Trianz Senior Software Engineer Interview Questions, Process, and Tips

Q1. Hashmap internal working
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Q2. Equals and hashcode
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Q1. Microservice design pattern
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Microservice design pattern focuses on breaking down a large application into smaller, independent services.
• Each microservice is responsible for a specific function or feature

• Communication between microservices is typically done through APIs

• Microservices can be developed, deployed, and scaled independently

• Examples: Netflix, Amazon, Uber
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Q2. Springboot annotation
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Q1. Difference between Scheduled script and Map reduce script?
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Scheduled script runs on a predefined schedule, while Map reduce script processes large datasets in parallel.
• Scheduled script is used for automating tasks at specific times, like sending reports daily at 8am.

• Map reduce script is used for processing large datasets by splitting them into smaller chunks and processing them in parallel.

• Scheduled script is typically used for routine tasks, while Map reduce script is used fo...read more
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Q2. Types of scripts in NetSuite.
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Types of scripts in NetSuite include SuiteScript, SuiteTalk, SuiteFlow, and SuiteBuilder.
• SuiteScript: JavaScript-based scripts for customizing NetSuite functionality.

• SuiteTalk: Web services integration for connecting NetSuite with external systems.

• SuiteFlow: Visual workflow tool for automating business processes.

• SuiteBuilder: Customization tool for modifying NetSuite forms, fields, and records.
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Q1. Questions on java , spring boot , containarisation tools, coding, SOLID principles
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5 coading questions were asked in it

Q1. Manegerial round
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Choose the Options in Javascript, HTML, CSS

Q1. ES6 concepts of javascript
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Q2. Core concepts of Reactjs
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Reactjs is a JavaScript library for building user interfaces.
• Component-based architecture

• Virtual DOM for efficient updates

• JSX for writing HTML in JavaScript

• State management with setState()

• Lifecycle methods like componentDidMount()
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Q1. Role discussion with Manager
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Q2. Salary discussion with HR
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Q1. About Self introduction and Core Functions of experiences
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Q2. Deep dive into Technologies what we have worked so far
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I have worked with a variety of technologies including Java, Python, SQL, AWS, Docker, and Kubernetes.
• Java

• Python

• SQL

• AWS

• Docker

• Kubernetes
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Q1. Ability to handle the product
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I have extensive experience in handling complex software products and have successfully led teams to deliver high-quality solutions.
• Led a team to successfully launch a new product feature within tight deadlines

• Managed the development of a large-scale software product from conception to release

• Collaborated with cross-functional teams to ensure product requirements were met

• Implemented agile methodologies to improve produ
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Q2. Customer or client interaction and project evaluations
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Q1. About Complete personal traits
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Q2. Compensation and Willingness
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Q1. There we a lot of question on Python basics 1. Iterators 2. Generator 3. List Comprehensions 4. Static Method, Class Method 5. Testing in Python - Pytest 6. Magic Methon 7. Try Except Else Block in Python ...read more
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Q2. DSA Questions 1. Balanced Parenthesis 2. String Compression - Check on Leetcode
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Q3. Basic SQL Count(*) query
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Q1. Memory Management in Python
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Memory management in Python involves automatic memory allocation and deallocation through garbage collection.
• Python uses automatic memory management through garbage collection to allocate and deallocate memory.

• Memory is managed using reference counting and a cycle-detecting garbage collector.

• Python's memory management is efficient for most use cases, but can lead to memory leaks if circular references are not handled p
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Q2. Garbage Collection in Python
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Garbage collection in Python is an automatic memory management process that helps in reclaiming memory occupied by objects that are no longer in use.
• Python uses a built-in garbage collector to manage memory automatically.

• The garbage collector in Python uses reference counting and a cycle-detecting algorithm to reclaim memory.

• Explicitly calling the 'gc.collect()' function can trigger garbage collection in Python.

• Garbage...read more
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Q3. Code a system to query an API, do multiprocessing and improve the efficiency
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Code a system to query an API, do multiprocessing and improve efficiency
• Use a library like requests in Python to query the API

• Implement multiprocessing using a library like multiprocessing or threading in Python

• Optimize efficiency by caching API responses or using asynchronous programming
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