10 GlobalLogic Interview Questions and Answers

GlobalLogic is a leading digital product engineering services company that blends design, complex engineering, and data expertise to help clients transform their businesses. Known for its innovative solutions and cutting-edge technology, GlobalLogic collaborates with companies across various industries to create impactful digital products and experiences. With a strong emphasis on agile methodologies and a global talent pool, the company is at the forefront of driving digital transformation.

This article provides a curated selection of interview questions tailored to help you prepare for a role at GlobalLogic. By familiarizing yourself with these questions and their answers, you will gain a deeper understanding of the skills and knowledge areas that are crucial for success in this dynamic and fast-paced environment.

GlobalLogic Interview Questions and Answers

1. How do you ensure code quality and maintainability in a project?

Ensuring code quality and maintainability in a project involves several best practices:

• Code Reviews: Regular reviews help catch bugs early, ensure adherence to standards, and facilitate knowledge sharing. They also provide an opportunity for feedback and improvement.
• Automated Testing: Implementing unit, integration, and end-to-end tests ensures that the code behaves as expected. Automated testing frameworks can run these tests frequently, catching regressions early.
• Adherence to Coding Standards: Following a consistent style and industry guidelines makes the code more readable. Tools like linters can automatically check for style violations.
• Continuous Integration/Continuous Deployment (CI/CD): Setting up CI/CD pipelines ensures that code changes are automatically tested and deployed, maintaining a stable codebase.
• Documentation: Comprehensive documentation, including inline comments and user guides, helps new developers understand the codebase quickly.
• Refactoring: Regularly improving code structure without changing functionality helps maintain quality and adaptability.
• Modular Design: Designing code in a modular fashion, with well-defined interfaces, makes it easier to understand, test, and maintain.

2. Explain how you would optimize a database query in an application.

Optimizing a database query involves strategies to ensure efficient application performance:

• Indexing: Indexes speed up data retrieval. Creating indexes on frequently used columns helps the database locate rows quickly.
• Query Optimization: Writing efficient SQL queries is essential. This includes selecting necessary columns, using appropriate JOINs, and minimizing subqueries.
• Database Schema Design: A well-designed schema impacts performance. Normalization reduces redundancy, while denormalization can improve performance in read-heavy applications.
• Caching: Implementing caching mechanisms reduces database load by storing frequently accessed data in memory.
• Connection Pooling: Efficiently managing database connections improves performance by reusing connections.
• Regular Maintenance: Performing tasks like updating statistics and rebuilding indexes helps maintain optimal performance.

3. How would you handle version control in a multi-developer project?

Handling version control in a multi-developer project involves best practices to ensure smooth collaboration. The primary tool is a Version Control System (VCS) like Git, which tracks changes and manages code versions.

Key strategies include:

• Branching Strategy: Implementing a strategy like Git Flow or trunk-based development helps manage feature development and releases.
• Code Reviews: Conducting regular reviews through pull requests ensures code quality and consistency.
• Continuous Integration (CI): Integrating CI tools automates testing and integration, ensuring new changes don’t break the codebase.
• Commit Messages: Writing clear messages helps track changes and understand project history.
• Conflict Resolution: Regularly pulling changes and resolving conflicts promptly helps avoid integration issues.

4. How do you ensure security in a web application?

Ensuring security in a web application involves implementing various strategies to protect against vulnerabilities:

• Input Validation: Validate and sanitize user inputs to prevent injection attacks like SQL injection and XSS.
• Authentication: Implement strong mechanisms, such as multi-factor authentication, to verify user identity.
• Authorization: Ensure proper checks are in place to restrict access based on roles and permissions.
• Encryption: Use encryption to protect data in transit and at rest.
• Secure Session Management: Implement practices like using secure cookies and setting session timeouts.
• Regular Security Audits: Conduct audits and assessments to identify and address potential issues.
• Security Headers: Use headers like Content Security Policy to protect against attacks.
• Dependency Management: Regularly update dependencies to protect against known vulnerabilities.
• Logging and Monitoring: Implement logging and monitoring to detect and respond to suspicious activities.

5. How would you design a scalable system for a client?

Designing a scalable system involves principles to ensure the system can handle increased load:

• Load Balancing: Distribute traffic across multiple servers to prevent bottlenecks.
• Database Optimization: Use techniques like sharding, indexing, and caching to improve performance.
• Microservices Architecture: Break down the application into smaller, independent services for easier scaling.
• Auto-Scaling: Implement mechanisms to automatically adjust resources based on demand.
• Caching: Use caching to store frequently accessed data, reducing database load.
• Asynchronous Processing: Offload tasks to background processes to keep the application responsive.
• Monitoring and Logging: Implement monitoring and logging to track performance and identify issues.

6. Explain how you would integrate third-party APIs into a project.

Integrating third-party APIs into a project involves several steps:

1. Understanding the API Documentation: Thoroughly read and understand the API documentation, including endpoints and response formats.

2. Setting Up Authentication: Follow the authentication process outlined in the documentation to ensure secure access.

3. Making API Requests: Construct appropriate HTTP requests with necessary headers and parameters.

4. Handling Responses: Parse response data, handle errors, and process information as needed.

Example:

import requests

def get_weather(city, api_key):
    url = f"http://api.openweathermap.org/data/2.5/weather?q={city}&appid={api_key}"
    response = requests.get(url)
    
    if response.status_code == 200:
        data = response.json()
        return data
    else:
        return None

api_key = 'your_api_key_here'
city = 'London'
weather_data = get_weather(city, api_key)

if weather_data:
    print(weather_data)
else:
    print("Failed to retrieve data")

7. How do you approach DevOps practices in your projects?

DevOps practices streamline development and operations, ensuring faster delivery and higher quality. My approach involves several principles:

• Continuous Integration (CI): Automatically integrate code changes into a shared repository using tools like Jenkins or Travis CI.
• Continuous Deployment (CD): Automatically deploy code to production or staging environments, reducing time between writing and deploying code.
• Infrastructure as Code (IaC): Manage infrastructure through scripts using tools like Terraform or Ansible.
• Monitoring and Logging: Use tools like Prometheus or ELK Stack to collect and analyze metrics and logs.
• Collaboration and Communication: Use tools like Slack or Jira to maintain clear communication and manage tasks efficiently.

8. How do you handle technical debt in a long-term project?

Handling technical debt in a long-term project involves several strategies:

• Identification and Documentation: Identify and document instances of technical debt through reviews and automated tools.
• Prioritization: Prioritize debt based on its impact and the effort required to address it.
• Regular Refactoring: Incorporate regular refactoring sessions to gradually reduce debt.
• Automated Testing: Implement automated testing to catch issues early and prevent new debt.
• Code Reviews: Conduct regular reviews to maintain code quality and prevent new debt.
• Technical Debt Backlog: Maintain a separate backlog for debt items and review it regularly.
• Stakeholder Communication: Communicate the importance of addressing debt to stakeholders.

9. Describe a time when you had to refactor a large codebase. What was your approach?

Refactoring a large codebase requires careful planning. I once refactored a legacy codebase by conducting a thorough analysis to understand its structure and identify areas for improvement. I prioritized areas based on their impact on performance and maintainability, creating a detailed plan reviewed by stakeholders. During refactoring, I made incremental changes, used automated tests to ensure functionality, and improved documentation for future developers.

10. Write a function to solve the “N-Queens” problem.

The N-Queens problem can be solved using backtracking. The idea is to place queens one by one in different columns, starting from the leftmost column. When placing a queen, we check for clashes with already placed queens. If a clash is found, we backtrack and try the next position. This process continues until all queens are placed on the board.

def solve_n_queens(n):
    def is_safe(board, row, col):
        for i in range(col):
            if board[row][i] == 1:
                return False
        for i, j in zip(range(row, -1, -1), range(col, -1, -1)):
            if board[i][j] == 1:
                return False
        for i, j in zip(range(row, n, 1), range(col, -1, -1)):
            if board[i][j] == 1:
                return False
        return True

    def solve(board, col):
        if col >= n:
            return True
        for i in range(n):
            if is_safe(board, i, col):
                board[i][col] = 1
                if solve(board, col + 1):
                    return True
                board[i][col] = 0
        return False

    board = [[0] * n for _ in range(n)]
    if not solve(board, 0):
        return []
    return board

# Example usage:
n = 4
solution = solve_n_queens(n)
for row in solution:
    print(row)