AH INFOTECH Software Engineer Interview Questions and Answers

3 questions, medium hard

Q1. Greedy Algorithm, simple jumps question, easily approachable by greedy algorithm
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Q2. Binary Search, simple array based
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Q1. DBMS, Projects, SQL Queries
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Q2. 2 coding questions
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Q1. What are the modules worked on Facets?
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Q2. What is Dental claim processing?
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Q1. What is your work experience
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Q2. Is working timing flexible
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Initially, they shortlist the candidates and group them into batches of 15 students. During this process, they conduct a group discussion (GD) in which each student has 3 minutes to think, followed by an opportunity to describe their points in 2 to 3 minutes.

Q1. Types of Triggers in ADF
Ans. 
Types of triggers in Azure Data Factory include schedule, tumbling window, event-based, and manual.
• Schedule trigger allows you to run pipelines on a specified schedule

• Tumbling window trigger runs pipelines at specified time intervals

• Event-based trigger runs pipelines based on events like file arrival or HTTP request

• Manual trigger allows you to manually trigger pipeline runs
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Coding questions on Javascript

Q1. Coding questions were asked
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Q1. IAM & PAM Operations
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Q2. Related to Sailpoint
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45 questions were asked

3 questions were asked one from SQL and 2 from java

Q1. Oops concepts and java basics
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There were 13 MCQ questions on DSA, 17 MCQ aptitude questions, and 2 coding questions.

Q1. There's a string s1,s2 and s3. s1 and s2 are divided into n and m parts respectively. check if, after interleaving strings s1 and s2, we get s3 as one of the answers.
Ans. 
Check if after interleaving strings s1 and s2, we get s3 as one of the answers.
• Create a recursive function to check all possible interleavings of s1 and s2

• Check if the current interleaving matches s3

• Return true if a valid interleaving is found, false otherwise
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Q2. Difference between cluster and non-cluster indexing. Do you know about database indexing?
Ans. 
Cluster indexing physically reorders the data on disk to match the index, while non-cluster indexing does not.
• Cluster indexing physically reorders the data on disk to match the index structure, leading to faster retrieval of data.

• Non-cluster indexing creates a separate data structure that points to the actual data, which may result in slower retrieval times.

• Cluster indexing is typically used in primary keys, while non-...read more
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Q3. Difference between stack and heap memory.
Ans. 
Stack memory is used for static memory allocation and follows a Last In First Out (LIFO) structure, while heap memory is used for dynamic memory allocation and has a more flexible structure.
• Stack memory is limited in size and is typically faster to access compared to heap memory.

• Variables stored in stack memory have a fixed size determined at compile time, while variables in heap memory can have a size determined at ru...read more
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Q4. What is a stable sort?
Ans. 
A stable sort is a sorting algorithm that preserves the relative order of equal elements in the sorted output.
• Stable sorts are useful when the original order of equal elements needs to be maintained.

• Examples of stable sorting algorithms include Merge Sort, Bubble Sort, and Insertion Sort.

• In a stable sort, if two elements have the same key value, their relative order in the original array is preserved in the sorted arra
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Q5. What's the time complexity of insertion in a hashmap?
Ans. 
Time complexity of insertion in a hashmap is O(1).
• Insertion in a hashmap has a constant time complexity of O(1) on average.

• This is because hashmaps use a hashing function to determine the index where the key-value pair should be stored.

• Even in the worst-case scenario, where there are collisions, the time complexity is still O(1) due to techniques like chaining or open addressing.

• Example: Inserting a key-value pair into...read more
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Q6. What is hashing?
Ans. 
Hashing is a process of converting input data into a fixed-size string of bytes using a hash function.
• Hashing is used to securely store passwords by converting them into a hash value.

• Hashing is used in data structures like hash tables to quickly retrieve data based on a key.

• Common hash functions include MD5, SHA-1, and SHA-256.
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