearScanIterator class
• ✅ LinearScanExample.java demonstrates LinearScanIterator usage
• ✅ HeapBasedExample.java demonstrates HeapBasedIterator usage
• ✅ ComparisonDemo.java compares all variants side-by-side
• ✅ Clear naming reveals purpose without reading code

Critical: Implement Multiple Variants for Comparison

IMPORTANT: Implement multiple algorithm variants, not just the "optimal" one selected in Stage 3.

Why:

• Empirical validation of theoretical analysis
• Benchmark comparison baselines
• Demonstrates understanding of trade-offs
• Validates design decision with real data

Minimum Implementation Set:

1. Naive baseline - O(N²) or O(Nk) approach for comparison
2. Standard approach - Common textbook solution (e.g., binary heap)
3. Selected optimal - Algorithm chosen in Stage 3 (e.g., loser tree)

Benefits:

• Stage 6 benchmarks can measure actual performance differences
• Validates constant factor analysis from Stage 3
• Identifies crossover points (e.g., when naive wins for small k)
• Shows candidate can implement multiple approaches, not just one

Java Implementation Guidelines

• Use standard library types: Iterator<T>, PriorityQueue<T>, Comparator<T>
• Implement Iterator<T> interface with hasNext(), next(), remove() optional
• Handle generics properly with type erasure constraints
• Document with Javadoc
• Package structure: com.research.iterator
• Null checks: Objects.requireNonNull()
• Exceptions: NoSuchElementException for exhausted iterator
• Generics: Use bounded types <T extends Comparable<? super T>>
• Collections: Prefer ArrayList, PriorityQueue from stdlib

Multi-Variant Implementation Pattern

Structure code to support multiple algorithm implementations with same interface:

Java Package Structure

com/research/iterator/
├── LinearScanIterator.java          # O(Nk) naive baseline
├── LinearScanExample.java           # Demo LinearScanIterator
├── HeapBasedIterator.java           # O(N log k) standard (binary heap)
├── HeapBasedExample.java            # Demo HeapBasedIterator
├── LoserTreeIterator.java           # O(N log k) optimized (selected)
├── LoserTreeExample.java            # Demo LoserTreeIterator
└── ComparisonDemo.java              # Compare all variants side-by-side

Naming Convention

• Naive: LinearScanIterator, NaiveIterator
• Standard: HeapBasedIterator, StandardIterator
• Optimized: LoserTreeIterator, TournamentTreeIterator
• Examples: <Algorithm>Example.java for individual demos
• Comparison: ComparisonDemo.java for side-by-side comparison

Iterator Pattern Template

public class MergeIterator<T extends Comparable<? super T>> implements Iterator<T> {
    private PriorityQueue<Entry<T>> heap;

    public MergeIterator(List<? extends Iterator<T>> iterators) {
        // Initialize data structure
    }

    @Override
    public boolean hasNext() { /* ... */ }

    @Override
    public T next() { /* ... */ }

    @Override
    public void remove() {
        throw new UnsupportedOperationException("remove() not supported");
    }
}

Example File Template

package com.research.iterator;

import java.util.*;

/**
 * Demonstrates <AlgorithmName> usage and edge cases.
 */
public class AlgorithmNameExample {

    public static void main(String[] args) {
        demonstrateBasicUsage();
        demonstrateEdgeCases();
    }

    private static void demonstrateBasicUsage() {
        // Simple example with clear expected output
    }

    private static void demonstrateEdgeCases() {
        // Empty iterators, single iterator, unequal lengths
    }
}

Comparison Demo Template

package com.research.iterator;

import java.util.*;

/**
 * Compares LinearScanIterator, HeapBasedIterator, and LoserTreeIterator
 * on same input to verify correctness and demonstrate usage.
 */
public class ComparisonDemo {

    public static void main(String[] args) {
        // Prepare input data
        List<List<Integer>> testData = prepareTestData();

        // Run same test with all three variants
        System.out.println("=== Linear Scan (O(Nk)) ===");
        runTest(testData, "linear");

        System.out.println("\n=== Heap Based (O(N log k)) ===");
        runTest(testData, "heap");

        System.out.println("\n=== Loser Tree (O(N log k)) ===");
        runTest(testData, "loser");
    }

    private static void runTest(List<List<Integer>> data, String variant) {
        // Create iterators from data
        // Instantiate appropriate algorithm variant
        // Print results
    }

    private static List<List<Integer>> prepareTestData() {
        // Return test data sets
    }
}

Cross-Skill Integration

Requires: problem_specification, algorithmic_analysis Feeds into: unit_test_generation, benchmark_design