feat(algorithms, strings, dynamic programming): word break #118
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BrianLusina
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Caution Review failedThe pull request is closed. WalkthroughAdds a Word Break feature with five solution implementations and tests, introduces an AlphabetTrie and AlphabetTrieNode (with exports), and updates DIRECTORY.md to rearrange several algorithm/navigation entries; includes a minor test formatting change. Changes
Estimated code review effort🎯 4 (Complex) | ⏱️ ~45 minutes
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Actionable comments posted: 4
🧹 Nitpick comments (5)
algorithms/dynamic_programming/word_break/__init__.py (3)
86-89: List aliasing issue with[[]] * npattern.Using
[[]] * (len(s) + 1)creates a list where all elements initially reference the same empty list object. While the current code works becausedp[i] = tempreassigns each position, this pattern is error-prone and could cause subtle bugs if the code is modified later.Apply this diff to use a list comprehension for independent lists:
# Initializing the dp table of size s.length + 1 - dp = [[]] * (len(s) + 1) + dp: List[List[str]] = [[] for _ in range(len(s) + 1)] # Setting the base case dp[0] = [""]
104-108: Consider using a set for O(1) lookup.The
suffix in word_dictcheck on a list has O(m) complexity where m is the dictionary size. Convertingword_dictto a set would improve this to O(1) average case.+ word_set = set(word_dict) + # For each substring in the input string, repeat the process. for i in range(1, len(s) + 1): prefix = s[:i] ... - if suffix in word_dict: + if suffix in word_set:
145-146: Consider using a set for O(1) lookup in word_break_dp_2 as well.Similar to
word_break_dp, the dictionary lookup could benefit from set conversion.datastructures/trees/trie/alphabet_trie/alphabet_trie.py (2)
4-15: Add docstrings for the class and methods.The
AlphabetTrieclass and itsinsertmethod lack docstrings. Adding comprehensive docstrings would improve code maintainability and help users understand the purpose, parameters, and behavior of the trie.Apply this diff to add docstrings:
class AlphabetTrie: + """ + A trie data structure for storing English words (a-z). + + Uses a fixed 26-child array per node for efficient storage + and retrieval of lowercase English words. + """ def __init__(self): self.root = AlphabetTrieNode() def insert(self, word: str) -> None: + """ + Insert a word into the trie. + + Args: + word: The word to insert (must contain only English letters a-z). + + Raises: + ValueError: If word contains non-English letters. + """ node = self.root for char in word: index = ord(char.lower()) - ord("a") if not node.children[index]: node.children[index] = AlphabetTrieNode() node = node.children[index] node.is_end_of_word = True
4-15: Consider adding a search method for completeness.The
AlphabetTriecurrently only supports insertion. Adding asearchorcontainsmethod would make the trie more useful for typical trie operations like word lookup and prefix checking.Would you like me to generate the implementation for
searchandstarts_withmethods?
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📒 Files selected for processing (10)
DIRECTORY.md(3 hunks)algorithms/dynamic_programming/word_break/README.md(1 hunks)algorithms/dynamic_programming/word_break/__init__.py(1 hunks)algorithms/dynamic_programming/word_break/test_word_break.py(1 hunks)algorithms/greedy/gas_stations/test_gas_stations.py(1 hunks)datastructures/trees/trie/__init__.py(1 hunks)datastructures/trees/trie/alphabet_trie/README.md(1 hunks)datastructures/trees/trie/alphabet_trie/__init__.py(1 hunks)datastructures/trees/trie/alphabet_trie/alphabet_trie.py(1 hunks)datastructures/trees/trie/alphabet_trie/alphabet_trie_node.py(1 hunks)
🧰 Additional context used
🧬 Code graph analysis (5)
algorithms/greedy/gas_stations/test_gas_stations.py (1)
algorithms/greedy/gas_stations/__init__.py (1)
can_complete_circuit(4-31)
algorithms/dynamic_programming/word_break/__init__.py (1)
datastructures/trees/trie/alphabet_trie/alphabet_trie.py (1)
AlphabetTrie(4-15)
datastructures/trees/trie/__init__.py (2)
datastructures/trees/trie/alphabet_trie/alphabet_trie.py (1)
AlphabetTrie(4-15)datastructures/trees/trie/alphabet_trie/alphabet_trie_node.py (1)
AlphabetTrieNode(4-7)
datastructures/trees/trie/alphabet_trie/alphabet_trie.py (1)
datastructures/trees/trie/alphabet_trie/alphabet_trie_node.py (1)
AlphabetTrieNode(4-7)
datastructures/trees/trie/alphabet_trie/__init__.py (2)
datastructures/trees/trie/alphabet_trie/alphabet_trie.py (1)
AlphabetTrie(4-15)datastructures/trees/trie/alphabet_trie/alphabet_trie_node.py (1)
AlphabetTrieNode(4-7)
🪛 LanguageTool
algorithms/dynamic_programming/word_break/README.md
[style] ~39-~39: ‘whether or not’ might be wordy. Consider a shorter alternative.
Context: ... every word of the dictionary and check whether or not the string starts with the current ...
(EN_WORDINESS_PREMIUM_WHETHER_OR_NOT)
[style] ~124-~124: Three successive sentences begin with the same word. Consider rewording the sentence or use a thesaurus to find a synonym.
Context: ...the dp table equal to the temp array. - We repeat the steps above for all prefixes...
(ENGLISH_WORD_REPEAT_BEGINNING_RULE)
🪛 markdownlint-cli2 (0.18.1)
DIRECTORY.md
71-71: Unordered list indentation
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🔇 Additional comments (14)
algorithms/greedy/gas_stations/test_gas_stations.py (1)
8-14: LGTM!The reformatting of the
@parameterized.expanddecorator to a multi-line structure improves readability while preserving the same test cases and functionality.DIRECTORY.md (4)
71-72: LGTM!The Word Break entry is correctly added under Dynamic Programming, aligning with the new implementation.
86-89: LGTM!Gas Stations and Majority Element entries are appropriately placed under the Greedy section.
96-101: LGTM!Interval-related entries (Insert Interval, Meeting Rooms, Merge Intervals) are properly organized under the Intervals section.
343-345: LGTM!Alphabet Trie documentation entries are correctly added, matching the new trie implementation files.
algorithms/dynamic_programming/word_break/__init__.py (2)
5-66: Well-structured trie-based implementation.The reverse DP approach with trie traversal is correctly implemented. The algorithm properly builds sentences by combining current words with previously computed suffixes.
115-160: Clean implementation of reverse DP.This function mirrors the trie-based approach but uses direct dictionary lookups, providing a good alternative when trie overhead isn't needed.
datastructures/trees/trie/alphabet_trie/README.md (1)
1-3: LGTM!Basic documentation is in place. Consider expanding with usage examples in a future update.
datastructures/trees/trie/alphabet_trie/alphabet_trie_node.py (1)
4-7: LGTM!Clean implementation of the trie node with proper type annotations. The fixed-size children array of 26 elements correctly maps to lowercase alphabet characters.
algorithms/dynamic_programming/word_break/README.md (2)
61-141: Excellent documentation of the DP approach!The explanation of the dynamic programming tabulation approach is comprehensive, well-structured, and includes helpful step-by-step breakdowns. The optimal substructure and overlapping subproblems properties are clearly explained with concrete examples.
142-154: All referenced image files exist inimages/solution/. No action required.datastructures/trees/trie/alphabet_trie/__init__.py (1)
1-7: LGTM!The package initialization correctly exports
AlphabetTrieandAlphabetTrieNode, following Python packaging conventions.datastructures/trees/trie/__init__.py (1)
5-6: LGTM!The additions correctly export
AlphabetTrieandAlphabetTrieNodefrom the trie package, maintaining consistency with the existing export pattern.Also applies to: 13-14
algorithms/dynamic_programming/word_break/test_word_break.py (1)
1-4: Verify the test execution and coverage.The test file is well-structured with comprehensive test cases covering various scenarios (overlapping dictionary entries, multiple valid segmentations, and unsplittable strings). Please ensure that all three implementations (
word_break_trie,word_break_dp, andword_break_dp_2) are correctly imported and that the tests pass successfully.
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Actionable comments posted: 2
♻️ Duplicate comments (2)
algorithms/dynamic_programming/word_break/__init__.py (1)
39-41: Case sensitivity mismatch remains unaddressed.This issue was previously identified: the code doesn't lowercase
charbefore computing the index, whileAlphabetTrie.insert()does. Uppercase characters will produce incorrect (potentially negative or out-of-bounds) indices.Apply this diff:
for end_idx in range(start_idx, len(s)): char = s[end_idx] - index = ord(char) - ord("a") + index = ord(char.lower()) - ord("a")algorithms/dynamic_programming/word_break/README.md (1)
138-138: Formatting issue remains unaddressed.This was previously identified: "than
q" should be "thanq" (add space before backtick).Apply this diff:
- least one character shorter than`q`. Therefore, this problem obeys the optimal substructure property. + least one character shorter than `q`. Therefore, this problem obeys the optimal substructure property.
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📒 Files selected for processing (3)
algorithms/dynamic_programming/word_break/README.md(1 hunks)algorithms/dynamic_programming/word_break/__init__.py(1 hunks)algorithms/dynamic_programming/word_break/test_word_break.py(1 hunks)
🚧 Files skipped from review as they are similar to previous changes (1)
- algorithms/dynamic_programming/word_break/test_word_break.py
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algorithms/dynamic_programming/word_break/__init__.py (1)
datastructures/trees/trie/alphabet_trie/alphabet_trie.py (1)
AlphabetTrie(4-15)
🪛 LanguageTool
algorithms/dynamic_programming/word_break/README.md
[style] ~45-~45: ‘whether or not’ might be wordy. Consider a shorter alternative.
Context: ... every word of the dictionary and check whether or not the string starts with the current ...
(EN_WORDINESS_PREMIUM_WHETHER_OR_NOT)
[style] ~192-~192: Three successive sentences begin with the same word. Consider rewording the sentence or use a thesaurus to find a synonym.
Context: ...the dp table equal to the temp array. - We repeat the steps above for all prefixes...
(ENGLISH_WORD_REPEAT_BEGINNING_RULE)
🔇 Additional comments (3)
algorithms/dynamic_programming/word_break/__init__.py (1)
115-160: LGTM!The dictionary-based DP approach is clean and avoids the shallow copy issues present in
word_break_dp. The backwards iteration and sentence construction logic are correct.algorithms/dynamic_programming/word_break/README.md (2)
1-26: LGTM!The problem statement, constraints, and topics are clearly presented and comprehensive.
27-233: Comprehensive documentation with multiple approaches.The documentation effectively covers naive, backtracking, and dynamic programming approaches with detailed explanations and complexity analyses. The step-by-step algorithm descriptions and solution summaries are particularly helpful.
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Actionable comments posted: 1
♻️ Duplicate comments (3)
algorithms/dynamic_programming/word_break/__init__.py (3)
39-41: Case sensitivity issue already flagged in previous review.The past review correctly identified that line 40 doesn't lowercase the character before calculating the index, which is inconsistent with
AlphabetTrie.insert(). While the problem constraints guarantee lowercase input, this should still be fixed for robustness.
87-87: Shallow copy issue already flagged in previous review.The past review correctly identified the shallow copy pattern. While the current code avoids bugs by reassigning each element, this pattern is fragile and should be replaced with a list comprehension for safety.
235-256: Parameter encapsulation issue already flagged in previous review.The past review correctly identified that the
backtrackfunction declares asentenceparameter but references the outer scope variableson line 249. This breaks encapsulation and should be fixed by using thesentenceparameter for the substring operation.
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📒 Files selected for processing (3)
algorithms/dynamic_programming/word_break/README.md(1 hunks)algorithms/dynamic_programming/word_break/__init__.py(1 hunks)algorithms/dynamic_programming/word_break/test_word_break.py(1 hunks)
🚧 Files skipped from review as they are similar to previous changes (1)
- algorithms/dynamic_programming/word_break/test_word_break.py
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algorithms/dynamic_programming/word_break/__init__.py (1)
datastructures/trees/trie/alphabet_trie/alphabet_trie.py (1)
AlphabetTrie(4-15)
🪛 LanguageTool
algorithms/dynamic_programming/word_break/README.md
[style] ~45-~45: ‘whether or not’ might be wordy. Consider a shorter alternative.
Context: ... every word of the dictionary and check whether or not the string starts with the current ...
(EN_WORDINESS_PREMIUM_WHETHER_OR_NOT)
[style] ~192-~192: Three successive sentences begin with the same word. Consider rewording the sentence or use a thesaurus to find a synonym.
Context: ...the dp table equal to the temp array. - We repeat the steps above for all prefixes...
(ENGLISH_WORD_REPEAT_BEGINNING_RULE)
[grammar] ~391-~391: Ensure spelling is correct
Context: ...t = ["a", "aa", "aaa", "aaaa", "aaaaa", "aaaaa"]. Every possible partition is a valid ...
(QB_NEW_EN_ORTHOGRAPHY_ERROR_IDS_1)
🔇 Additional comments (2)
algorithms/dynamic_programming/word_break/__init__.py (2)
115-160: LGTM!This implementation uses a dictionary-based DP approach that avoids the shallow copy issue present in
word_break_dp_tabulation. The logic correctly iterates backwards, validates substrings, and accumulates sentences.
163-216: LGTM!The memoization approach correctly caches results by substring to avoid recomputation. The logic handles the base case and recursive construction properly. Line 209's f-string expression is complex but functions correctly.
Describe your change:
Implements dynamic programming techniques using memoization and tabulation as well as backtracking and using a trie to solve the word break algorithm challenge.
Checklist:
Fixes: #{$ISSUE_NO}.Summary by CodeRabbit
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