Technical Associate Consultant

Oracle

Let's explore some common data structures and algorithms. I'd like you to describe the following: Arrays: Explain what an array is and how it stores data. What are the advantages and disadvantages of using arrays? Provide an example of how you would use an array in a real-world scenario. For instance, how could you use an array to store a list of student names or inventory items? Linked Lists: What is a linked list, and how does it differ from an array? Describe the different types of linked lists (singly, doubly, circular). Walk me through the process of inserting a node into a singly linked list. What are the time complexities of insertion and deletion in a linked list? Stacks and Queues: Explain the concepts of stacks and queues. What are the key differences between them? (LIFO vs FIFO). Give an example of a situation where you would prefer to use a stack over a queue, and vice versa. How could you implement a queue using two stacks? Trees: Describe what a tree data structure is. What are the different types of trees (binary tree, binary search tree, etc.)? Explain the properties of a binary search tree. How does it enable efficient searching? How would you traverse a binary tree (in-order, pre-order, post-order)? Provide examples. Sorting Algorithms: Explain the concept of sorting algorithms. Describe the following sorting algorithms: Bubble Sort, Insertion Sort, Merge Sort, and Quick Sort. What are the time complexities of each of these sorting algorithms in the best, average, and worst-case scenarios? Which sorting algorithm would you choose for a nearly sorted array, and why? Searching Algorithms: Describe the difference between linear search and binary search. When is binary search applicable, and what are its advantages? What is the time complexity of linear search and binary search? For each of these, please be prepared to discuss their real-world applications, time and space complexities, and trade-offs.

Oracle

Let's design a URL shortening service like bit.ly. Consider the following: Functional Requirements: The service should accept a long URL and generate a unique short URL. Users should be able to access the original URL by visiting the shortened URL. The service should track click statistics for each shortened URL. Non-Functional Requirements: The service should be highly available and scalable to handle a large number of URL shortening and redirection requests. Shortened URLs should be generated quickly. The system should be fault-tolerant. Considerations: How would you handle URL collisions (when the same short URL is generated for different long URLs)? How would you design the data storage? How would you optimize the system for read-heavy traffic (redirections)? How would you implement analytics and track clicks? Explain the architectural components, data model, algorithms, and scaling strategies you would use to build such a system. Provide specific examples for URL encoding and decoding. For example, how would you encode https://www.example.com/very/long/url/path into something like bit.ly/xyz123?

Oracle

Let's discuss your strengths and weaknesses. Could you provide specific examples that highlight both your key strengths and areas where you are actively working to improve? Think about situations where your strengths significantly contributed to a positive outcome, and conversely, instances where your weaknesses presented a challenge. For instance, perhaps you excel at quickly learning new technologies, as demonstrated by your successful implementation of a novel machine learning algorithm for a recent project, resulting in a 15% performance improvement. On the other hand, you might find public speaking challenging, and you are addressing this by joining a Toastmasters club and practicing presentations regularly. Providing concrete examples like these will give me a better understanding of your capabilities and your commitment to continuous self-improvement.