Requirements & Design

Project goal

Inputs and outputs

Normalization rules

Counting strategy

Reporting plan

Prototype: tiny run

public class Main {
  public static void main(String[] args) {
    // Prototype: hard coded text, normalize, count, and print simple stats.
    String text = "To be, or not to be: that is the question. To be or not?";
    // 1) Lowercase
    String lower = text.toLowerCase();
    // 2) Replace non letters with spaces for splitting
    String cleaned = lower.replaceAll("[^a-z]+", " ");
    // 3) Split on spaces and filter empty tokens
    String[] tokens = cleaned.trim().split("\\s+");

    java.util.Map<String, Integer> freq = new java.util.HashMap<>();
    int total = 0;
    for (int i = 0; i < tokens.length; i = i + 1) {
      String w = tokens[i];
      if (w.length() == 0) continue;
      total = total + 1;
      Integer c = freq.get(w);
      if (c == null) freq.put(w, 1);
      else freq.put(w, c + 1);
    }

    // Simple top 3 by repeated linear scan (fine for small texts)
    for (int k = 0; k < 3; k = k + 1) {
      String bestWord = null;
      int bestCount = -1;
      for (java.util.Map.Entry<String,Integer> e : freq.entrySet()) {
        String word = e.getKey();
        int count = e.getValue();
        if (count > bestCount) {
          bestCount = count;
          bestWord = word;
        }
      }
      if (bestWord == null) break;
      System.out.println("#" + (k + 1) + " " + bestWord + " = " + bestCount);
      // mark as used
      freq.put(bestWord, -1000000);
    }

    System.out.println("Total words: " + total);
    System.out.println("Unique words: " + (freq.size()));
  }
}

Design first

Recap