Siemens Building Technologies Software Developer Interview Questions and Answers

Q1. Just based on resume
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Q1. Tell me about your projects
Ans. 
I have worked on various projects including web development, mobile app development, and data analysis.
• Developed a web application using React and Node.js for a client in the e-commerce industry

• Created a mobile app using Flutter for tracking daily expenses

• Performed data analysis on customer feedback data using Python and SQL
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Q2. He gave me a DSA question.
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Q3. Asked about oops concepts
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Q4. Asked about dbms
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Q1. Good URI design
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Q2. Accessing id parameter in URL
Ans. 
Accessing id parameter in URL involves parsing the URL and extracting the id value.
• Use the window.location object to access the URL of the current page.

• Parse the URL using methods like split() or URLSearchParams to extract the id parameter.

• Example: If the URL is 'http://example.com/page?id=123', you can access the id value by parsing the URL.
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Q1. Salary expectations
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Q2. Plan of growing up technically
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30 min 30 ques and gaming ques

Q1. What is ML and AI in your project?
Ans. 
ML and AI are used in our project to analyze user behavior and provide personalized recommendations.
• ML algorithms are used to analyze user data and predict user preferences.

• AI is used to provide personalized recommendations based on the analysis of user behavior.

• Examples include recommendation systems for e-commerce websites and personalized content suggestions on streaming platforms.
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Q2. What is lagging concept and more?
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Lagging concept refers to a concept or idea that is behind or not up to date compared to current standards or practices.
• Refers to outdated technology or methods in software development

• Can lead to inefficiencies, bugs, or security vulnerabilities

• Examples include using deprecated libraries or not following best practices for coding
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Q1. 1. Basic OOP Concepts 2. Difference between structure and class in terms of constructor 3. Can members of structure be defined as private 4. What's lambda function and it's real life use case 5. Difference...read more
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Q2. 6. What's O(n) in time and space complexity
Ans. 
O(n) refers to linear time and space complexity.
• O(n) means that the time or space required by an algorithm grows linearly with the size of the input.

• It implies that the algorithm's performance is directly proportional to the input size.

• For example, if an algorithm takes 10 seconds to process 100 elements, it would take 20 seconds to process 200 elements.

• O(n) complexity is considered efficient and desirable in most case
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Basic coding, duration 1hr

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