Accenture is a global professional services company known for its expertise in digital, cloud, and security services. It provides a wide range of services, including consulting, technology, and operations, to clients across various industries. With its strong reputation, Accenture attracts many job seekers, making the hiring process highly competitive. One of the crucial stages in Accenture’s hiring process is the coding round, especially for technical roles.

The coding round plays a significant role in Accentureâ€™s selection process, as it helps identify candidates with strong programming and problem-solving skills. Whether you’re a fresher or an experienced professional, acing the coding round is essential for securing a position at Accenture. This article aims to provide you with comprehensive guidance on how to crack the Accenture coding round, ensuring that you are well-prepared to meet the challenges it presents.

## Understanding Accenture’s Coding Interview

Accentureâ€™s coding interview is designed to assess your ability to solve programming problems efficiently and accurately. Understanding the format, allowed programming languages, types of questions, and evaluation criteria is crucial for your preparation.

### Accenture Coding Round Format

The coding round can be conducted either online or offline, depending on the recruitment drive or interview stage. Typically, the round lasts between 45 minutes to an hour. You will be presented with 1-3 coding problems that vary in difficulty, and your task is to solve as many as possible within the given time frame.

The online format is usually proctored and conducted on platforms like CoCubes, HackerRank, or AMCAT. Youâ€™ll need a stable internet connection and a quiet environment to focus on solving the problems. In an offline setting, the coding round is usually conducted on a computer in an Accenture office or a designated test centre.

### Programming Languages Allowed

Accenture allows candidates to solve coding problems using a variety of programming languages. The most commonly accepted languages include:

- C
- C++
- Java
- Python

Each of these languages has its own strengths, so itâ€™s important to choose the one youâ€™re most comfortable with. For instance, Python is known for its simplicity and speed in writing code, while C++ offers more control over memory management, which can be useful for certain types of problems.

### Types of Questions

The coding round typically includes questions that test your knowledge of algorithms, data structures, and problem-solving skills. Hereâ€™s a breakdown of the types of questions you might encounter:

**Algorithms:** These questions may involve sorting, searching, recursion, or dynamic programming. Youâ€™ll need to implement algorithms that solve the problem efficiently.

**Data Structures:** You may be asked to work with arrays, strings, linked lists, stacks, queues, trees, graphs, or heaps. Understanding how these data structures work and how to manipulate them is crucial.

**Problem-Solving:** Some questions may require you to solve a specific problem, like finding the shortest path in a graph or optimising a certain process. These problems often test your ability to think critically and apply your knowledge of algorithms and data structures.

### Evaluation Criteria

Accenture evaluates your coding round performance based on several factors:

**Code Correctness:**Your solution must produce the correct output for all test cases, including edge cases.**Efficiency:**The time and space complexity of your solution are important. Efficient code that runs quickly and uses minimal memory is preferred.**Code Quality:**Writing clean, readable, and well-organised code is also essential. This includes using appropriate variable names, comments, and following best practices.

Next, we will delve into the specific types of questions that candidates may encounter during the coding round. This will provide you with a clearer picture of what to study and practice.

## Accenture Coding Round Questions and Answers

In this section, we will discuss the types of questions you can expect in the Accenture coding round, categorised by difficulty level. Each question will be accompanied by a detailed explanation, code samples, and an analysis of the time and space complexity.

### Accenture Basic Level Coding Round Questions and Answers

At the basic level, questions typically involve simple data structures and algorithms. These are designed to test your fundamental programming skills.

#### Simple Data Structures: Arrays and Strings

**Example Question:**

**Problem:** Given an array of integers, return a new array where each element is the product of all the elements in the original array except the one at the current index.

**Example:**

Input: [1, 2, 3, 4]

Output: [24, 12, 8, 6]

**Explanation:**

To solve this problem, you can use two arrays to store the prefix and suffix products of the original array elements. Then, multiply the corresponding prefix and suffix to get the final product for each element.

**Code Explanation:**

python

def product_except_self(nums):

n = len(nums)

left_products = [1] * n

right_products = [1] * n

result = [1] * n

for i in range(1, n):

left_products[i] = left_products[i – 1] * nums[i – 1]

for i in range(n – 2, -1, -1):

right_products[i] = right_products[i + 1] * nums[i + 1]

for i in range(n):

result[i] = left_products[i] * right_products[i]

return result

# Test the function

print(product_except_self([1, 2, 3, 4])) # Output: [24, 12, 8, 6]

Time Complexity: O(n)

Space Complexity: O(n)

#### Basic Algorithms: Sorting and Searching

**Example Question:**

**Problem:** Implement the binary search algorithm to find the index of a target element in a sorted array. If the target is not found, return -1.

**Example:**

Input: array = [1, 2, 4, 6, 7, 10], target = 4

Output: 2

**Code Explanation:**

python

def binary_search(arr, target):

left, right = 0, len(arr) – 1

while left <= right:

mid = (left + right) // 2

if arr[mid] == target:

return mid

elif arr[mid] < target:

left = mid + 1

else:

right = mid – 1

return -1

# Test the function

print(binary_search([1, 2, 4, 6, 7, 10], 4)) # Output: 2

Time Complexity: O(log n)

Space Complexity: O(1)

### Accenture Medium Level Coding Round Questions and Answers

Medium-level questions often involve more complex data structures and algorithms. These questions test your ability to handle recursion, dynamic programming, and more intricate data structures.

#### More Complex Data Structures: Linked Lists, Stacks, Queues

**Example Question:**

**Problem:** Reverse a linked list.

**Example:**

Input: 1 -> 2 -> 3 -> 4 -> 5

Output: 5 -> 4 -> 3 -> 2 -> 1

**Code Explanation:**

python

class ListNode:

def __init__(self, value=0, next=None):

self.value = value

self.next = next

def reverse_linked_list(head):

prev = None

current = head

while current:

next_node = current.next

current.next = prev

prev = current

current = next_node

return prev

# Test the function

# Creating a linked list: 1 -> 2 -> 3 -> 4 -> 5

head = ListNode(1, ListNode(2, ListNode(3, ListNode(4, ListNode(5)))))

reversed_head = reverse_linked_list(head)

# Print the reversed linked list

while reversed_head:

print(reversed_head.value, end=” -> ” if reversed_head.next else “”)

reversed_head = reversed_head.next

# Output: 5 -> 4 -> 3 -> 2 -> 1

Time Complexity: O(n)

Space Complexity: O(1)

#### Intermediate Algorithms: Recursion and Dynamic Programming

**Example Question:**

**Problem:** Write a function to calculate the nth Fibonacci number using dynamic programming.

**Example:**

Input: n = 5

Output: 5

**Explanation:**

The Fibonacci sequence is defined as:

F(0) = 0, F(1) = 1

F(n) = F(n-1) + F(n-2) for n > 1

**Code Explanation:**

python

def fibonacci(n):

if n <= 1:

return n

fib = [0] * (n + 1)

fib[1] = 1

for i in range(2, n + 1):

fib[i] = fib[i – 1] + fib[i – 2]

return fib[n]

# Test the function

print(fibonacci(5)) # Output: 5

Time Complexity: O(n)

Space Complexity: O(n)

### Accenture Advanced Level Coding Round Questions and Answers

Advanced-level questions are designed to challenge your understanding of complex data structures and algorithms. These questions often involve trees, graphs, and advanced algorithmic techniques.

#### Data Structures: Trees, Graphs, Heaps

**Example Question:**

**Problem:** Find the lowest common ancestor (LCA) of two nodes in a binary tree.

**Explanation:**

The Lowest Common Ancestor (LCA) of two nodes p and q in a binary tree is defined as the deepest node that has both p and q as descendants. A node can be a descendant of itself.

**Example:**

Input: A binary tree with root 3, left child 5, right child 1, and further children:

markdown

3

/ \

5 1

/ \ / \

6 2 0 8

/ \

7 4

Nodes: p = 5, q = 1

Output: 3

**Code Explanation:**

python

class TreeNode:

def __init__(self, value=0, left=None, right=None):

self.value = value

self.left = left

self.right = right

def lowest_common_ancestor(root, p, q):

if not root or root == p or root == q:

return root

left = lowest_common_ancestor(root.left, p, q)

right = lowest_common_ancestor(root.right, p, q)

if left and right:

return root

return left if left else right

# Test the function

# Constructing the binary tree from the example

root = TreeNode(3)

root.left = TreeNode(5)

root.right = TreeNode(1)

root.left.left = TreeNode(6)

root.left.right = TreeNode(2, TreeNode(7), TreeNode(4))

root.right.left = TreeNode(0)

root.right.right = TreeNode(8)

p = root.left # Node with value 5

q = root.right # Node with value 1

lca = lowest_common_ancestor(root, p, q)

print(lca.value) # Output: 3

Time Complexity: O(n)

Space Complexity: O(h), where h is the height of the tree (due to recursion stack)

#### Advanced Algorithms: Greedy and Backtracking

**Example Question:**

**Problem:** Implement a solution to solve the “N-Queens” problem, where you must place N queens on an N x N chessboard such that no two queens threaten each other.

**Example:**

Input: N = 4

Output:

css

[ [“.Q..”, “…Q”, “Q…”, “..Q.”],

[“..Q.”, “Q…”, “…Q”, “.Q..”]

]

**Code Explanation:**

python

def solve_n_queens(n):

def is_safe(board, row, col):

for i in range(col):

if board[row][i] == ‘Q’:

return False

for i, j in zip(range(row, -1, -1), range(col, -1, -1)):

if board[i][j] == ‘Q’:

return False

for i, j in zip(range(row, n, 1), range(col, -1, -1)):

if board[i][j] == ‘Q’:

return False

return True

def solve(board, col):

if col >= n:

solutions.append([“”.join(row) for row in board])

return

for i in range(n):

if is_safe(board, i, col):

board[i][col] = ‘Q’

solve(board, col + 1)

board[i][col] = ‘.’

solutions = []

board = [[‘.’ for _ in range(n)] for _ in range(n)]

solve(board, 0)

return solutions

# Test the function

n = 4

result = solve_n_queens(n)

for solution in result:

for line in solution:

print(line)

print()

Time Complexity: O(N!), where N is the size of the board

Space Complexity: O(N^2)

With these examples in mind, we will move on to effective strategies for preparing for the coding round. These tips will help you enhance your skills and boost your confidence before the interview.

## Tips to Prepare for Accenture Coding Round Questions

Preparation is key to performing well in the Accenture coding round. Here are some practical tips to help you maximise your chances of success.

### 1) Importance of Practice

The best way to prepare for coding interviews is to practise regularly. Working through various coding problems helps you become familiar with different question types and improves your problem-solving speed. iScalePro offers a wide range of coding problems, including mock interviews that simulate the real Accenture coding round.

By solving problems daily, youâ€™ll improve your coding skills and gain confidence. Focus on solving problems of varying difficulty levels, starting with basic ones and gradually moving to more advanced questions. Mock interviews are particularly beneficial as they mimic the pressure of the actual interview, helping you manage time and nerves.

### 2) Time Management and Problem-Solving Skills

During the coding round, managing your time effectively is crucial. Youâ€™ll typically have limited time to solve multiple problems, so itâ€™s important to allocate your time wisely. Start by quickly reading through all the questions to identify the ones you can solve easily. Prioritise these questions to secure some early points, then move on to the more challenging problems.

Additionally, break down each problem into smaller parts to make it more manageable. Write down the steps or pseudocode before you start coding to clarify your approach. This will help you avoid getting stuck and will ensure that your solution is logical and well-structured.

### 3) Choosing the Right Programming Language

Choosing the right programming language can significantly impact your performance in the coding round. Select a language that youâ€™re most comfortable with and one that is efficient for the types of problems youâ€™ll encounter.

**Python:**Known for its simplicity and large set of built-in libraries, Python is an excellent choice for beginners and those who prefer quick development.**Java:**Java is a widely-used language with strong type-checking and object-oriented features, making it suitable for complex problems.**C++:**C++ offers fine-grained control over memory management and is known for its performance, making it a great choice for competitive programming.**C:**C is a low-level language that provides direct access to hardware and memory. Itâ€™s a good choice for candidates who are familiar with systems programming.

Whichever language you choose, ensure you are familiar with its syntax, standard libraries, and best practices.

### 4) Handling Stress and Nerves

Coding interviews can be stressful, especially when the stakes are high. Itâ€™s important to stay calm and composed during the coding round. Here are some tips to help you manage stress:

**Practise deep breathing:**Before the interview begins, take a few deep breaths to relax and focus your mind.**Stay positive:**Approach each question with a positive attitude. Even if you get stuck, keep trying different approaches until you find a solution.**Take breaks if needed:**If you feel overwhelmed, take a brief moment to collect your thoughts before continuing.**Stay focused on the present:**Donâ€™t worry about the outcome of the interview or other candidates. Concentrate on the problem in front of you and give it your best shot.

## Conclusion

The coding round is a critical part of Accentureâ€™s hiring process, especially for technical roles. Whether youâ€™re a fresher or an experienced professional, preparing thoroughly for this round can significantly increase your chances of success. Understanding the format, types of questions, and evaluation criteria will give you a clear idea of what to expect.

By practising regularly, managing your time effectively, choosing the right programming language, and handling stress calmly, youâ€™ll be well-prepared to tackle the coding round with confidence. Remember, consistent effort and a positive mindset are key to cracking the Accenture coding round.