Autodesk Interview Questions and Answers

Q1. Write a program which will take string and number of occurrences as a input. Find a character with same occurrences count in single interation.(multiples cases around this, not able to recall)
Ans. 
Program to find a character with same occurrences count in a string in a single iteration.
• Iterate through the string and keep track of character occurrences in a hashmap.

• Check for characters with the same occurrence count in the hashmap.

• Return the first character found with the same occurrence count.
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Q2. Graph traversal
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Q1. System design components discussed in detail with different scenarios
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Q1. Prepare standard conflict manager round questions like conflict resolution, team leading experience, best work delivered, standard practices etc
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Q1. Tell me about yourself
Ans. 
I am a dedicated SDET with a passion for automation testing and ensuring software quality.
• Experienced in creating and executing automated test scripts using tools like Selenium and JUnit

• Proficient in programming languages such as Java and Python

• Skilled in identifying and reporting software defects

• Strong understanding of software development lifecycle and agile methodologies
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Q2. Why you want to join autodesk
Ans. 
I want to join Autodesk because of its innovative technology and global impact in the design industry.
• Autodesk is a leader in providing cutting-edge software solutions for design and engineering professionals

• I am excited about the opportunity to work on challenging projects and contribute to the company's success

• I admire Autodesk's commitment to sustainability and diversity in the workplace
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Q1. Work experinece
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I have extensive experience in software development and testing, focusing on automation and quality assurance.
• Developed automated test scripts using Selenium and Java, improving test coverage by 40%.

• Collaborated with developers to identify and resolve bugs early in the development cycle.

• Implemented CI/CD pipelines using Jenkins, reducing deployment time by 30%.

• Conducted performance testing using JMeter, identifying bot...read more
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Q2. Behavioral Questions
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Q3. Scenario based questions
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Q1. Javascript basic difference between var let.
Ans. 
var is function scoped, let is block scoped in JavaScript.
• var is function scoped, let is block scoped

• var can be redeclared, let cannot be redeclared

• let is recommended for use over var in modern JavaScript
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Q2. OOPS concept of java
Ans. 
OOPS concept of Java refers to Object-Oriented Programming principles like inheritance, encapsulation, polymorphism, and abstraction.
• Inheritance: Allows a class to inherit properties and behavior from another class.

• Encapsulation: Bundling data and methods that operate on the data into a single unit.

• Polymorphism: Ability to present the same interface for different data types.

• Abstraction: Hiding the implementation detail...read more
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How you handle a difficult situation

Q1. Kth largest element
Ans. 
Find the Kth largest element in an unsorted array using efficient algorithms.
• Use a min-heap of size K to keep track of the largest K elements.

• Example: For array [3, 2, 1, 5, 6, 4] and K=2, the 2nd largest is 5.

• Alternatively, sort the array and access the element at index len(array) - K.

• Example: Sorting [3, 2, 1, 5, 6, 4] gives [1, 2, 3, 4, 5, 6], 2nd largest is 5.

• Quickselect algorithm can also be used for average O(n) ...read more
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Q2. Peak Element in an Array
Ans. 
A peak element in an array is an element that is greater than its neighbors.
• A peak element can be at the beginning, end, or middle of the array.

• Example: In [1, 3, 20, 4, 1], 20 is a peak element.

• If an array has only one element, that element is a peak.

• Multiple peak elements can exist in an array.

• To find a peak, compare each element with its neighbors.
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Q3. Bagging vs boosting.
Ans. 
Bagging and boosting are ensemble techniques that improve model performance by combining multiple learners.
• Bagging (Bootstrap Aggregating) reduces variance by averaging predictions from multiple models trained on random subsets of data.

• Example of bagging: Random Forest, which builds multiple decision trees and averages their predictions.

• Boosting sequentially trains models, each focusing on the errors of the previous on...read more
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Q1. Questions on REST APIs, Python, 2 Coding questions medium, Web scrapping, JSON handling
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Q2. Questions in depth on AWS services
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Q1. Same as on round1
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Q2. Same as on round1 and in depth
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Q1. Same as on round 1
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Q2. Same as on round and in depth
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Q1. Questions related to ETA on tasks, architectures on aws
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Q2. More aws questions
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