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The "Recipe" for Quality Code
(think of it as your favorite cookbook—only instead of flour and sugar we’re mixing readability, maintainability, and reliability.)
| Step | What you do | Why it matters | Quick example |
|---|---|---|---|
| 1. Start with a clear purpose | Write a one‑sentence description or comment that explains why the code exists. | Helps anyone (including future you) instantly see what problem is being solved, saving hours of guesswork. | `// Calculates the tax amount for a given purchase.` |
| 2. Keep functions small & focused | Aim for 1–5 lines per function, or no more than ~50 LOC if it can’t be split further. | Small units are easier to test, debug, and reuse. | ```cpp int add(int a, int b) return a + b; ``` |
| 3. Use meaningful names | Variables, functions, types should describe intent (e.g., `taxRate` vs. `x`). | Reduces the cognitive load when reading code later. | `double tax = purchasePrice taxRate;` |
| 4. Avoid side‑effects where possible | Pure functions return results without modifying global state or I/O. | Predictable behavior simplifies reasoning about programs. | ```cpp int factorial(int n) if (n <= 1) return 1; return n factorial(n-1); ``` |
| 5. Keep functions small | One function should do one thing; no more than a few dozen lines. | Easier to test, reuse, and maintain. | `bool isPrime(int x);` (separate from printing results) |
| 6. Use descriptive names | Variables, parameters, and functions clearly indicate intent. | Reduces the need for comments or external documentation. | `int computeTaxableIncome(const Salary& s);` |
| 7. Prefer const where possible | Immutable objects reduce accidental state changes. | Makes code safer and easier to reason about. | `void printSalary(const Salary& salary) const;` |
| 8. Keep the main function minimal | The entry point should orchestrate, not implement logic. | Simplifies unit testing of components. | `int main() Salary s = getUserInput(); process(s); ` |
2.4 Example: Refactoring a Class
Suppose we have an old class:
class Salary
public:
double salary;
double tax_rate;
double net_salary()
return salary (1 - tax_rate);
;
Refactored version with proper encapsulation and immutability:
class Salary
private:
const double gross_;
const double taxRate_;
public:
Salary(double gross, double taxRate)
: gross_(gross), taxRate_(taxRate) {}
double net() const return gross_ (1.0 - taxRate_);
;
Here:
- The fields are `const`, making the object immutable after construction.
- Getter methods (`net`) provide read-only access.
- No setters; the state cannot change once created.
4. Summary of Key Findings
| Issue | Description | Impact |
|---|---|---|
| Unclear Naming | Method `add` uses ambiguous names (`c`, `d`). | Makes code hard to read and maintain. |
| Null Checks & Exceptions | No validation for null arguments or potential overflow. | Leads to runtime errors in production. |
| Incorrect Exception Type | Throws `NullPointerException` on empty stack. | Misleads developers; should be `IllegalStateException`. |
| Inefficient Data Structures | Using `ArrayList` with frequent inserts at the end and deletions from middle is costly (O(n)). | Poor performance, especially for large stacks. |
| Unnecessary Synchronization | Synchronized methods lock whole object, causing contention. | Reduces concurrency without clear benefit. |
---
4. Suggested Improvements
| Area | Current Issue | Proposed Solution |
|---|---|---|
| Data Structure | `ArrayList` + `HashMap`. | Use a linked list (e.g., `java.util.LinkedList`) or a custom node structure: each element stores its value and pointers to next/prev nodes. |
| Memory Efficiency | 2 arrays of size `maxSize`. | Allocate only what’s needed; use dynamic structures that grow as required. |
| Time Complexity | O(1) for add, but remove is O(log n). | With linked list, removal by value is still O(n); consider maintaining a hash map from values to nodes to achieve O(1) removal. |
| Synchronization | `synchronized` methods. | Use `java.util.concurrent.locks.ReentrantLock` for finer-grained control; or lock-free structures if needed. |
| Size Tracking | Separate `size` field. | Keep a single atomic counter (e.g., `AtomicInteger`) for thread-safe size updates. |
3.2 Suggested Optimizations
- Hash Map of Value to Node:
- Removal becomes O(1) by looking up the node directly, then unlinking it from the doubly linked list.
- Circular Doubly Linked List with Sentinel Head:
- Avoid null checks for https://git.mikspec.pl/ head/tail pointers.
- Atomic Operations for Size:
- Lock-Free Traversal:
- Memory Management:
- In manual memory management environments, ensure proper deallocation of nodes.
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7. Summary
- Node Removal: Deleting a node requires updating its predecessor’s `next` pointer and, if the node is not the tail, its successor’s `prev` pointer (or adjusting the head/tail references).
- Tail Node Handling: When removing the last node, the list becomes empty; update both head and tail to null.
- Complexity: The operation runs in constant time (`O(1)`) because it involves only a few pointer updates.
- Edge Cases: Must handle removal of the sole node, the first node, the last node, or any middle node correctly.
- Memory Management: In languages with manual memory management, free the node after detaching; otherwise rely on garbage collection.
