Technical Fundamentals & Core Skills Topics
Core technical concepts including algorithms, data structures, statistics, cryptography, and hardware-software integration. Covers foundational knowledge required for technical roles and advanced technical depth.
Cryptography Fundamentals
Core concepts and vocabulary of cryptography: confidentiality, integrity, authentication, and non-repudiation; the difference between symmetric and asymmetric primitives; and how standard algorithms, libraries, and protocols fit together. Covers threat models, common standards, and applying primitives and cryptographic libraries correctly to real-world security problems. The entry point for the cryptography track.
Asymmetric Encryption and Key Exchange
The construction and mathematics-adjacent mechanics of public-key (asymmetric) cryptography: how RSA, Diffie-Hellman, and elliptic-curve schemes actually work, including the group law and point-arithmetic formulas, scalar-multiplication algorithms (double-and-add, Montgomery ladder, windowed methods, GLV, multi-scalar batching), curve models and coordinate systems, and the hardness assumptions (integer factorization, discrete log, ECDLP) each scheme rests on. Covers key-establishment and authenticated key-exchange protocol design: forward-secrecy mechanics, key confirmation, downgrade protection, key-derivation and context binding, group and multi-party key agreement, and hybrid classical/post-quantum key-exchange composition. Also covers implementation-level attacks against these primitives and their mitigations: timing and side-channel leakage in modular exponentiation and scalar multiplication, invalid-curve and small-subgroup attacks, fault attacks, and padding-oracle attacks. Distinct from selecting, deploying, and operating these primitives in production: PKI certificate lifecycle, CA hierarchy, revocation, and key storage and rotation belong to applied cryptography and key management.
Heaps and Priority Queues
Binary heaps and priority queues for maintaining ordered access to the smallest or largest elements. Covers heapify, top-K selection, streaming medians via two-heap patterns, and merge-of-sorted-streams problems. Appears whenever a problem needs efficient repeated access to extremes without full sorting.
Cryptographic Hashing and Digital Signatures
Cryptographic hash functions (collision resistance, preimage resistance), message authentication codes, and digital-signature schemes. Covers HMAC, signature verification, and how hashing underpins integrity, commitments, and authentication. Distinct from non-cryptographic hashing used in data structures.
Graphs and Graph Algorithms
Graph representations (adjacency list and adjacency matrix) and the traversal algorithms applied to general, non-tree structures: BFS, DFS, topological sort (Kahn's algorithm and DFS-based), shortest paths (Dijkstra, Bellman-Ford, A*), minimum spanning trees, cycle detection, connected components, and union-find. Covers modeling a problem as a graph even when the underlying data is not obviously graph-shaped, such as state-space search, an implicit graph over strings or grid cells (for example Word Ladder), or a task-dependency graph, and implementing these traversals with a hash map or hash set as the storage vehicle (adjacency map, visited set, memoization table), not the subject being tested. The graded skill is traversal, ordering, connectivity, or shortest-path reasoning over nodes and edges. This topic does not own: traversal, reconstruction, or serialization of a single-rooted binary tree (preorder, inorder, postorder, or level-order implementation, rebuilding a tree from traversal arrays, lowest common ancestor, binary search tree validation), which belongs to binary trees and binary search trees even though a tree is technically a graph; hash table internals such as hash function design, collision resolution, and load factor and resizing, which belong to hashing and hash tables; and deriving or comparing algorithmic complexity across graph algorithms without implementing them, such as comparing the time complexity of BFS, DFS, Dijkstra, and A*, which belongs to time and space complexity analysis. One of the highest-signal areas in senior coding interviews.
Bit Manipulation
Working directly with binary representations: bitwise operators, masking, shifting, bit counting, and integer-encoding tricks. Covers using bit-level operations for compact state, fast arithmetic, and low-level optimization. Especially relevant where memory and cycles are constrained.
Hardware Troubleshooting and Diagnostics
Diagnosing and resolving hardware problems: component identification, installation and driver setup, boot and startup troubleshooting, peripheral faults, and server hardware architecture. Covers a systematic approach to isolating failures across CPU, memory, storage, and peripherals. Practical bench-and-datacenter knowledge for support and infrastructure roles.
Estimation and Capacity Sizing
Structured back-of-the-envelope estimation for engineering: decomposing an unknown quantity, choosing reasonable assumptions, and arriving at a defensible order-of-magnitude answer, with an emphasis on system capacity, throughput, and resource sizing and Fermi-style problems. The fast-approximate-reasoning skill probed in system-design and engineering screens; analytical and statistical quantitative reasoning for data roles is owned by Data Science & Analytics.