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Algorithms Education Skills
This skill defines the conventions and standards for an educational algorithms repository. The goal is to make every algorithm implementation clear, well-tested, and accessible to learners who may not have deep CS backgrounds.
Skill 1: Code Documentation
Goal: Every file should teach, not just implement.
Method-Level Documentation
Every public method gets a doc comment that explains:
- What the method does (in plain English, one sentence)
- How it works (brief description of the approach/algorithm)
- Parameters — what each input represents
- Returns — what the output means
- Time/Space complexity — always include Big-O
java1/** 2 * Finds the shortest path from a source node to all other nodes 3 * using Bellman-Ford's algorithm. Unlike Dijkstra's, this handles 4 * negative edge weights and detects negative cycles. 5 * 6 * @param graph - adjacency list where graph[i] lists edges from node i 7 * @param start - the source node index 8 * @param n - total number of nodes in the graph 9 * @return dist array where dist[i] = shortest distance from start to i, 10 * or Double.NEGATIVE_INFINITY if node i is in a negative cycle 11 * 12 * Time: O(V * E) — relaxes all edges V-1 times 13 * Space: O(V) — stores distance array 14 */
Inline Comments on Key Lines
Comment the why, not the what. Focus on lines where the logic isn't obvious:
java1// Relax all edges V-1 times. After V-1 passes, shortest paths 2// are guaranteed if no negative cycles exist. 3for (int i = 0; i < n - 1; i++) { 4 for (Edge e : edges) { 5 if (dist[e.from] + e.cost < dist[e.to]) { 6 dist[e.to] = dist[e.from] + e.cost; 7 } 8 } 9} 10 11// If we can still relax an edge after V-1 passes, that node 12// is reachable from a negative cycle — mark it as -infinity. 13for (int i = 0; i < n - 1; i++) { 14 for (Edge e : edges) { 15 if (dist[e.from] + e.cost < dist[e.to]) { 16 dist[e.to] = Double.NEGATIVE_INFINITY; 17 } 18 } 19}
File-Level Header
Every file starts with a comment block explaining the algorithm in the file
java1/** 2 * Bellman-Ford Shortest Path Algorithm 3 * 4 * Computes single-source shortest paths in a weighted graph. 5 * Handles negative edge weights and detects negative cycles. 6 * 7 * Use cases: 8 * - Graphs with negative weights (where Dijkstra fails) 9 * - Detecting negative cycles (e.g., currency arbitrage) 10 * 11 * Run with: 12 * bazel run //src/main/java/com/williamfiset/algorithms/graphtheory:BellmanFordAdjacencyList 13 * 14 * @see <a href="https://en.wikipedia.org/wiki/Bellman-Ford_algorithm">Wikipedia</a> 15 */
Skill 2: Test Coverage
Goal: Every algorithm has tests that prove it works and teach edge cases.
Test File Structure
Place tests alongside source files or in a tests/ directory. Name test files
to mirror the source: BellmanFord.java → BellmanFordTest.java.
What to Test
For every algorithm, cover these categories:
- Basic/Happy path — typical input, expected output
- Edge cases — empty input, single element, duplicates
- Boundary conditions — max/min values, zero, Integer.MAX_VALUE
- Known tricky inputs — cases that commonly break naive implementations
- Performance sanity check — large input doesn't hang or crash (optional)
Test Naming Convention
Use descriptive names that read like a sentence:
java1@Test 2public void testShortestPathSimpleGraph() { ... } 3 4@Test 5public void testDetectsNegativeCycle() { ... } 6 7@Test 8public void testSingleNodeGraph() { ... } 9 10@Test 11public void testDisconnectedNodes() { ... }
Test Documentation
Each test method gets a brief comment explaining what scenario it covers and why that scenario matters:
java1/** 2 * Graph with a negative cycle reachable from the source. 3 * Bellman-Ford should mark affected nodes as NEGATIVE_INFINITY. 4 * 5 * 0 --5--> 1 --(-10)--> 2 --3--> 1 6 * (creates cycle 1→2→1 with net cost -7) 7 */ 8@Test 9public void testDetectsNegativeCycle() { 10 // ... test body 11}
When Modifying Code, Update Tests
Every code change must be accompanied by:
- Running existing tests to check for regressions
- Adding new tests if new behavior is introduced
- Updating existing tests if method signatures or behavior changed
- Removing tests only if the feature they cover was deliberately removed
Skill 3: Refactoring and Code Debt
Goal: Keep the codebase clean without losing educational value.
When to Remove Code
Remove code that is:
- Exact duplicates of another implementation with no added educational value
- Dead code (unreachable, unused helper methods)
- Commented-out blocks with no explanation of why they exist
- Temporary debug/print statements
When to Keep "Duplicate" Code
Keep alternative implementations when they teach different approaches:
java1// ✓ KEEP — BFS and DFS solutions to the same problem teach different techniques 2public int[] bfsSolve(int[][] grid) { ... } 3public int[] dfsSolve(int[][] grid) { ... } 4 5// ✓ KEEP — iterative vs recursive shows tradeoffs 6public int fibRecursive(int n) { ... } 7public int fibIterative(int n) { ... } 8 9// ✗ REMOVE — identical logic, just different variable names 10public int search_v1(int[] arr, int target) { ... } 11public int search_v2(int[] arr, int target) { ... }
When keeping alternatives, clearly label them with a comment explaining the educational purpose:
java1/** 2 * Recursive implementation of binary search. 3 * Compare with binarySearchIterative() to see the iterative approach. 4 * The iterative version avoids stack overhead for large arrays. 5 */
Debt Checklist
When refactoring, scan for:
- Unused imports
- Unused variables or parameters
- Methods that can be combined or simplified
- Magic numbers that should be named constants
- Inconsistent naming within the same file
- Copy-pasted blocks that should be extracted into a helper
Skill 4: Code Formatting and Consistency
Goal: Uniform style across the entire repository.
Naming Conventions
Use short, clear variable names. Prefer readability through simplicity:
java1// ✓ GOOD — short and clear 2int n = graph.length; 3int[] dist = new int[n]; 4boolean[] vis = new boolean[n]; 5List<int[]> adj = new ArrayList<>(); 6Queue<Integer> q = new LinkedList<>(); 7int src = 0; 8int dst = n - 1; 9 10// ✗ BAD — verbose names that clutter algorithm logic 11int numberOfNodesInGraph = graph.length; 12int[] shortestDistanceFromSource = new int[numberOfNodesInGraph]; 13boolean[] hasNodeBeenVisited = new boolean[numberOfNodesInGraph]; 14List<int[]> adjacencyListRepresentation = new ArrayList<>(); 15Queue<Integer> breadthFirstSearchQueue = new LinkedList<>(); 16int sourceNodeIndex = 0; 17int destinationNodeIndex = numberOfNodesInGraph - 1;
Common short names (use consistently across the repo):
| Name | Meaning |
|---|---|
n | number of elements/nodes |
m | number of edges |
i, j | loop indices |
from, to | graph node endpoints |
cost | edge weight |
dist | distance array |
vis | visited array |
adj | adjacency list |
q | queue |
pq | priority queue |
st | stack |
dp | dynamic programming table |
ans | result/answer |
lo | low pointer/bound |
hi | high pointer/bound |
mid | midpoint |
src | source node |
dst | destination node |
cnt | counter |
sz | size |
cur | current element |
prev | previous element |
next | next element (use nxt if shadowing keyword) |
Formatting Rules
- Braces: opening brace on the same line (
if (...) {) - Indentation: 2 spaces (no tabs)
- Blank lines: one blank line between methods, none inside short methods
- Max line length: 100 characters (soft limit)
- Imports: group by package, alphabetize within groups, no wildcard imports
Big-O Notation Convention
Always use explicit multiplication and parentheses in Big-O expressions for clarity:
java1// ✓ GOOD — explicit and unambiguous 2// Time: O(n*log(n)) 3// Time: O(n*log^2(n)) 4// Time: O(n^2*log(n)) 5 6// ✗ BAD — missing multiplication and parentheses 7// Time: O(n log n) 8// Time: O(n log^2 n) 9// Time: O(n^2 log n) 10 11// Simple expressions without multiplication are fine as-is 12// Time: O(n) 13// Time: O(n^2) 14// Time: O(log(n)) 15// Space: O(n)
For Loop Body on Its Own Line
Always place the body of a for loop on its own line, even for single statements.
This improves readability, especially in nested loops:
java1// ✗ BAD — body on same line as for 2for (int j = 0; j < n; j++) augmented[i][j] = matrix[i][j]; 3 4// ✓ GOOD — body on its own line 5for (int j = 0; j < n; j++) 6 augmented[i][j] = matrix[i][j]; 7 8// ✓ GOOD — nested for loops, each level on its own line 9for (int i = 0; i < n; i++) 10 for (int j = 0; j < n; j++) 11 for (int k = 0; k < n; k++) 12 result[i][j] += m1[i][k] * m2[k][j];
Avoid Java Streams
Streams hurt readability for learners. Use plain loops instead:
java1// ✗ AVOID — streams obscure the logic for beginners 2int sum = Arrays.stream(arr).filter(x -> x > 0).reduce(0, Integer::sum); 3 4// ✓ PREFER — a loop is immediately readable 5int sum = 0; 6for (int x : arr) { 7 if (x > 0) sum += x; 8}
Skill 5: Simplification
Goal: The simplest correct code teaches the best.
Simplification Strategies
- Reduce nesting — invert conditions, return early
java1// ✗ AVOID — deep nesting 2if (node != null) { 3 if (node.left != null) { 4 if (node.left.val == target) { 5 return true; 6 } 7 } 8} 9return false; 10 11// ✓ PREFER — early returns keep code flat 12if (node == null) return false; 13if (node.left == null) return false; 14return node.left.val == target;
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Extract repeated logic — but only if it genuinely reduces complexity
-
Use standard library where it clarifies —
Arrays.sort(),Collections.swap(),Math.min(), etc. are fine because learners need to know these exist -
Remove unnecessary wrappers — don't wrap a single method call in another method
-
Prefer arrays over complex data structures when the problem allows it —
int[]is clearer thanArrayList<Integer>when the size is known
What NOT to Simplify
- Don't merge two clearly distinct algorithm phases into one loop just to save lines
- Don't replace clear if/else chains with ternary operators if it reduces readability
- Don't remove intermediate variables that give a name to a complex expression
Skill 6: Bug Detection
Goal: Catch bugs proactively whenever touching code.
Bug Scan Checklist
When modifying any lines of code, actively check for and report:
- Off-by-one errors — loop bounds, array indices, fence-post problems
- Integer overflow — multiplication or addition that could exceed int range
- Null/empty checks — missing guards for null arrays, empty collections
- Uninitialized values — using variables before assignment (especially in dp arrays)
- Wrong comparison —
==vs<=,<vs<=in loop conditions - Infinite loops — conditions that never become false, missing increments
- Array out of bounds — indexing with
i+1,i-1without range checks - Graph issues — missing visited check (infinite loop in cycles), wrong direction in directed graph
- Incorrect base cases — dp[0], recursion base case, empty graph
- Mutation bugs — modifying input that caller expects unchanged
- Copy vs reference — shallow copy when deep copy needed
- Return value misuse — ignoring return value, returning wrong variable
How to Report Bugs
When a bug is found, report it clearly:
🐛 BUG FOUND in BellmanFord.java line 42:
Loop runs `i < n` but should be `i < n - 1`.
The extra iteration incorrectly marks reachable nodes as
being in a negative cycle.
FIX: Change `i < n` to `i < n - 1`
Skill 7: Algorithm Explanation Comments
Goal: Help learners understand the why behind each algorithm.
Skill 8: Place main method at the bottom
Goal: The main java method should be near the bottom of the Java file for consistency throughout the project
FAQ & Installation Steps
These questions and steps mirror the structured data on this page for better search understanding.
? Frequently Asked Questions
What is algorithms-education?
algorithms-education is a collection of algorithms and data structures designed to educate and optimize code for developers.
How do I install algorithms-education?
Run the command: npx killer-skills add williamfiset/Algorithms/algorithms-education. It works with Cursor, Windsurf, VS Code, Claude Code, and 19+ other IDEs.
Which IDEs are compatible with algorithms-education?
This skill is compatible with Cursor, Windsurf, VS Code, Trae, Claude Code, OpenClaw, Aider, Codex, OpenCode, Goose, Cline, Roo Code, Kiro, Augment Code, Continue, GitHub Copilot, Sourcegraph Cody, and Amazon Q Developer. Use the Killer-Skills CLI for universal one-command installation.
↓ How To Install
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1. Open your terminal
Open the terminal or command line in your project directory.
-
2. Run the install command
Run: npx killer-skills add williamfiset/Algorithms/algorithms-education. The CLI will automatically detect your IDE or AI agent and configure the skill.
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3. Start using the skill
The skill is now active. Your AI agent can use algorithms-education immediately in the current project.