KPIT Technologies C Programming with DSA Interview Questions & Answers
Curated interview practice questions with answers. These are practice scenarios, not a verified list of past interview questions.
About KPIT Technologies hiring for C Programming with DSA roles
KPIT Technologies is a Pune-based software integration partner for the automotive and mobility industry. It works with vehicle makers and suppliers on embedded software, autonomous driving, electric powertrains, connected vehicles and AUTOSAR-based development. In India it hires software, embedded, testing and validation engineers, and many roles suit candidates from electronics, electrical, mechanical and computer science backgrounds with an interest in vehicles.
For C Programming with DSA roles, this KPIT Technologies practice set focuses most on Sorting, Searching and Dynamic Programming (6), Linked Lists (6), Pointers and Memory Management (5), C Basics, Data Types and Operators (4). It has 12 easy, 17 medium, 1 hard questions, so you can start easy and work up to the harder ones.
Company type
IT services
Headquarters
Pune, India
Main India offices
Pune, Bengaluru
KPIT Technologies C Programming with DSA interview process
Online assessment (aptitude + programming)
Technical interview
Managerial round
HR round
Typical pattern based on public candidate experiences. Rounds vary by role, team and year.
Solved for KPIT TechnologiesStart practicing
3 QUESTIONS FREESign up to unlock the full question bank and track your progress.Unlock every question and answer, then continue practising company-wise and package-wise.
✓ 3 questions free • Unlock the rest in seconds
01
You must schedule the maximum number of non-overlapping meetings in one room. What algorithm do you use?
This is activity selection, solved greedily. Sort meetings by end time, then pick each meeting whose start is not earlier than the end of the last picked one. Choosing the earliest finishing meeting always leaves the most room for the rest, which can be proven by an exchange argument. Sorting dominates, giving O(n log n) time.
A memory leak happens when dynamically allocated memory is never freed and the last pointer to it is lost, so the program keeps growing in memory use. Long running services and embedded systems eventually fail. Detect leaks with Valgrind memcheck, AddressSanitizer with LeakSanitizer or allocation tracking wrappers. Prevent them with clear ownership rules and a single cleanup path per function.
03
What is the difference between a macro and an inline function?
A macro is plain text substitution by the preprocessor, with no type checking, and arguments may be evaluated more than once, so SQUARE(i++) misbehaves. An inline function is a real function with type checks and single evaluation of arguments, which the compiler may expand in place for speed. Prefer static inline functions and use macros only for things like conditional compilation.
Adding an integer to a pointer moves it by that many elements, not bytes, so p + 1 on an int pointer advances by sizeof(int). Subtracting two pointers into the same array gives the number of elements between them as ptrdiff_t. Arithmetic is valid only within an array or one past its end; going further is undefined behaviour. Void pointer arithmetic is not allowed in standard C.
05
Write a function that swaps two integers using pointers.
Pass addresses so the function can modify the caller's variables.
void swap(int *a, int *b) {
int temp = *a;
*a = *b;
*b = temp;
}
int main(void) {
int x = 3, y = 7;
swap(&x, &y);
printf("%d %d\n", x, y); // 7 3
return 0;
}
C passes everything by value, so pointers are needed to change caller data.
A null pointer holds NULL and points to nothing; dereferencing it crashes. A dangling pointer points to memory that has been freed or a local that went out of scope. A wild pointer is uninitialised and holds a random address. A void pointer is a generic pointer that can hold any object address but must be cast before dereferencing, as malloc returns void *.
Backtracking builds a solution step by step and abandons a path as soon as it cannot lead to a valid answer, then tries the next option. It explores a search tree with pruning. Examples are N-Queens, Sudoku, generating permutations and subsets, and maze path finding. Time can be exponential, so good pruning and ordering choices matter a lot.
08
You need to find whether any two numbers in an unsorted array sum to a target. Compare approaches.
Brute force checks all pairs in O(n squared). Sorting first with qsort and then using two pointers takes O(n log n) time and O(1) extra space but loses original indexes. A hash set gives O(n) time with O(n) memory; in C you would implement a simple open addressing table. Choose based on size, memory limits and whether indexes must be returned.
BFS explores level by level using a queue and finds the shortest path in unweighted graphs. DFS goes deep along one path using recursion or a stack, and suits cycle detection, topological sort, connected components and backtracking. Both run in O(V + E). BFS may use more memory on wide graphs, while recursive DFS can overflow the call stack on very deep graphs.
10
Why is gets() dangerous and what should you use instead?
gets() reads a line into a buffer without knowing its size, so long input overflows the buffer and can be used for code execution attacks. It was removed in C11. Use fgets(buf, sizeof buf, stdin), which stops at the buffer size and keeps the newline, then strip the newline if needed. For formatted input, give scanf field widths like %19s.
Use an overflow safe midpoint.
int binarySearch(const int *a, int n, int target) {
int lo = 0, hi = n - 1;
while (lo <= hi) {
int mid = lo + (hi - lo) / 2;
if (a[mid] == target) return mid;
if (a[mid] < target) lo = mid + 1;
else hi = mid - 1;
}
return -1;
}
Time O(log n). The array must be sorted in ascending order.
Recursion is when a function calls itself on a smaller subproblem until reaching a base case. It expresses tree traversal, divide and conquer and backtracking naturally. Risks are stack overflow when depth is large, repeated work when subproblems overlap, like naive Fibonacci, and function call overhead. Use memoisation for overlapping subproblems and iterative versions when depth may be huge.
14
You need to implement a queue using two stacks. How does it work and what is its cost?
Use an in-stack for enqueue and an out-stack for dequeue. Enqueue always pushes to the in-stack. Dequeue pops from the out-stack, and only when it is empty moves all elements from the in-stack to it, which reverses their order so the oldest comes out first. Each element moves at most twice, so operations are O(1) amortised even though a single dequeue can be O(n).
15
What is a circular linked list and where is it used?
In a circular linked list the last node points back to the first, so there is no NULL end. You can start at any node and visit all nodes, and keeping only a tail pointer gives O(1) access to both ends. It is used in round-robin CPU scheduling, multiplayer turn order and circular buffers. Traversal loops must stop when they return to the starting node.
16
Insert a node at the end of a singly linked list using a double pointer.
A pointer to pointer handles the empty list without special cases.
int append(Node **head, int value) {
Node *n = malloc(sizeof *n);
if (!n) return -1;
n->data = value;
n->next = NULL;
while (*head) head = &(*head)->next;
*head = n;
return 0;
}
Call it as append(&head, 5). Keep a tail pointer if you append often.
17
What is the time complexity of common linked list operations?
Access or search by value is O(n). Insert or delete at the head is O(1). Insert at the tail is O(1) if you keep a tail pointer, otherwise O(n). Deleting a given node is O(1) in a doubly linked list but O(n) in a singly linked list, since you must find the previous node. Finding length is O(n) unless you store a count.
18
What is the difference between break and continue in C?
break immediately exits the nearest enclosing loop or switch statement, and execution continues after it. continue skips the rest of the current loop iteration and moves to the next one; in a for loop the update expression still runs. In nested loops both affect only the innermost loop, so a flag or goto is needed to exit outer loops early.
19
Rotate an array to the right by k positions in O(n) time and O(1) space.
Use three reversals.
void rev(int *a, int l, int r) {
while (l < r) { int t = a[l]; a[l++] = a[r]; a[r--] = t; }
}
void rotate(int *a, int n, int k) {
k %= n;
if (k == 0) return;
rev(a, 0, n - 1);
rev(a, 0, k - 1);
rev(a, k, n - 1);
}
For 1 2 3 4 5 with k = 2 the result is 4 5 1 2 3.
The master theorem gives the time complexity of divide and conquer recurrences of the form T(n) = aT(n/b) + f(n). Compare f(n) with n to the power log base b of a. For merge sort, a = 2, b = 2 and f(n) = n, which match, giving O(n log n). For binary search, a = 1 and b = 2 with constant work, giving O(log n). It does not cover every recurrence.
A monotonic stack keeps elements in increasing or decreasing order by popping elements that break the order before pushing a new one. Each element is pushed and popped at most once, so problems run in O(n). It solves next greater element, daily temperatures, stock span and largest rectangle in a histogram, which would otherwise need nested loops.
22
What is the difference between fseek, ftell and rewind?
fseek(fp, offset, origin) moves the file position relative to SEEK_SET, SEEK_CUR or SEEK_END. ftell(fp) returns the current position as a long. rewind(fp) moves to the start and clears error flags. Together they let you find file size, jump to a record in a fixed-size record file or re-read data. For very large files, use fseeko and ftello with off_t.
23
Write C code to count the number of set bits in an integer.
Brian Kernighan's trick clears the lowest set bit each step.
int countBits(unsigned int n) {
int count = 0;
while (n) {
n &= n - 1;
count++;
}
return count;
}
It runs once per set bit. GCC and Clang also offer __builtin_popcount(n), which uses a CPU instruction when available.
24
How do you find the middle of a linked list in one pass?
Use slow and fast pointers starting at the head. Move slow by one node and fast by two nodes each step. When fast reaches the end or NULL, slow is at the middle. For an even number of nodes this gives the second middle; start fast at head->next to get the first middle instead. It takes O(n) time and O(1) space.
25
A function to insert at the head does not change the list in main. Why?
C passes arguments by value, so the function receives a copy of the head pointer; changing that copy does not affect main. Pass a pointer to the head, as in void push(Node **head, int x), and assign *head = newNode, or return the new head and assign it in the caller with head = push(head, x). This is a very common fresher interview mistake.
26
What is the difference between stack and heap allocation?
Stack memory holds local variables, is allocated and freed automatically when functions enter and return, and is very fast but limited in size, often 1 to 8 MB. Heap memory is allocated with malloc and freed manually, can be large and outlive the function, but is slower and can fragment or leak. Large or variable sized data and data that must outlive a function belong on the heap.
27
What is typedef and how is it used with structures?
typedef creates an alias for a type. typedef struct Node { int data; struct Node *next; } Node; lets you write Node *head instead of struct Node *head. It is also useful for function pointer types and platform specific types. Some style guides avoid hiding pointers behind typedefs because it makes ownership and const usage less clear.
From low to high address, a typical process has the text segment holding code, the initialised data segment for globals and statics with values, BSS for uninitialised or zero globals, the heap growing upward for malloc memory, and the stack growing downward for function frames and local variables. Knowing this helps explain stack overflow, memory leaks and where variables live.
29
Why is a dummy or sentinel node useful in linked list code?
A dummy node placed before the real head removes special cases for an empty list or for inserting and deleting at the head, because every real node then has a previous node. Code for merging lists, removing elements and partitioning becomes shorter and less error prone. At the end, return dummy.next as the new head. It costs one extra node.
Dynamic programming solves problems that have overlapping subproblems and optimal substructure by storing results of subproblems instead of recomputing them. Top-down memoisation caches recursive calls, while bottom-up tabulation fills a table iteratively. Classic examples are Fibonacci, 0/1 knapsack, longest common subsequence, coin change and edit distance. Defining the state and transition clearly is the hardest part.
Tips to crack the KPIT Technologies C Programming with DSA interview
Revise C programming, pointers, embedded systems basics and microcontroller concepts, which are central to many KPIT engineering roles.
Learn the basics of automotive software such as AUTOSAR, CAN communication and electric vehicle components to stand out in discussions.
Prepare to explain any vehicle, robotics or embedded project in detail, including hardware used and how you tested it.
Keep a one-minute story ready for every project on your CV: problem, your part, tools, result.
Practise the hard questions on this page aloud; KPIT Technologies interviewers usually ask follow-ups on your first answer.
Frequently asked questions
How many rounds are there in the KPIT Technologies C Programming with DSA interview?
Candidates usually go through 4 stages: Online assessment (aptitude + programming); Technical interview; Managerial round; HR round. The exact rounds change with the role, team, location and your experience, so confirm the process with the recruiter.
Which topics should I prepare for the KPIT Technologies C Programming with DSA interview?
This practice set leans on Sorting, Searching and Dynamic Programming (6), Linked Lists (6), Pointers and Memory Management (5), C Basics, Data Types and Operators (4). Revise those first, then practise explaining one or two of your own projects end to end, because most KPIT Technologies interviewers ask you to walk through real work.
Are these the exact questions asked at KPIT Technologies?
No. These are curated practice questions that match the skills and difficulty usually tested in it services interviews like KPIT Technologies's. They are not a leaked or verified list of past questions.
Where does KPIT Technologies hire C Programming with DSA professionals in India?
KPIT Technologies has large teams in Pune, Bengaluru. Openings and locations change often, so check the KPIT Technologies careers page and filter by city and experience.
C Programming with DSA questions for similar companies