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@pertrai1 pertrai1 commented Dec 24, 2025

Summary by CodeRabbit

  • New Features

    • Added Deep Clone utility to the JavaScript Utilities collection.
    • Progress updated to 5/75 completed problems.
  • Documentation

    • Added comprehensive documentation for the Deep Clone problem and deepClone function implementation.
  • Tests

    • Added test suite for the deepClone function covering primitives, objects, and nested structures.

✏️ Tip: You can customize this high-level summary in your review settings.

@pertrai1 pertrai1 requested a review from Copilot December 24, 2025 22:08
@pertrai1 pertrai1 added the code challenge this is a coding challenge label Dec 24, 2025
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coderabbitai bot commented Dec 24, 2025

📝 Walkthrough

Walkthrough

A new Deep Clone utility function is added to the GFE75 JavaScript Utilities collection, advancing progress from 4/75 to 5/75 completed problems. The addition includes TypeScript implementation, unit tests, and documentation. Progress tracking across multiple README files has been updated accordingly.

Changes

Cohort / File(s) Summary
Documentation & Progress Updates
README.md, greatfrontend/README.md, greatfrontend/gfe-75/README.md, greatfrontend/gfe-75/javascript-utilities/README.md
Updated progress counters from 4/75 to 5/75. Reformatted section headers in gfe-75 README by removing problem-count suffixes (e.g., removed "(2/20)" from "JavaScript Utilities"). Moved Deep Clone from To Do to Completed. Removed Progress section from greatfrontend root README.
Deep Clone Feature
greatfrontend/gfe-75/javascript-utilities/deep-clone/deep-clone.ts, greatfrontend/gfe-75/javascript-utilities/deep-clone/deep-clone.test.ts, greatfrontend/gfe-75/javascript-utilities/deep-clone/README.md
New generic deepClone function recursively cloning primitives, arrays, and plain objects using Object.entries/Object.fromEntries. Includes unit tests validating primitive values, object cloning, and nested structures without shared references. Adds documentation with usage examples and assumed constraints.

Estimated code review effort

🎯 3 (Moderate) | ⏱️ ~22 minutes

Poem

🐰 A deep clone hops into the fold,
No shared refs, just copies bold,
From nested arrays to objects spun,
Five-seventy-five—another one done! ✨

Pre-merge checks and finishing touches

❌ Failed checks (1 warning)
Check name Status Explanation Resolution
Docstring Coverage ⚠️ Warning Docstring coverage is 0.00% which is insufficient. The required threshold is 80.00%. You can run @coderabbitai generate docstrings to improve docstring coverage.
✅ Passed checks (2 passed)
Check name Status Explanation
Description Check ✅ Passed Check skipped - CodeRabbit’s high-level summary is enabled.
Title check ✅ Passed The title accurately summarizes the main change: adding the GFE Deep Clone problem implementation with supporting documentation, tests, and progress updates.
✨ 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 gfe-12242025

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github-actions bot commented Dec 24, 2025

Claude finished @pertrai1's task in 1m 9s —— View job


Code Review Complete ✅

I've reviewed the GreatFrontEnd Deep Clone solution. Here's my comprehensive feedback:


1. Correctness ✅

The solution correctly implements deep cloning for JSON-serializable values. The logic handles:

  • ✅ Primitives (strings, numbers, booleans)
  • null values
  • ✅ Arrays (with nested values)
  • ✅ Objects (with nested properties)

However, there are critical edge cases missing:

Missing Edge Cases

The current implementation doesn't handle several important scenarios:

  1. Circular References - Would cause infinite recursion:
const obj = { a: 1 };
obj.self = obj;
deepClone(obj); // Stack overflow!
  1. Empty Objects and Arrays - Should work but worth testing:
deepClone({})  // Should return {}
deepClone([])  // Should return []
  1. Non-enumerable Properties - Currently ignored (this may be intentional for JSON-serializable constraint)

  2. Prototype Chain - Lost during cloning (expected for plain objects, but worth documenting)


2. Complexity Analysis

Time Complexity: O(n) where n is the total number of values (primitives + objects + arrays) in the entire nested structure. Every value is visited exactly once.

Space Complexity: O(d + n) where:

  • d is the maximum depth of nesting (recursion call stack)
  • n is the total size of the cloned structure

Why: Each recursive call adds a frame to the call stack (depth), and we create a complete copy of all values (size).


3. Code Quality

Strengths:

  • ✅ Clean, readable implementation
  • ✅ Good use of modern ES6+ features (map, Object.entries, Object.fromEntries)
  • ✅ Proper TypeScript generic typing with <T>
  • ✅ Correct use of const throughout

Suggestions:

Add inline comments for clarity (greatfrontend/gfe-75/javascript-utilities/deep-clone/deep-clone.ts:1-11):

export function deepClone<T>(value: T): T {
  // Base case: primitives and null are returned as-is
  if (typeof value !== 'object' || value === null) {
    return value;
  }
  
  // Handle arrays by recursively cloning each element
  if (Array.isArray(value)) {
    return value.map((val) => deepClone(val)) as T;
  }
  
  // Handle objects by recursively cloning each property
  return Object.fromEntries(
    Object.entries(value).map(([key, val]) => [key, deepClone(val)])
  ) as T;
}

4. Testing Considerations

The test suite covers basic scenarios but is missing important cases:

Missing Test Cases:

// Empty structures
it('empty objects and arrays', () => {
  expect(deepClone({})).toEqual({});
  expect(deepClone([])).toEqual([]);
});

// Null values
it('null values', () => {
  expect(deepClone(null)).toBeNull();
  expect(deepClone({ a: null })).toEqual({ a: null });
});

// Arrays of primitives
it('arrays of primitives', () => {
  const arr = [1, 2, 3];
  const cloned = deepClone(arr);
  cloned[0] = 999;
  expect(arr[0]).toBe(1);
});

// Mixed nested structures
it('arrays containing objects', () => {
  const data = [{ id: 1 }, { id: 2 }];
  const cloned = deepClone(data);
  cloned[0].id = 999;
  expect(data[0].id).toBe(1);
});

5. Learning Summary

Pattern: Recursive Traversal with Type Checking

This solution uses a fundamental pattern in JavaScript: recursive tree traversal with runtime type checking. This pattern appears frequently in:

  • Tree/graph algorithms
  • Data transformation utilities
  • Serialization/deserialization logic

Key Insight 🔑

The key insight is recognizing that deep cloning is a tree traversal problem. Each object/array is a node, and properties/elements are children. By recursively traversing and rebuilding the structure, we create an independent copy.

The type checking order matters:

  1. Check for non-objects first (base case)
  2. Check for arrays (they're objects but need special handling)
  3. Handle plain objects last

Why This Approach Works

  • Recursion naturally handles arbitrary depth - No need to manually track nesting levels
  • Type checking ensures correct handling - Arrays get mapped, objects get entry-transformed
  • Immutability preserved - We create new structures rather than modifying existing ones

Related Problems for Practice

  1. Lodash _.cloneDeep (implement with circular reference handling)

    • Same pattern but with WeakMap to track visited objects
    • Handles edge cases like Date, RegExp, Map, Set
  2. Serialize and Deserialize Binary Tree (LeetCode #297)

    • Similar recursive traversal concept
    • Practice converting tree structures
  3. Copy List with Random Pointer (LeetCode Active Recall Session: Architecture — This #138)

    • Deep cloning with complex references
    • Requires handling non-tree structures

Alternative Approaches

Approach 1: JSON.parse(JSON.stringify()) ⚡ Fastest for simple cases

const deepClone = <T>(value: T): T => JSON.parse(JSON.stringify(value));
  • ✅ One-liner, very fast
  • ❌ Loses functions, undefined, symbols
  • ❌ Fails on circular references
  • ❌ Can't handle Date, RegExp, etc.

Approach 2: structuredClone() (Modern Web API)

const deepClone = <T>(value: T): T => structuredClone(value);
  • ✅ Handles more types (Date, Map, Set, etc.)
  • ✅ Handles circular references
  • ✅ Browser native, very efficient
  • ❌ Not available in older browsers
  • ❌ Won't work in all Node.js versions

Your recursive approach offers the best balance for:

  • Educational purposes (shows the algorithm)
  • Customizability (easy to extend)
  • Understanding what's happening under the hood

Common Mistakes to Avoid

  1. Forgetting the null check - typeof null === 'object' in JavaScript! Always check value === null explicitly.

  2. Not handling arrays separately - Arrays are objects, but Object.fromEntries won't preserve array behavior.

  3. Shallow copying by accident - Using spread operator {...obj} or Object.assign() only copies one level.

  4. Ignoring circular references - In production code, always handle this to avoid stack overflow.


Overall Assessment

Strong foundation! The solution demonstrates understanding of:

  • Recursion
  • JavaScript type system
  • Modern array/object methods
  • TypeScript generics

For production use, you'd want to add:

  • Circular reference handling (WeakMap to track visited objects)
  • More comprehensive tests
  • Performance optimizations for large structures

For learning purposes, this is an excellent clean implementation that clearly shows the recursive pattern. Consider adding the missing test cases to strengthen your understanding of edge cases.


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github-actions bot commented Dec 24, 2025

🧮 Solution Analysis

PR: GFE Deep Clone Problem
Files Changed: greatfrontend/gfe-75/javascript-utilities/deep-clone/deep-clone.test.ts greatfrontend/gfe-75/javascript-utilities/deep-clone/deep-clone.ts

📊 Code Quality Results

ESLint Analysis

  • Errors: 0
  • Warnings: 0

🔍 Complexity Analysis

deep-clone

📋 Analysis Results:

🔍 Automated Complexity Analysis

⚠️ Disclaimer: This is an automated analysis that may not be 100% accurate.
Always verify the complexity analysis manually, especially for complex algorithms.
Dynamic Programming, recursive, and mathematical algorithms may need manual review.

File: greatfrontend/gfe-75/javascript-utilities/deep-clone/deep-clone.ts
Generated: 2025-12-24T22:08:51.409Z

Time Complexity

Estimated: O(n)
Description: Linear time - single pass through data or DP table construction
Confidence: 66.7%

⚠️ Low Confidence: Please manually verify this analysis.
💡 Tip: Add // @complexity: O(n) time, O(1) space to override automated detection.

Space Complexity

Estimated: O(1)
Reason: Constant extra space

Data Structures Used

  • Array: [key, val]
    • access: O(1)
    • search: O(n)
    • insertion: O(1) amortized
    • deletion: O(n)

Code Metrics

  • Lines of Code: 11
  • Cyclomatic Complexity: 3
  • Max Nesting Level: 2

Recommendations

  • VERIFICATION: ⚠️ Manual Review Needed: Low confidence score suggests manual verification is required

deep-clone.test

📋 Analysis Results:

🔍 Automated Complexity Analysis

⚠️ Disclaimer: This is an automated analysis that may not be 100% accurate.
Always verify the complexity analysis manually, especially for complex algorithms.
Dynamic Programming, recursive, and mathematical algorithms may need manual review.

File: greatfrontend/gfe-75/javascript-utilities/deep-clone/deep-clone.test.ts
Generated: 2025-12-24T22:08:51.372Z

Time Complexity

Estimated: Unknown
Description: N/A
Confidence: 0.0%

⚠️ Low Confidence: Please manually verify this analysis.
💡 Tip: Add // @complexity: O(n) time, O(1) space to override automated detection.

Space Complexity

Estimated: O(1)
Reason: Constant extra space

Code Metrics

  • Lines of Code: 20
  • Cyclomatic Complexity: 1
  • Max Nesting Level: 4

Recommendations

  • VERIFICATION: ⚠️ Manual Review Needed: Low confidence score suggests manual verification is required

💡 Analysis Tips

  • Time Complexity: Focus on the dominant operation in loops
  • Space Complexity: Consider auxiliary data structures
  • Optimization: Look for opportunities to improve efficiency
  • Edge Cases: Ensure your solution handles empty inputs, null/undefined, edge conditions

📁 Analysis Files Created

Detailed analysis files have been automatically generated and committed to docs/analysis/ for future reference.

🎯 Next Steps

  1. Review any ESLint errors/warnings above
  2. Consider the complexity analysis - is this the optimal approach?
  3. Test with edge cases mentioned in the problem description
  4. Add comments explaining complex logic
  5. Check the docs/analysis/ directory for detailed complexity analysis files

Analysis generated for PR files only

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✅ Test Results

Tests have been executed for this pull request.

📊 Coverage Summary

Metric Coverage
Statements 92.95%
Branches 87.39%
Functions 80.64%
Lines 93.11%

Check the workflow logs for detailed test output.

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🤖 Gemini Code Review (Model: gemini-2.5-flash)

Code Review: Deep Clone

1. Pattern Identification

This solution primarily uses the Recursion pattern. Specifically, it employs a technique often called Structural Recursion or Deep Traversal. The algorithm recursively visits each nested object and array, making a new copy of each element or property value.

2. Complexity Verification

  • Time Complexity: O(N), where N is the total number of elements and properties in the input object/array.
    • Verification: The algorithm iterates through each element of an array (using map) or each property of an object (using Object.entries and map). For each element/property, it performs a constant number of operations (type checking, creating new array/object entries) and a recursive call. Since each node in the object graph (primitive value, array, or object) is visited and processed exactly once, the total time complexity is proportional to the number of nodes.
  • Space Complexity: O(N) for the new cloned object/array, and O(D) for the recursion call stack, where D is the maximum depth of the nested structure.
    • Verification: A completely new object graph is constructed, which in the worst case (e.g., an array containing N elements, or an object with N properties) will take O(N) space. Additionally, each recursive call adds a frame to the call stack. The maximum depth of this stack corresponds to the deepest nesting level of objects or arrays. If D is the maximum depth, the stack space is O(D). Since D can be at most N (e.g., a linked list like object { a: { b: ... } }), the dominant factor is O(N).

3. Key Insight

The key insight for a deep clone is to distinguish between primitive values and complex objects/arrays, and to handle complex types by recursively cloning their contents rather than just copying their references.

  1. Primitives are copied by value: If the current value is a primitive (number, string, boolean, undefined, symbol, bigint) or null, it can be returned directly because primitives are immutable and copying them creates a distinct value.
  2. Objects and arrays require recursive cloning: If the value is a complex type (an object or an array), a new container (a new array or a new plain object) must be created. Then, each of its members (elements for arrays, key-value pairs for objects) must be recursively deep-cloned and assigned to the new container. This ensures that nested objects/arrays also have their own independent copies.
  3. Arrays vs. Plain Objects: JavaScript treats arrays as a special type of object. It's crucial to differentiate them (Array.isArray(value)) because they require different iteration mechanisms (.map() for arrays, Object.entries() and Object.fromEntries() for plain objects).

4. Edge Case Analysis

The problem statement provides a crucial constraint: "You can assume the input only contains JSON-serializable values (null, boolean, number, string, Array, Object) and will not contain any other objects like Date, Regex, Map or Set." This simplifies the problem significantly.

Given these constraints, the current solution correctly handles:

  • Primitive values: null, boolean, number, string (returned directly).
  • Empty objects {}: Object.entries({}) returns [], Object.fromEntries([]) correctly returns {}.
  • Empty arrays []: [].map(...) correctly returns [].
  • Nested objects and arrays: Handled correctly by recursion.

Edge cases not handled (but explicitly excluded by problem statement):

  • Circular references: If an object contains a reference to itself or an ancestor in its property chain (e.g., obj.self = obj), the current recursive approach would lead to an infinite loop and a stack overflow. A robust deep clone typically requires tracking visited objects (e.g., using a WeakMap or Map) to prevent this.
  • Special JavaScript objects: Date, RegExp, Map, Set, Function, Error, Promise, Blob, File, DOM nodes, etc. These would require specific handling (e.g., new Date(originalDate) for dates, new RegExp(originalRegExp) for regexes). The problem statement explicitly excludes these, so the current solution is fine.
  • Class instances: Cloning a class instance usually involves creating a new instance and copying its properties, potentially also copying its prototype chain or methods. This is complex and beyond the scope of a basic deep clone.

For the given problem constraints, the solution is robust.

5. Learning Points

  • Similar problems using this pattern:
    • Deep Equal: Comparing two objects/arrays for deep equality.
    • Flatten Nested Array/Object: Transforming a deeply nested structure into a flat one.
    • JSON.parse(JSON.stringify(obj)): A common, albeit limited, shortcut for deep cloning JSON-serializable data. Understanding its limitations (dates, functions, undefined, circular refs) is key.
    • Tree Traversal algorithms (DFS/BFS): While this specific problem uses recursion (a form of DFS), the underlying idea of systematically visiting nodes in a graph/tree structure is fundamental to many problems.
  • Common mistakes people make with this pattern:
    • Confusing shallow copy with deep copy: Accidentally copying references instead of values for nested objects.
    • Not handling null correctly: typeof null is 'object', so it needs an explicit check value === null.
    • Not distinguishing arrays from plain objects: Treating arrays like plain objects (or vice-versa) can lead to incorrect behavior (e.g., Object.entries([1, 2, 3]) would yield [['0', 1], ['1', 2], ['2', 3]]).
    • Forgetting about circular references: A critical oversight in general-purpose deep clone implementations.
    • Ignoring special object types: Assuming all objects are plain objects.
  • Variations of this problem:
    • Deep clone with circular reference handling: Requires a Map or WeakMap to store references to already cloned objects.
    • Deep clone with specific object type handling: Extending the function to clone Date, RegExp, Map, Set, etc.
    • Deep clone with custom cloning logic: Allowing users to provide a custom function for cloning specific types or properties.
    • Structured Clone Algorithm: The algorithm used by browser APIs (like postMessage) which is much more comprehensive and handles a wider range of types and issues.

6. Code Quality

The code quality is good:

  • Clarity: The logic is straightforward and easy to follow.
  • Readability: Variable names (value, key, val) are appropriate for their context.
  • Conciseness: Uses modern JavaScript features (Array.isArray, Object.fromEntries, Object.entries, map) effectively.
  • Type Safety: The use of generics <T> and type assertions as T provides good type inference and safety in TypeScript.

Minor suggestion for robustness/defensive coding (optional, given problem constraints):

While the problem guarantees JSON-serializable inputs, in a real-world scenario, Object.fromEntries could throw an error if Object.entries(value) somehow produced a non-iterable or non-pair array. This is highly unlikely given the typeof value === 'object' check, but it's something to be aware of. For this specific problem, it's perfectly fine.

7. Alternative Approaches

  1. Using JSON.parse(JSON.stringify(value)):

    • Description: This is a very common and concise way to deep clone objects in JavaScript. It serializes the object to a JSON string and then parses it back into a new object.
    • Trade-offs:
      • Pros: Extremely simple to write, leverages built-in browser/runtime optimization, works perfectly for JSON-serializable data (numbers, strings, booleans, null, plain objects, arrays).
      • Cons:
        • Limitations: It cannot handle Date objects (converts them to ISO strings), RegExp, Map, Set, Function, undefined, Infinity, NaN (loses them or converts them to null or string).
        • Circular References: Throws an error if the object contains circular references.
        • Performance: Can be slower than a custom recursive solution for very large or deeply nested objects due to the overhead of string conversion.
    • Applicability: For this specific problem, given the constraints (JSON-serializable only), this approach would technically pass the tests and be the most concise. However, understanding the recursive approach is more fundamental for learning DSA.
  2. Iterative Approach (using a stack/queue):

    • Description: Instead of using recursion, one can implement deep cloning iteratively using a stack (DFS-like) or a queue (BFS-like) to manage the objects/arrays to be processed. This typically involves maintaining a mapping of original objects to their cloned counterparts to handle circular references and avoid re-cloning.
    • Trade-offs:
      • Pros: Avoids potential stack overflow issues with extremely deep recursion (though modern JavaScript engines have good tail-call optimization for some cases, it's not guaranteed for general recursion). Can handle circular references more naturally by checking the map before processing.
      • Cons: More complex and verbose to implement compared to the recursive solution, often less intuitive to read.
    • Applicability: Useful when dealing with extremely deep structures where recursion stack limits might be a concern, or when circular references are expected and need robust handling.

The chosen recursive approach is idiomatic, clean, and perfectly suited for the given problem constraints and learning objectives.

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🤖 Gemini Code Review (Model: gemini-2.5-flash)

This is an excellent problem for understanding recursion and object manipulation in JavaScript. Let's break down your solution.


1. Pattern Identification

This solution primarily uses Recursion for Structural Cloning. It's a classic example of traversing a tree-like data structure (where objects and arrays form the nodes and their properties/elements are children) and creating a new, independent copy of it.


2. Complexity Verification

  • Time Complexity: O(N)

    • Verification: This is accurate. N represents the total number of elements/properties within the input value (including primitives, objects, and arrays).
    • Why:
      • Every primitive value, object, and array element in the input structure is visited exactly once.
      • For each visit:
        • Primitive values are returned in O(1).
        • Arrays use Array.isArray() (O(1)) and map() which iterates through all its elements, performing a recursive call for each.
        • Objects use Object.entries() (which iterates over all keys, O(P) where P is number of properties), map() (iterates over entries, O(P)), and Object.fromEntries() (reconstructs the object, O(P)).
      • Since each node (primitive, object, array) is processed once, and the operations per node are proportional to its immediate children/properties, the total time complexity scales linearly with the total number of items in the structure.
  • Space Complexity: O(N)

    • Verification: This is accurate.
    • Why:
      • Recursion Stack: In the worst-case scenario (e.g., a deeply nested object like { a: { b: { c: ... } } }), the recursion depth D can be proportional to N. Each recursive call adds a frame to the call stack. So, the stack space is O(D).
      • Cloned Object: A completely new copy of the input object is created. This new object will occupy space proportional to the original object's size, which is O(N).
      • Combining these, the total space complexity is O(N + D), which simplifies to O(N) since D is at most N.

3. Key Insight

The key insight for deep cloning is recognizing that non-primitive values (objects and arrays) must be recursively processed to create truly independent copies.

  1. Base Cases: Primitive values (numbers, strings, booleans, null, undefined) are immutable and can be returned directly, as copying them creates a new value.
  2. Recursive Step: For objects and arrays, you cannot simply copy their references. Instead, you must:
    • Create a new empty object or array.
    • Iterate over each of its properties (for objects) or elements (for arrays).
    • For each property/element, recursively call the deepClone function to clone its value.
    • Assign the cloned value to the corresponding key/index in the newly created object/array.

This recursive decomposition allows the function to handle arbitrarily nested structures by breaking them down into simpler, clonable parts.


4. Edge Case Analysis

The problem statement provides a crucial constraint: "You can assume the input only contains JSON-serializable values (null, boolean, number, string, Array, Object) and will not contain any other objects like Date, Regex, Map or Set." This simplifies the problem significantly.

Let's analyze how your solution handles various edge cases within these constraints:

  • Primitive values (null, boolean, number, string):
    • deepClone(null): Returns null. Correct. (value === null)
    • deepClone(123): Returns 123. Correct. (typeof value !== 'object')
    • deepClone("hello"): Returns "hello". Correct. (typeof value !== 'object')
    • deepClone(true): Returns true. Correct. (typeof value !== 'object')
  • Empty objects and arrays:
    • deepClone({}): Object.entries({}) is [], map on [] is [], Object.fromEntries([]) is {}. Correct.
    • deepClone([]): Array.isArray([]) is true, [].map(...) is []. Correct.
  • Shallow objects/arrays (containing only primitives):
    • deepClone({ a: 1, b: 'foo' }): Correctly clones to { a: 1, b: 'foo' } with new object reference.
    • deepClone([1, 'foo', true]): Correctly clones to [1, 'foo', true] with new array reference.
  • Nested objects/arrays (as per examples):
    • { user: { role: 'admin' } } and { foo: [{ bar: 'baz' }] }: The recursive calls correctly handle these multi-level structures, ensuring all nested objects and arrays are new instances.
  • undefined values:
    • While undefined is not strictly JSON-serializable (JSON.stringify omits undefined properties), if it were a direct input deepClone(undefined) would return undefined.
    • If undefined is a value in an object property (e.g., { a: 1, b: undefined }), Object.entries will typically omit properties with undefined values, leading to { a: 1 } as the cloned output. This behavior is consistent with JSON.stringify and the JSON-serializable constraint.

Edge Cases Not Handled (and why it's acceptable here):

  • Circular References: Your current solution does not handle circular references (e.g., obj.self = obj). If such an object were passed, it would lead to an infinite recursion and a stack overflow.
    • Why it's acceptable: The problem statement explicitly implies JSON-serializable values, and JSON itself does not support circular references (JSON.stringify throws an error). Therefore, within the given constraints, this is not a correctness issue. If the constraints were relaxed, this would be a critical bug.
  • Non-JSON-serializable types (Date, RegExp, Map, Set, Function, Symbol, Class instances): Your solution would either return them by reference (if they are typeof 'object' but not null or Array) or return them directly (if they are typeof 'function' or typeof 'symbol').
    • Why it's acceptable: Again, the problem statement explicitly excludes these types.

5. Learning Points

  • Similar problems using this same pattern:

    • JSON.parse(JSON.stringify(obj)): This common JS idiom for deep cloning works for purely JSON-serializable data, implicitly using a similar recursive structural cloning idea. It's a good way to understand the limitations of this specific deep clone implementation.
    • Implementing _.cloneDeep (Lodash): A more comprehensive version of deep clone that handles many more JavaScript types, including Date, RegExp, Function, and crucially, circular references. This problem is a simplified stepping stone to understanding such robust implementations.
    • Tree Traversal Algorithms: Any problem that requires visiting every node in a tree or graph-like structure (e.g., calculating sum of values, finding maximum depth, serializing/deserializing a binary tree, copying a linked list with random pointers).
    • Immutable Data Structures: Problems involving creating new versions of data structures without modifying the originals often rely on deep copying techniques.
  • Common mistakes people make with this pattern:

    1. Shallow Copying: A very frequent mistake is to use techniques like Object.assign({}, obj) or the spread operator {...obj} or [...arr] expecting a deep copy. These only create new instances at the top level; nested objects/arrays still share references with the original.
    2. Forgetting null check: typeof null is 'object', so a common bug is to only check typeof value === 'object' without explicitly checking value === null. This would cause Object.entries(null) to throw an error. Your solution correctly handles this.
    3. Handling Arrays and Objects identically: While some generic iteration might work, it's generally best practice and clearer to distinguish between arrays (Array.isArray) and plain objects, as their construction (.map vs Object.fromEntries) is different.
    4. Infinite Recursion with Circular References: This is the most challenging aspect of deep cloning. Without a mechanism to track already-cloned objects (like a Map or WeakMap), circular references will cause a stack overflow. This problem cleverly sidesteps this by constraint.
  • Variations of this problem:

    • Deep clone with specific type handling: Extend the function to correctly clone Date objects (create a new Date instance), RegExp (create a new RegExp), Map/Set (iterate and add elements), Function (often returned by reference or skipped), etc.
    • Deep clone with circular reference handling: Implement a mechanism (e.g., a WeakMap or Map) to store originalObject -> clonedObject mappings during traversal. If an object is encountered that's already in the map, return its cloned version instead of recursing, thus breaking the cycle.
    • Iterative Deep Clone: Instead of recursion, implement the traversal using an explicit stack or queue. This avoids potential stack overflow issues for extremely deep objects, though it's typically more complex to write.

6. Code Quality

Your code is very clean, concise, and idiomatic for TypeScript/JavaScript.

  • Variable Naming: value, val, key are standard and clear in this context. T for the generic type parameter is also standard.
  • Code Structure: The if/else if/else structure is logical and easy to follow, handling base cases first, then arrays, then objects.
  • Readability: The use of Array.isArray().map() for arrays and Object.entries().map().Object.fromEntries() for objects is modern, concise, and highly readable.
  • Type Annotations: Using <T>(value: T): T provides good type inference and safety. The as T casts are sometimes necessary for TypeScript to correctly infer the return type of recursive functions or Object.fromEntries when generics are involved.

Suggestions for Improvement (Minor):

  1. JSDoc Comments: Adding JSDoc comments would enhance clarity, especially for a utility function that might be used by others or revisited later. It clearly states assumptions and limitations.

    /**
     * Performs a deep clone operation on JavaScript objects and arrays.
     * Assumes input only contains JSON-serializable values (null, boolean, number, string, Array, Object).
     * Does NOT handle circular references (will cause stack overflow), Date, Regex, Map, Set, Function, or undefined as object properties.
     *
     * @template T The type of the value to clone.
     * @param {T} value The value to deep clone.
     * @returns {T} A deep copy of the input value.
     */
    export function deepClone<T>(value: T): T {
        // ...
    }

7. Alternative Approaches

  1. Using JSON.parse(JSON.stringify(value)):

    • Description: This is a common JavaScript "hack" for deep cloning. It serializes the object to a JSON string and then parses it back into a new JavaScript object.
    • Trade-offs:
      • Pros: Extremely concise, easy to write, and often sufficient for simple, purely JSON-serializable data.
      • Cons:
        • Limitations: It has significant limitations. It cannot handle undefined, Function, Date, RegExp, Map, Set, Symbol, or circular references. undefined values in objects are silently dropped. Date objects are converted to ISO strings. RegExp objects become empty objects {}.
        • Performance: Can be slower than a custom recursive solution for very large objects due to the overhead of string conversion and parsing.
        • Error Handling: Throws an error for circular references.
    • Applicability: Only suitable when you are absolutely certain that the data strictly adheres to JSON format and these limitations are acceptable. Given the problem's constraints, it would technically pass, but it's not the "algorithmic" solution.
  2. Iterative Approach with a Stack/Queue and a Map for Cycles:

    • Description: Instead of using the call stack for recursion, you can implement the traversal iteratively using an explicit stack (for DFS-like traversal) or a queue (for BFS-like traversal). To handle circular references, you would use a WeakMap (or Map) to keep track of originalObject -> clonedObject mappings as you process them.
    • Trade-offs:
      • Pros:
        • No Recursion Stack Limit: Avoids potential stack overflow issues for extremely deeply nested objects.
        • Circular Reference Handling: This pattern is naturally suited for implementing robust circular reference detection and handling by storing visited objects and their clones.
      • Cons:
        • More Complex: Significantly more complex to implement compared to the recursive approach. Requires explicit management of the stack/queue and the Map for visited objects.
    • Applicability: This approach is preferred for highly robust deep cloning utilities (like Lodash's cloneDeep) where objects can be arbitrarily deep, contain various types, and potentially have circular references. It would be the next step if the problem constraints were relaxed.

Your chosen recursive solution is the most elegant and efficient for the problem as stated, given its constraints.

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Pull request overview

This PR adds a solution for the "Deep Clone" problem from GreatFrontEnd's GFE 75 collection. The implementation provides a TypeScript function that recursively clones JavaScript objects and arrays, handling JSON-serializable values while excluding special objects like Date, Regex, Map, or Set.

Key changes:

  • Implements a recursive deepClone function that handles primitives, arrays, and objects
  • Adds basic test coverage for primitive values, objects, and nested objects
  • Updates progress trackers across README files to reflect the completion of 5/75 problems

Reviewed changes

Copilot reviewed 7 out of 7 changed files in this pull request and generated 4 comments.

Show a summary per file
File Description
greatfrontend/gfe-75/javascript-utilities/deep-clone/deep-clone.ts Core implementation using recursion with Array.isArray check and Object.entries/fromEntries for cloning
greatfrontend/gfe-75/javascript-utilities/deep-clone/deep-clone.test.ts Basic test suite covering primitives, objects, and nested objects
greatfrontend/gfe-75/javascript-utilities/deep-clone/README.md Problem description with examples and constraints
greatfrontend/gfe-75/javascript-utilities/README.md Moves Deep Clone from To Do to completed section
greatfrontend/gfe-75/README.md Updates progress counter from 4/75 to 5/75
greatfrontend/README.md Removes progress section (simplification)
README.md Updates GreatFrontEnd count from 7 to 8 and GFE 75 from 4/75 to 5/75

Comment on lines +4 to +23
describe('deepClone', () => {
it('primitive values', () => {
expect(deepClone('foo')).toEqual('foo');
expect(deepClone(123)).toEqual(123);
});

it('objects', () => {
const obj = { role: 'foo' };
const clonedObj = deepClone(obj);
clonedObj.role = 'bar';
expect(obj).toEqual({ role: 'foo' });
});

it('nested objects', () => {
const obj = { user: { role: 'admin', id: '123' } };
const clonedObj = deepClone(obj);
clonedObj.user.role = 'bar';
expect(obj).toEqual({ user: { role: 'admin', id: '123' } });
});
});
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The current implementation doesn't handle arrays within the test cases. While the implementation correctly handles arrays, there are no tests that verify arrays are deep cloned. Consider adding a test case for arrays, such as:

  • Simple array cloning
  • Nested arrays
  • Arrays containing objects
  • Mixed arrays with primitives and objects

This would ensure the array handling in line 5-6 of the implementation is properly tested.

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Comment on lines +5 to +8
it('primitive values', () => {
expect(deepClone('foo')).toEqual('foo');
expect(deepClone(123)).toEqual(123);
});
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The test suite is missing coverage for null values. The implementation specifically handles null in line 2 of deep-clone.ts, but there's no test verifying that deepClone(null) returns null correctly. Add a test case to verify null handling.

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Comment on lines +10 to +15
it('objects', () => {
const obj = { role: 'foo' };
const clonedObj = deepClone(obj);
clonedObj.role = 'bar';
expect(obj).toEqual({ role: 'foo' });
});
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Tests should verify that the cloned object is not the same reference as the original. While the current tests check that modifying the clone doesn't affect the original (which is good), they don't explicitly verify that the references are different. Consider adding assertions like expect(clonedObj).not.toBe(obj) to make this explicit.

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Comment on lines +5 to +8
it('primitive values', () => {
expect(deepClone('foo')).toEqual('foo');
expect(deepClone(123)).toEqual(123);
});
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Missing test coverage for boolean primitive values. The README examples mention that the function should handle boolean values, but the primitive values test only covers strings and numbers. Add a test case for boolean values (true/false).

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Actionable comments posted: 0

🧹 Nitpick comments (1)
greatfrontend/gfe-75/javascript-utilities/deep-clone/deep-clone.test.ts (1)

4-23: Expand test coverage for additional JSON-serializable types.

The current tests cover primitives (string, number), objects, and nested objects well. However, several JSON-serializable types mentioned in the requirements are not tested:

  • Arrays (standalone and nested)
  • null and undefined
  • Booleans
  • Empty objects and arrays
  • Mixed structures (objects containing arrays, arrays containing objects)

The README examples specifically demonstrate array handling, which should be tested.

🔎 Suggested additional test cases
+  it('null and undefined', () => {
+    expect(deepClone(null)).toBeNull();
+    expect(deepClone(undefined)).toBeUndefined();
+  });
+
+  it('boolean values', () => {
+    expect(deepClone(true)).toBe(true);
+    expect(deepClone(false)).toBe(false);
+  });
+
+  it('arrays', () => {
+    const arr = [1, 2, 3];
+    const clonedArr = deepClone(arr);
+    clonedArr.push(4);
+    expect(arr).toEqual([1, 2, 3]);
+    expect(clonedArr).toEqual([1, 2, 3, 4]);
+  });
+
+  it('nested arrays and objects', () => {
+    const obj = { foo: [{ bar: 'baz' }] };
+    const clonedObj = deepClone(obj);
+    clonedObj.foo[0].bar = 'qux';
+    expect(obj.foo[0].bar).toBe('baz');
+  });
+
+  it('empty structures', () => {
+    expect(deepClone({})).toEqual({});
+    expect(deepClone([])).toEqual([]);
+  });

Based on learnings, comprehensive test coverage helps verify parameter validation and edge case handling.

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Reviewing files that changed from the base of the PR and between d6c9a54 and 06940e3.

📒 Files selected for processing (7)
  • README.md
  • greatfrontend/README.md
  • greatfrontend/gfe-75/README.md
  • greatfrontend/gfe-75/javascript-utilities/README.md
  • greatfrontend/gfe-75/javascript-utilities/deep-clone/README.md
  • greatfrontend/gfe-75/javascript-utilities/deep-clone/deep-clone.test.ts
  • greatfrontend/gfe-75/javascript-utilities/deep-clone/deep-clone.ts
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  • greatfrontend/README.md
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**/*.ts

📄 CodeRabbit inference engine (AGENTS.md)

**/*.ts: Use explicit type annotations for function parameters and return types in TypeScript solutions
Follow strict TypeScript configuration with ES2020 target and CommonJS modules in TypeScript solutions
Enforce full type safety in TypeScript solutions

Files:

  • greatfrontend/gfe-75/javascript-utilities/deep-clone/deep-clone.ts
  • greatfrontend/gfe-75/javascript-utilities/deep-clone/deep-clone.test.ts
**/*.{js,ts}

📄 CodeRabbit inference engine (AGENTS.md)

**/*.{js,ts}: Use clear, descriptive variable names across all solutions
Add comments for non-obvious logic or algorithm steps in code
Keep functions focused and single-purpose across all solutions
Prefer readability over cleverness in code implementation

**/*.{js,ts}: Use descriptive variable names; single letters like i, j, k are acceptable for loop iterators and standard mathematical contexts
Add comments for complex logic, but prefer self-documenting code with clear logic
Minimize external dependencies and keep solutions self-contained

**/*.{js,ts}: Use clear, descriptive variable names (not just i, j, k unless in simple loops) and add comments for non-obvious logic or algorithm steps
Keep functions focused and single-purpose, preferring readability over cleverness
Use const by default, let only when reassignment needed; avoid var except for LeetCode solution function definitions
Use modern ES6+ syntax (arrow functions, destructuring, spread operators) where appropriate
Prefer built-in methods (.map(), .filter(), .reduce()) when appropriate and use strict equality (===) over loose equality (==)

Files:

  • greatfrontend/gfe-75/javascript-utilities/deep-clone/deep-clone.ts
  • greatfrontend/gfe-75/javascript-utilities/deep-clone/deep-clone.test.ts
**/*.{ts,tsx}

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**/*.{ts,tsx}: Use explicit type annotations for function parameters and return types in TypeScript
Follow strict TypeScript configuration as defined in tsconfig.json with ES2020 target and CommonJS modules

Files:

  • greatfrontend/gfe-75/javascript-utilities/deep-clone/deep-clone.ts
  • greatfrontend/gfe-75/javascript-utilities/deep-clone/deep-clone.test.ts
**/*.md

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**/*.md: Create comprehensive documentation guides for arrays, trees, graphs, heaps, and other data structures
Document reusable code templates for common algorithmic patterns
Maintain Big O complexity cheatsheets and references

Files:

  • README.md
  • greatfrontend/gfe-75/javascript-utilities/deep-clone/README.md
  • greatfrontend/gfe-75/README.md
  • greatfrontend/gfe-75/javascript-utilities/README.md
**/README.md

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Each problem directory should include a README.md containing: problem title and difficulty badge, link to the problem on the respective platform, problem description, examples and constraints

Files:

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  • greatfrontend/gfe-75/javascript-utilities/deep-clone/README.md
  • greatfrontend/gfe-75/README.md
  • greatfrontend/gfe-75/javascript-utilities/README.md
🧠 Learnings (6)
📚 Learning: 2025-12-02T17:56:01.747Z
Learnt from: CR
Repo: pertrai1/coding-challenges PR: 0
File: CLAUDE.md:0-0
Timestamp: 2025-12-02T17:56:01.747Z
Learning: Applies to GreatFrontEnd/**/*.{js,ts} : Evaluate the public API for clarity and usability, check for consistent naming conventions, verify parameter validation and error handling in GreatFrontEnd solutions

Applied to files:

  • README.md
  • greatfrontend/gfe-75/README.md
  • greatfrontend/gfe-75/javascript-utilities/README.md
📚 Learning: 2025-12-02T17:56:01.747Z
Learnt from: CR
Repo: pertrai1/coding-challenges PR: 0
File: CLAUDE.md:0-0
Timestamp: 2025-12-02T17:56:01.747Z
Learning: Applies to GreatFrontEnd/**/*.{js,ts} : Check for unnecessary re-renders or DOM manipulations, verify efficient data structure usage for UI updates in GreatFrontEnd solutions

Applied to files:

  • greatfrontend/gfe-75/README.md
  • greatfrontend/gfe-75/javascript-utilities/README.md
📚 Learning: 2025-12-02T17:56:01.747Z
Learnt from: CR
Repo: pertrai1/coding-challenges PR: 0
File: CLAUDE.md:0-0
Timestamp: 2025-12-02T17:56:01.747Z
Learning: Applies to GreatFrontEnd/**/*.{js,ts} : Look for debouncing/throttling where appropriate and consider memory leaks (event listeners, timers, closures) in GreatFrontEnd solutions

Applied to files:

  • greatfrontend/gfe-75/javascript-utilities/README.md
📚 Learning: 2025-12-02T17:56:01.747Z
Learnt from: CR
Repo: pertrai1/coding-challenges PR: 0
File: CLAUDE.md:0-0
Timestamp: 2025-12-02T17:56:01.747Z
Learning: Applies to **/*.{js,ts} : Prefer built-in methods (.map(), .filter(), .reduce()) when appropriate and use strict equality (===) over loose equality (==)

Applied to files:

  • greatfrontend/gfe-75/javascript-utilities/README.md
📚 Learning: 2025-11-26T14:46:46.097Z
Learnt from: CR
Repo: pertrai1/coding-challenges PR: 0
File: .github/copilot-instructions.md:0-0
Timestamp: 2025-11-26T14:46:46.097Z
Learning: Applies to [0-9]*-*/*.{js,ts} : Use standard algorithmic patterns (two pointers, sliding window, hash maps, DFS, BFS, DP) and leverage appropriate data structures (Map, Set, arrays)

Applied to files:

  • greatfrontend/gfe-75/javascript-utilities/README.md
📚 Learning: 2025-11-24T23:55:10.338Z
Learnt from: CR
Repo: pertrai1/coding-challenges PR: 0
File: AGENTS.md:0-0
Timestamp: 2025-11-24T23:55:10.338Z
Learning: Applies to **/*.js : Keep JavaScript solutions concise and focused on the algorithm

Applied to files:

  • greatfrontend/gfe-75/javascript-utilities/README.md
🪛 LanguageTool
greatfrontend/gfe-75/javascript-utilities/deep-clone/README.md

[style] ~3-~3: Consider using a different adverb to strengthen your wording.
Context: ... a copy of JavaScript value, leading to a completely new value that has no references pointi...

(COMPLETELY_ENTIRELY)

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🔇 Additional comments (5)
README.md (1)

10-10: LGTM! Progress tracking accurately reflects the new Deep Clone problem.

The updates correctly increment the problem counts across the GreatFrontEnd platform summary.

Also applies to: 46-46

greatfrontend/gfe-75/javascript-utilities/README.md (1)

12-12: LGTM! Deep Clone properly added to completed utilities.

The entry follows the established format and correctly reflects the new implementation.

greatfrontend/gfe-75/javascript-utilities/deep-clone/README.md (1)

1-25: LGTM! Clear and comprehensive documentation.

The documentation effectively explains the deep clone concept, provides practical examples, and sets clear expectations about the input constraints (JSON-serializable values only).

greatfrontend/gfe-75/javascript-utilities/deep-clone/deep-clone.ts (1)

1-11: LGTM! Clean and correct implementation.

The implementation correctly handles all JSON-serializable types as specified in the requirements:

  • Primitives and null (lines 2-4): Properly detected with typeof and null check
  • Arrays (lines 5-7): Correctly identified with Array.isArray() and recursively cloned
  • Objects (lines 8-10): Efficiently cloned using Object.entries and Object.fromEntries pattern with recursion

The function follows TypeScript best practices with explicit type annotations and leverages modern ES6+ features. The generic type parameter T provides good type inference while the as T assertions are necessary and safe given the control flow.

Based on learnings, the public API is clear with a descriptive function name and straightforward parameter signature.

greatfrontend/gfe-75/README.md (1)

7-7: LGTM! Progress tracking and completed items accurately updated.

The GFE 75 progress correctly reflects the new Deep Clone implementation, and the entry is properly placed under JavaScript Utilities with the correct difficulty level and path.

Also applies to: 16-16

@pertrai1 pertrai1 merged commit 5d65055 into main Dec 24, 2025
16 of 17 checks passed
@pertrai1 pertrai1 deleted the gfe-12242025 branch December 24, 2025 22:14
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github-actions bot pushed a commit that referenced this pull request Dec 24, 2025
  Problem: #GFE-69c2 - Deep Clone
  PR: #103
  First review scheduled (subsequent reviews auto-scheduled on completion)

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