VetsWhoCode: Combat-Ready Coding Patterns 🎖️

"In code as in combat, patterns and preparation determine success." - VetsWhoCode

Mission Overview

These battle-tested coding patterns form the foundation of technical interviews and efficient problem-solving. Like standard operating procedures (SOPs) in combat, these patterns provide proven solutions to common challenges.

Table of Contents

Mission Briefing

These patterns are your tactical toolset for coding interviews. Like a well-maintained weapon system, each pattern serves a specific purpose and should be mastered through consistent practice and application.

Battle Rhythm

  1. Identify the pattern that fits your mission
  2. Apply the appropriate tactical solution
  3. Test and verify your implementation
  4. Optimize for better performance

Two Pointers Pattern

Tactical Overview

Mission Type: Coordinated Movement Operations

Military Context: Like coordinating two fire teams during a patrol - each team moves with purpose and coordination to achieve the mission objective. Just as fire teams maintain relative positioning, our pointers maintain their relationship while moving through the array.

Battle Plan

  1. Initialize two pointers at strategic positions
  2. Move pointers based on mission parameters
  3. Maintain coordination between pointer movements
  4. Achieve objective with minimal traversal

Implementation: Equipment Load Distribution

def find_equipment_pairs(weights, target_weight):
    """
    Mission: Find pairs of equipment that add up to target weight.

    Tactical Application: 
    - Organizing gear for balanced load distribution
    - Matching battle buddies for equipment carry
    - Ensuring optimal weight distribution across the unit

    Operation Parameters:
    weights (list): List of equipment weights
    target_weight (int): Target combined weight

    Mission Outcome:
    list: Pairs of weights that match target
    """
    weights.sort()  # Organize equipment by weight
    left = 0  # Alpha team position
    right = len(weights) - 1  # Bravo team position
    pairs = []

    while left < right:
        current_weight = weights[left] + weights[right]
        if current_weight == target_weight:
            pairs.append((weights[left], weights[right]))
            left += 1  # Alpha team advances
            right -= 1  # Bravo team falls back
        elif current_weight < target_weight:
            left += 1  # Alpha team moves forward
        else:
            right -= 1  # Bravo team adjusts position

    return pairs

# Field Operations Test
equipment_weights = [10, 15, 20, 25, 30, 35]
target = 45
pairs = find_equipment_pairs(equipment_weights, target)
print(f"SITREP: Equipment pairs matching {target}lbs: {pairs}")

Combat Tips

  • Always sort when dealing with pair finding
  • Consider edge cases like empty arrays
  • Watch for pointer bounds

Sliding Window Pattern

Tactical Overview

Mission Type: Surveillance and Monitoring Operations

Military Context: Analogous to maintaining a surveillance window on an area of operation. Like how a unit maintains constant observation while moving through terrain, the sliding window keeps track of a specific subset of data while moving through the array.

Battle Plan

  1. Establish initial observation window
  2. Monitor and record metrics within window
  3. Advance window systematically
  4. Maintain optimal window size for mission requirements

Implementation: Unit Performance Tracking

def analyze_performance_window(performance_scores, days):
    """
    Mission: Track maximum average performance over consecutive days.

    Tactical Application:
    - Monitoring unit readiness
    - Tracking squad performance trends
    - Identifying optimal training periods
    - Measuring combat effectiveness

    Operation Parameters:
    performance_scores (list): Daily performance metrics
    days (int): Window size to analyze

    Mission Outcome:
    float: Maximum average performance for any window
    """
    if not performance_scores or days <= 0:
        return 0

    # Establish initial observation window
    current_sum = sum(performance_scores[:days])
    max_sum = current_sum

    # Advance observation window
    for i in range(days, len(performance_scores)):
        # Shift window forward
        current_sum = current_sum - performance_scores[i - days] + performance_scores[i]
        max_sum = max(max_sum, current_sum)

    return max_sum / days

# Field Operations Test
daily_scores = [85, 90, 92, 88, 86, 95, 92]
window_size = 3
max_avg = analyze_performance_window(daily_scores, window_size)
print(f"SITREP: Peak performance average over {window_size} days: {max_avg}")

Combat Tips

  • Initialize window bounds correctly
  • Update window contents efficiently
  • Track maximum/minimum values as needed

Fast & Slow Pointers Pattern

Tactical Overview

Mission Type: Reconnaissance Operations

Military Context: Similar to scout team and main element movement. The scout team (fast pointer) moves ahead at twice the pace while maintaining coordination with the main element (slow pointer).

Battle Plan

  1. Deploy scout element (fast pointer)
  2. Coordinate with main element (slow pointer)
  3. Maintain communication between elements
  4. Identify patterns or cycles in movement

Implementation: Patrol Route Cycle Detection

class PatrolPoint:
    """
    Tactical waypoint in patrol route
    """
    def __init__(self, location, next=None):
        self.location = location
        self.next = next

def detect_circular_patrol(patrol_route):
    """
    Mission: Detect if a patrol route circles back to a previous point.

    Tactical Application:
    - Route reconnaissance
    - Patrol pattern analysis
    - Identifying redundant coverage
    - Ensuring efficient area coverage

    Operation Parameters:
    patrol_route: Starting point of patrol route

    Mission Outcome:
    bool: True if route contains a cycle
    """
    if not patrol_route:
        return False

    # Scout team (fast) and main element (slow)
    main_element = patrol_route
    scout_team = patrol_route.next

    while scout_team and scout_team.next:
        if main_element == scout_team:
            return True  # Circular pattern detected
        main_element = main_element.next
        scout_team = scout_team.next.next

    return False

# Field Operations Test
# Create patrol route: Alpha -> Bravo -> Charlie -> Delta -> Bravo
point_a = PatrolPoint("Alpha")
point_b = PatrolPoint("Bravo")
point_c = PatrolPoint("Charlie")
point_d = PatrolPoint("Delta")

point_a.next = point_b
point_b.next = point_c
point_c.next = point_d
point_d.next = point_b  # Creates cycle

is_circular = detect_circular_patrol(point_a)
print(f"SITREP: Patrol route contains circular pattern: {is_circular}")

Combat Tips

  • Watch for null/none values
  • Handle edge cases carefully
  • Maintain proper pointer speeds

Binary Search Pattern

Tactical Overview

Mission Type: Target Acquisition Operations

Military Context: Similar to bracketing procedures in artillery fire missions. You systematically narrow down your target area by adjusting between known boundaries until you achieve target acquisition.

Battle Plan

  1. Establish search boundaries
  2. Calculate mid-point
  3. Adjust search sector based on target position
  4. Repeat until target acquired or sector cleared

Implementation: Personnel Location in Formation

def locate_in_formation(positions, target_id):
    """
    Mission: Efficiently locate a service member's position in formation.

    Tactical Application:
    - Personnel accountability
    - Formation management
    - Quick reaction force assignments
    - Rapid personnel location

    Operation Parameters:
    positions (list): Sorted list of position IDs
    target_id (int): ID to locate

    Mission Outcome:
    int: Index of target position or -1 if not found
    """
    left = 0  # Left boundary
    right = len(positions) - 1  # Right boundary

    while left <= right:
        mid = (left + right) // 2  # Center of current sector

        if positions[mid] == target_id:
            return mid  # Target acquired
        elif positions[mid] < target_id:
            left = mid + 1  # Adjust sector right
        else:
            right = mid - 1  # Adjust sector left

    return -1  # Target not found

# Field Operations Test
formation_positions = [2, 4, 6, 8, 10, 12, 14, 16]
target = 10
position = locate_in_formation(formation_positions, target)
print(f"SITREP: Service member {target} located at position: {position}")

Combat Tips

  • Ensure array is sorted before search
  • Handle boundary conditions
  • Watch for integer overflow in midpoint calculation

After Action Review

Key Tactical Points

  1. Each pattern represents a battle-tested approach to solving specific types of problems
  2. Practice these patterns until they become muscle memory
  3. Remember: In both coding and combat, preparation and pattern recognition are key to success

Field Notes

  • Document your approaches
  • Learn from failed attempts
  • Build your pattern recognition skills

Standard Operating Procedures

  1. Always identify the pattern before coding
  2. Test with multiple scenarios
  3. Consider edge cases
  4. Optimize after achieving basic functionality

"Code with Honor, Debug with Discipline" - VetsWhoCode

"Mission success through tactical coding excellence"