Top Strategies for Acing the Cisco OA Coding Questions

Cisco’s Online Assessment (OA) for software engineering roles is known for its algorithmic and networking-focused coding challenges. To maximize your success, follow these proven strategies based on recent candidate experiences and insider insights.

Understand Cisco OA Coding Structure Cisco’s coding section typically includes:
- 2-3 algorithm questions (LeetCode Medium level)
- 1 networking-related problem (e.g., packet routing, TCP/IP logic)
- Time limit: 60-90 minutes

2024 Trends:

More graph and tree problems (BFS/DFS applications).
Increased focus on optimization (time/space complexity matters).

Master the Most Frequent Question Types

A. Algorithms & Data Structures

Graphs (BFS/DFS) – 40% of Questions Why? Cisco’s networking focus means pathfinding, connectivity, and routing problems are common.

Example Question:

"Find the shortest path between two nodes in a network topology."

Optimal Approach:

from collections import deque  

def shortest_path(graph, start, end):  
    queue = deque([(start, [start])])  
    visited = set()  
    while queue:  
        node, path = queue.popleft()  
        if node == end:  
            return path  
        for neighbor in graph[node]:  
            if neighbor not in visited:  
                visited.add(neighbor)  
                queue.append((neighbor, path + [neighbor]))  
    return []

Key Insight:

Use BFS for shortest path (unweighted graphs).
DFS for connectivity checks (e.g., "Are two routers connected?").

Dynamic Programming (DP) – 30% of Questions Why? Cisco loves optimization problems (e.g., bandwidth allocation, resource management).

Example Question:

"A network router can handle W packets/sec. Given n flows with different sizes, maximize throughput without exceeding W."

Optimal Approach:

def max_throughput(packets, W):  
    dp = [0]  (W + 1)  
    for p in packets:  
        for w in range(W, p - 1, -1):  
            dp[w] = max(dp[w], dp[w - p] + p)  
    return dp[W]

Key Insight:

Knapsack-style problems dominate Cisco’s DP questions.
Memoization vs. Tabulation: Prefer tabulation for Cisco (interviewers favor iterative DP).

String/Array Manipulation – 20% of Questions Example Question: "Given a log of network events, extract IP addresses that made >100 requests."

Optimal Approach:

def find_spammers(logs):  
    from collections import defaultdict  
    ip_count = defaultdict(int)  
    for log in logs:  
        ip = log.split()[0]  
        ip_count[ip] += 1  
    return [ip for ip, cnt in ip_count.items() if cnt > 100]

Key Insight:

HashMaps (dicts) are your best friend for counting problems.
Time complexity matters—avoid O(n²) solutions.

Networking Logic – 10% of Questions Example Question: "Simulate TCP congestion control (AIMD algorithm)."

Optimal Approach:

def aimd(cwnd, max_thresh):  
    if cwnd >= max_thresh:  
        return cwnd // 2   Multiplicative Decrease  
    else:  
        return cwnd + 1     Additive Increase

Key Insight:

Basic networking knowledge (TCP/IP, DNS, HTTP) is a must.
Practice simple simulations (e.g., packet drops, retransmissions).

Step-by-Step Problem-Solving Strategy

Step 1: Clarify the Problem (2 mins)

Ask:
- "Can the graph have cycles?"
- "Should I optimize for time or space?"

Step 2: Brute Force First (5 mins)

Write a working (but slow) solution to ensure correctness.
Example:

   Brute-force substring search  
  def find_substring(s, pattern):  
      for i in range(len(s) - len(pattern) + 1):  
          if s[i:i+len(pattern)] == pattern:  
              return i  
      return -1

Step 3: Optimize (8 mins)

Identify bottlenecks:
- Nested loops? → Use sliding window or hashmap.
- Recursive calls? → Switch to DP/memoization.
Upgrade to optimal solution:

   Optimized with sliding window  
  def find_substring(s, pattern):  
      n, m = len(s), len(pattern)  
      if m == 0: return 0  
      lps = compute_lps(pattern)   KMP algorithm  
       ... (O(n) solution)