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Computer science concepts
Explore algorithm tutorials, coding and system design questions, interview experiences, and computer science study guides.
601 resources · Page 25 of 26
Computer science concepts
Topological Sorting And Cycle Detection
Candidates must model dependency graphs and produce a valid Topological sort when possible, or detect a cycle that makes ordering impossible. Interviewers…
Computer science concepts
Trajectory, Kinematics, And Collision Analysis
Interviewers probe your ability to convert vehicle motion into analyzable mathematical objects, select appropriate statistical or numerical methods, and…
Computer science concepts
Transactional Banking System Design
The interviewer is probing your ability to design a transactional account-balance service that is correct under concurrency, auditable, and resilient at…
Computer science concepts
Transformer Architecture And LLM Lifecycle
The interviewer is checking that you can reason end-to-end about large language models: from data and pretraining objectives, through Transformer internals…
Computer science concepts
Transformer Attention And Masking
Candidates must demonstrate practical mastery of Transformer attention and masking semantics as they appear in real training and inference pipelines…
Computer science concepts
Transformer Attention and Variants
Candidates must demonstrate practical mastery of modern Transformer building blocks (self-attention mechanics, positional handling, and computational cost)
Computer science concepts
Transformer Architecture and Attention Internals
Candidates must demonstrate concrete mastery of self-attention math, compute/memory complexity, and practical tradeoffs when training or serving large…
Computer science concepts
Transformer Internals And Scaling
Interviewers are probing whether you can design, scale, and operate Transformer training and inference for production — balancing compute, memory, cost…
Computer science concepts
Transformer Self-Attention and Backpropagation
Interviewers probe whether you can reason about and implement Transformer-style self-attention end-to-end: the algebra of the forward pass, the chain-rule…
Computer science concepts
Transformer Training Pipeline Debugging
Candidates must show practical fluency debugging the entire Transformer training pipeline: data/tokenization correctness, attention and positional masking…
Computer science concepts
Tree Algorithms, Traversal, LCA, And Dynamic Programming
These problems test mastery of tree traversal and connectivity reasoning (preorder listing, path queries, deletions) plus lowest common ancestor (LCA) and…
Computer science concepts
Tree Ensembles And XGBoost For Tabular ML
The interviewer is probing whether you can choose, tune, evaluate, and explain tree ensemble models—especially XGBoost —for real-world tabular problems.…
Computer science concepts
Trees, Tries, and Hierarchical Data
Trees, tries, and hierarchical data questions test whether you can model parent-child structure, preserve invariants, and choose the right index for prefix…
Computer science concepts
Trie and Prefix Indexing
Tests construction and use of a Trie (prefix tree) for efficient prefix indexing, exact-word lookup, and longest-prefix matching. Interviewers probe…
Computer science concepts
Trust, Safety, Fake Accounts, And Fraud
Interviewers probe a candidate's ability to design, evaluate, and interpret detection systems for fraud / fake accounts and abuse, balancing statistical…
Computer science concepts
Trust, Safety, Fraud, And Content Moderation Measurement
Interviewers are testing whether you can measure rare, adversarial, high-stakes product problems where “ground truth” is delayed, noisy, and expensive. At…
Computer science concepts
Trust, Safety, Privacy, And Guardrails
You will be evaluated on making product decisions that balance user value with safety, privacy, and legal risk — especially when introducing automation (e.
Computer science concepts
Unit Testing And Production Code Quality
Interviewers are probing whether you can produce reliable, maintainable production code by designing and executing appropriate tests, and by embedding…
Computer science concepts
Unsupervised Anomaly Detection: Isolation Forest And LOF For Integrity
This tests whether you can apply unsupervised anomaly detection to ambiguous integrity problems where clean labels are scarce, delayed, biased, or…
Computer science concepts
Variance Estimation for Ratio Metrics
1. What it is Variance estimation for metrics that are ratios of two aggregates, like clicks/impressions (CTR), revenue/users (ARPU), or watch…
Computer science concepts
Vector Embeddings and ANN Indexing
Interviewers are checking that you can design, build, and operate a production-grade embedding retrieval pipeline: how embeddings are trained, indexed, and…
Computer science concepts
Versioned Graphs And Snapshotting
These problems test building a mutable directed graph that supports versioning and efficient snapshotting for point-in-time queries alongside live…
Computer science concepts
Weighted Random Sampling Data Structures
You must design a dynamic data structure that supports insert, delete, and getRandom where getRandom returns items proportional to their weight.…
Computer science concepts
Window Functions, Cohorting, and Time Series SQL
1. What it is Window functions compute per-row metrics across a related set of rows without collapsing them (rankings, running totals, lag/lead). Cohorting…