Qualys Web Developer Interview Questions and Answers

The task was a Codility type

Q1. Implement readers-writer lock
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Basic question asked

Q1. Computer networking based question
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Q2. Dsa question based on graph and dp
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Q3. Based on operating system
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Q4. Function of oops
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Object-oriented programming paradigm that focuses on objects and classes for code organization and reusability.
• Encapsulation: bundling data and methods that operate on the data into a single unit (object)

• Inheritance: ability of a class to inherit properties and behavior from another class

• Polymorphism: ability to present the same interface for different data types
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Q1. Behavior question asked
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Q1. About user management
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Q2. Regarding Migration process
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Q1. Have you done any Complex workflow
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Q2. About issue types and screens
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Q1. How you handle pressure
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I handle pressure by prioritizing tasks, taking breaks, and seeking support when needed.
• I prioritize tasks based on urgency and importance

• I take short breaks to clear my mind and recharge

• I seek support from colleagues or supervisors when necessary

• I maintain a positive attitude and focus on solutions rather than problems
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Q2. How you priorities work
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Q1. Explain dependency injection, indexes in sql, SOLID principles.
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Dependency injection is a design pattern where dependencies are injected into a class rather than created within the class itself.
• Dependency injection helps in achieving loose coupling between classes.

• It allows for easier testing and maintenance of code.

• Example: Constructor injection, setter injection, and interface injection are common types of dependency injection.

• Indexes in SQL are used to improve the performance of...read more
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Q1. Difference between Procedure, Packages and functions.
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Procedures, Packages and Functions are all subprograms in PL/SQL with different characteristics.
• Procedures are subprograms that perform a specific task and may or may not return a value.

• Functions are subprograms that always return a value and can be used in SQL statements.

• Packages are a collection of related procedures, functions, variables, and other program constructs that can be used as a single unit.

• Packages provid...read more
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Q2. If table or view does not exist what does it mean
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It means that the table or view does not exist in the database.
• The query will fail and return an error message.

• The application may crash or behave unexpectedly.

• The table or view may have been deleted or renamed.

• Check the spelling and syntax of the query.

• Make sure the database connection is established and valid.
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Q3. Difference Between Views and Materialized Views
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Views are virtual tables while Materialized Views are physical tables.
• Views are created using SELECT statement while Materialized Views are created using CREATE MATERIALIZED VIEW statement.

• Views do not store data while Materialized Views store data.

• Views are updated dynamically while Materialized Views are updated manually or automatically based on refresh settings.

• Materialized Views are faster for read-heavy workloads...read more
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Q1. Details explanation about the projects and the concepts what we used.
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Q1. SOLID principles
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Q2. Microservice Architecture and Kafka
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Q1. Explain random forest
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Random forest is an ensemble learning method that builds multiple decision trees and merges them to improve accuracy and prevent overfitting.
• Random forest is a type of ensemble learning method.

• It builds multiple decision trees during training.

• Each tree is built using a subset of the training data and a random subset of features.

• The final prediction is made by averaging the predictions of all the individual trees.

• Random...read more
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Q2. What is boosting
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Boosting is a machine learning ensemble technique where multiple weak learners are combined to create a strong learner.
• Boosting is an iterative process where each weak learner is trained based on the errors of the previous learners.

• Examples of boosting algorithms include AdaBoost, Gradient Boosting, and XGBoost.

• Boosting is used to improve the accuracy of models and reduce bias and variance.
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