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I appeared for an interview before Mar 2023.
Coding test, on C, around 1 hr, on teams
Top trending discussions
I tend to be overly critical of my own work, which can slow down my progress and decision-making.
I often spend too much time refining code, aiming for perfection, which can delay project timelines.
In team settings, I sometimes hesitate to share my ideas, fearing they may not meet high standards.
I have learned to set deadlines for myself to ensure I complete tasks without getting stuck in analysis paralysis.
I applied via Walk-in and was interviewed before Sep 2020. There were 5 interview rounds.
posted on 16 Oct 2024
posted on 28 Jun 2024
Design patterns in C++ are reusable solutions to common problems in software design.
Design patterns help in creating flexible, maintainable, and scalable code.
Examples of design patterns in C++ include Singleton, Factory, Observer, and Strategy.
Each design pattern has its own purpose and can be applied in different scenarios.
Understanding design patterns can improve code quality and efficiency.
I applied via LinkedIn and was interviewed in Nov 2023. There was 1 interview round.
A virtual function is a member function in a base class that can be overridden in derived classes, enabling polymorphism.
Enables dynamic binding, allowing the program to decide at runtime which function to call.
Declared using the keyword 'virtual' in the base class.
Example: In a base class 'Shape', a virtual function 'draw()' can be overridden in derived classes like 'Circle' and 'Square'.
Supports polymorphism, allowin...
Polymorphism allows objects to be treated as instances of their parent class, enabling method overriding and overloading.
Types of polymorphism: compile-time (method overloading) and runtime (method overriding).
Example of method overloading: multiple functions with the same name but different parameters.
Example of method overriding: a subclass providing a specific implementation of a method defined in its superclass.
Pol...
posted on 1 Jun 2024
posted on 12 Sep 2024
Preprocessing raw data involves cleaning, transforming, and organizing data to make it suitable for analysis.
Remove any irrelevant or duplicate data
Handle missing values by imputation or deletion
Normalize or standardize numerical data
Encode categorical variables using techniques like one-hot encoding
Feature scaling for machine learning algorithms
Perform text preprocessing like tokenization and stemming
Specify the existing solution by documenting its architecture, components, technologies used, and any modifications made.
Document the architecture of the solution, including high-level components and their interactions
List the technologies used in the solution, such as programming languages, frameworks, and databases
Describe any modifications or customizations made to the existing solution
Include any performance metric...
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Bosch
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