Want to crack the TCS NQT coding section? It's a guide to help you. We'll cover the patterns, the types of questions they throw at you, and how to solve them without unnecessary complexity.<\/p>\n\n\n\n
The coding section is where they separate the people who can talk about code from the people who can write it. Your goal is to pass the test cases. Let's get straight to it.<\/p>\n\n\n\n
Before diving into problems, understand the structure and common challenges of the NQT coding section.<\/p>\n\n\n\n
Structure (The Integrated Test Pattern):<\/strong> TCS now uses a single 190-minute exam to decide all three job profiles. The test is strictly divided into: <\/p>\n\n\n\n Part A:<\/strong> Foundation (75 mins for basic aptitude\/verbal) \n Java DSA Course<\/a>\n <\/p>\n Learn Data Structures & Algorithms (DSA) in Java to excel in coding interviews and software development. Master linked lists, trees, graphs, heaps, hashing, sorting, and more while building efficient, optimized solutions.<\/p>\n This is very important. More people fail because they can't read the input correctly than because their logic is wrong. The compiler is strict, and the problem descriptions can be vague about the input format.<\/p>\n\n\n\n The Rule:<\/strong> Assume the simplest input format unless specified.<\/p>\n\n\n\n Pro Tip for Python Users:<\/strong> The compiler's handling of tabs versus spaces for indentation is a known issue. Use spaces for indentation to be safe. Some candidates report that tabs simply do not work correctly.<\/p>\n\n\n\n Here's a breakdown of the question types you will face. We'll go through each with examples. Focus on the logic. The implementation is just a tool.<\/p>\n\n\n\n Arrays<\/a> are the bread and butter of the NQT. You are almost guaranteed to get an array question. They test your ability to manipulate a list of numbers.<\/p>\n\n\n\n Common Array Problems:<\/strong><\/p>\n\n\n\n Problem:<\/strong> Given an array of integers, find the second largest element.<\/p>\n\n\n\n The Logic:<\/strong><\/p>\n\n\n\n Don't overthink this. You don't need to sort the whole array; that's inefficient. You only need two variables: Explanation:<\/strong><\/p>\n\n\n\n \n Python Programming Course<\/a>\n <\/p>\n In this course, you will learn the fundamentals of Python: from basic syntax to mastering data structures, loops, and functions. You will also explore OOP concepts and objects to build robust programs.<\/p>\n Problem:<\/strong> Given a sorted array, remove the duplicates in-place such that each element appears only once. Return the new length of the array.<\/p>\n\n\n\n The Logic:<\/strong><\/p>\n\n\n\n This is a classic two-pointer problem. Since the array is sorted, all duplicate elements will be adjacent.<\/p>\n\n\n\n Explanation:<\/strong><\/p>\n\n\n\n String questions are also very common. They test your understanding of characters, substrings<\/a>, and basic string algorithms.<\/p>\n\n\n\n Common String Problems:<\/strong><\/p>\n\n\n\n Problem:<\/strong> Given two strings, determine if they are anagrams of each other.<\/p>\n\n\n\n The Logic (Optimized for Digital\/Prime Constraints):<\/strong><\/p>\n\n\n\n While sorting the strings is the easiest method, it takes O(N log N)<\/strong> time. In the new TCS Advanced section, string lengths can be massive (e.g., 10^5 characters), and sorting will result in a Time Limit Exceeded (TLE) error. The optimal approach is O(N)<\/strong> time using a frequency counter (Hash Map\/Dictionary).<\/p>\n\n\n\n Explanation:<\/strong><\/p>\n\n\n\n These questions involve logic based on mathematical concepts. They are less about complex data structures<\/a> and more about your problem-solving logic.<\/p>\n\n\n\n Common Number Theory Problems:<\/strong><\/p>\n\n\n\n Problem:<\/strong> Given an integer, determine if it is a prime number.<\/p>\n\n\n\n The Logic:<\/strong><\/p>\n\n\n\n A prime number is a number greater than 1 that has no positive divisors other than 1 and itself.<\/p>\n\n\n\n Explanation:<\/strong><\/p>\n\n\n\n If you are targeting the 7 LPA (Digital) or 9-12 LPA (Prime) packages, the 90-minute advanced coding section will push your limits. TCS has significantly raised the bar for Prime candidates, so basic arrays won't be enough. <\/p>\n\n\n\n Topics to master for 2026:<\/strong><\/p>\n\n\n\n
Part B: <\/strong>Advanced (115 mins for advanced math, reasoning, and coding). <\/p>\n\n\n\n\n
The Most Important Skill: Handling Input<\/h2>\n\n\n\n
\n
split()<\/code> or parsing comma-separated strings unless the problem explicitly says so.<\/li>\n\n\n\nCore Topics & Solved Questions<\/h2>\n\n\n\n
1. Array-Based Questions<\/h3>\n\n\n\n
\n
Question 1: Find the Second Largest Number in an Array<\/h3>\n\n\n\n
largest<\/code> and second_largest<\/code>.<\/p>\n\n\n\n\n
largest<\/code> and second_largest<\/code> to the smallest possible integer value.<\/li>\n\n\n\n\n
largest<\/code>, the current largest<\/code> becomes the new second_largest<\/code>, and this element becomes the new largest<\/code>.<\/li>\n\n\n\nsecond_largest<\/code> (but not largest<\/code>), it becomes the new second_largest<\/code>.<\/li>\n<\/ul>\n<\/li>\n\n\n\nsecond_largest<\/code>.<\/li>\n<\/ul>\n\n\n\nPython Solution:<\/h3>\n\n\n
\ndef find_second_largest(arr):\n if len(arr) < 2:\n return "Array size must be at least 2"\n\n # Use float('-inf') to avoid importing sys and handle all negatives\n largest = float('-inf')\n second_largest = float('-inf')\n\n for num in arr:\n if num > largest:\n second_largest = largest\n largest = num\n elif num > second_largest and num != largest:\n second_largest = num\n \n if second_largest == float('-inf'):\n return "No second largest element exists"\n else:\n return second_largest\n\n# How to handle input in the TCS environment\ntry:\n n = int(input().strip())\n arr = []\n for _ in range(n):\n arr.append(int(input().strip()))\n \n result = find_second_largest(arr)\n print(result)\n\nexcept ValueError:\n print("Invalid input")\n<\/pre><\/div>\n\n\n\n
list(set(arr))<\/code> , and then sort()<\/code>, grabbing the second-to-last item. Do not do this.<\/strong> Sorting takes O(N log N)<\/strong> time. This single-pass solution takes O(N)<\/strong> time and O(1)<\/strong> space, which is mandatory to clear hidden test cases for large arrays.<\/li>\n\n\n\nfloat('-inf')<\/code> instead of importing modules. It's cleaner, standard Python practice, and properly catches arrays filled entirely with negative integers (e.g., [-10, -40, -20]<\/code>).<\/li>\n\n\n\ninput().strip()<\/code> addition is crucial; TCS compilers often inject invisible trailing spaces that crash standard int()<\/code> conversions.<\/li>\n<\/ul>\n\n\n\n Question 2: Remove Duplicates from a Sorted Array<\/h3>\n\n\n\n
\n
write_index<\/code>) to keep track of the position where the next unique element should be placed. Initialize it to 1 (since the first element is always unique).<\/li>\n\n\n\ni<\/code>) to iterate through the array from the second element (i = 1<\/code>).<\/li>\n\n\n\ni<\/code> with the element at i-1<\/code>.<\/li>\n\n\n\narr[write_index]<\/code> and increment write_index<\/code>.<\/li>\n\n\n\ni<\/code>.<\/li>\n\n\n\nwrite_index<\/code> is your new length.<\/li>\n<\/ul>\n\n\n\nPython Solution:<\/h3>\n\n\n
\ndef remove_duplicates(arr):\n if not arr:\n return 0\n\n write_index = 1\n for i in range(1, len(arr)):\n if arr[i] != arr[i-1]:\n arr[write_index] = arr[i]\n write_index += 1\n \n return write_index\n\n# Example Input Handling\ntry:\n # Assuming input is space-separated integers on one line\n # Note: This input style might vary. Adapt as needed.\n input_line = input()\n arr = list(map(int, input_line.split()))\n \n new_length = remove_duplicates(arr)\n \n # Printing the modified array up to the new length\n for i in range(new_length):\n print(arr[i], end=" ")\n print() # for a newline at the end\n\nexcept (ValueError, IndexError):\n print("Invalid input format")\n\n<\/pre><\/div>\n\n\n\n
2. String Manipulation<\/a> Questions<\/h3>\n\n\n\n
\n
Question 3: Check if Two Strings are Anagrams<\/h3>\n\n\n\n
\n
Python Solution:<\/h3>\n\n\n
\ndef are_anagrams(str1, str2):\n s1 = str1.replace(" ", "").lower()\n s2 = str2.replace(" ", "").lower()\n\n if len(s1) != len(s2):\n return False\n\n char_counts = {}\n \n # Build frequency map for first string\n for char in s1:\n char_counts[char] = char_counts.get(char, 0) + 1\n \n # Check frequencies against the second string\n for char in s2:\n if char not in char_counts or char_counts[char] == 0:\n return False\n char_counts[char] -= 1\n \n return True\n\n# Input handling\ntry:\n string1 = input().strip()\n string2 = input().strip()\n\n if are_anagrams(string1, string2):\n print("Yes")\n else:\n print("No")\n \nexcept Exception:\n print("Invalid input")\n<\/pre><\/div>\n\n\n\n
.get(char, 0)<\/code> to avoid KeyError<\/code> exceptions when building the dictionary, which is a common pitfall in high-pressure testing environments.<\/li>\n<\/ul>\n\n\n\n3. Number Theory and Mathematical Problems<\/h3>\n\n\n\n
\n
Question 4: Check for a Prime Number<\/h3>\n\n\n\n
\n
Python Solution:<\/h3>\n\n\n
\nimport math\n\ndef is_prime(n):\n if n <= 1:\n return False\n if n == 2:\n return True\n if n % 2 == 0:\n return False\n \n # Iterate from 3 up to the square root of n, only checking odd numbers\n i = 3\n while i * i <= n:\n if n % i == 0:\n return False\n i += 2\n \n return True\n\n# Input handling\ntry:\n num = int(input())\n if is_prime(num):\n print("Prime")\n else:\n print("Not Prime")\n \nexcept ValueError:\n print("Invalid input. Please enter an integer.")\n\n<\/pre><\/div>\n\n\n\n
i * i <= n<\/strong><\/code> condition is an optimized way of checking up to the square root of N, executing in O(\u221aN)<\/strong> time. It cleverly avoids floating-point calculations which can occasionally cause precision issues in strict testing environments.<\/li>\n\n\n\n4. Advanced Topics (For Digital\/Prime Roles)<\/h3>\n\n\n\n
\n