Refactor minimum deletions to use O(n) time

[yamcodes]

Summary by CodeRabbit

• Performance Improvements

  • Optimized algorithm for the LeetCode problem reduces time complexity from O(n²) to O(n), with the original approach retained for reference.

• Documentation

  • README updated with revised complexity metrics and improved in-code documentation/comments.

• Chores

  • Added contributor metadata/comments to the repository for maintainability.

[coderabbitai]

Caution

Review failed

The pull request is closed.

Walkthrough

This PR updates the README entry for LeetCode problem 1653 and replaces the solution implementation: it adds an optimized O(n) minimumDeletions(String) (with O(n) space) while preserving the original O(n²) approach as minimumDeletionsNaive(String), plus minor Javadoc and annotation edits.

Changes

Cohort / File(s)	Summary
Documentation README.md	Adjusted time/space complexities for problem 1653 and added contributor block metadata and suppression comment.
Algorithm Implementation src/main/java/.../minimumdeletionstomakestringbalanced/Solution.java	Added optimized O(n) minimumDeletions(String) using prefix/suffix counts, introduced minimumDeletionsNaive(String) preserving the O(n²) approach, added @SuppressWarnings("unused") to getSliceInfo, and updated Javadoc/header text.

Estimated code review effort

🎯 4 (Complex) | ⏱️ ~45 minutes

Possibly related PRs

• PR #10: Same code-level changes — replaces naive O(n²) implementation with optimized O(n), adds minimumDeletionsNaive, and includes @SuppressWarnings on getSliceInfo.
• PR #8: Directly related edits to the same Solution.java adding the naive getSliceInfo-based approach and adjustments around minimumDeletions.

Poem

🐰
From looping hills of n-squared night,
I hopped to linear morning light.
Prefix trails and suffix streams,
Balance found in tidy teams.
Hooray — a carrot for clean code! 🥕

🚥 Pre-merge checks | ✅ 3

✅ Passed checks (3 passed)

Check name	Status	Explanation
Description Check	✅ Passed	Check skipped - CodeRabbit’s high-level summary is enabled.
Title check	✅ Passed	The pull request title 'Refactor minimum deletions to use O(n) time' directly and clearly describes the main change: optimizing the time complexity from O(n²) to O(n) for the minimum deletions solution.
Docstring Coverage	✅ Passed	Docstring coverage is 100.00% which is sufficient. The required threshold is 80.00%.

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✨ Finishing touches

• 📝 Generate docstrings

🧪 Generate unit tests (beta)

• Create PR with unit tests
• Post copyable unit tests in a comment
• Commit unit tests in branch 9-improve-minimum-deletions-to-make-string-balanced-to-on-time-complexity

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[coderabbitai]

Caution

Some comments are outside the diff and can’t be posted inline due to platform limitations.

⚠️ Outside diff range comments (1)

src/main/java/codes/yam/leetcode/minimumdeletionstomakestringbalanced/Solution.java (1)

52-61: ⚠️ Potential issue | 🟡 Minor

Naive method returns Integer.MAX_VALUE for empty input.

If s is empty, minimumDeletionsNaive returns Integer.MAX_VALUE while minimumDeletions returns 0. This is likely a non-issue given LeetCode constraints (1 ≤ s.length), but worth noting the behavioral divergence if these methods are ever compared in tests.

🧹 Nitpick comments (1)

src/main/java/codes/yam/leetcode/minimumdeletionstomakestringbalanced/Solution.java (1)

76-106: Consider O(1) space single-pass variant.

The problem can be solved in O(n) time with O(1) space by maintaining a running bCount and tracking min(bCount + suffixA) in a single backward pass (or equivalently, a forward pass tracking bCount and computing min deletions on the fly). This would avoid the two auxiliary arrays.

Not a blocker — the current solution is clear and correct.