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.
Algorithmic Problem-Solving and Data Structure Selection
The higher-order meta-skill of attacking an unfamiliar problem: recognizing problem archetypes and mapping them to known techniques, decomposing under constraints, and choosing, composing, or designing the right data structures to meet specified operation costs (LRU cache, min-stack, ordered maps, disjoint-set/union-find). Covers reasoning about trade-offs between competing structures and approaches, working through medium-to-hard problems methodically, handling problem variations, and communicating an approach before coding. The connective-tissue topic that ties the individual structure and algorithm topics together, rather than any single structure or algorithm.
Symmetric Encryption and Block Ciphers
Symmetric-key cryptography: block-cipher design (AES, Feistel structures), modes of operation, stream ciphers, and authenticated encryption with associated data (AEAD). Covers padding, IV/nonce handling, and the failure modes of misusing modes. Foundational for anyone building or evaluating data-at-rest and data-in-transit protection.
Time and Space Complexity Analysis
Reasoning about algorithmic efficiency: Big-O/Theta/Omega notation, amortized analysis, recurrence solving, and the time-versus-space trade-off. Covers deriving bounds from code, comparing candidate approaches, and communicating complexity clearly under interview pressure. The analytical layer applied across every algorithm topic.
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 Cryptography and Key Exchange
Public-key cryptography: RSA, Diffie-Hellman, elliptic-curve cryptography, and public-key infrastructure (PKI). Covers key establishment and agreement protocols, certificate trust chains, and the mathematical hardness assumptions each scheme rests on. Essential for TLS, secure messaging, and identity systems.
Version Control and Developer Tooling
The everyday toolchain of software work: version control with Git (branching, merging, rebasing, conflict resolution, using git bisect to find a regression), command-line and shell proficiency for day-to-day navigation, log inspection, and troubleshooting, IDE and editor workflows, build systems and package/dependency management (npm, Maven, pip, Gradle, CocoaPods, and embedded/cross-compilation toolchains), and the growing practice of AI-assisted coding: using, reviewing, and verifying AI-generated code and tests. Deliberately generic across languages and stacks; language- and domain-specific frameworks live in their own categories. This topic covers a developer's individual command of these tools, not: writing durable shell automation and glue scripts (Shell Scripting and Automation owns that), producing, versioning, and publishing build artifacts or container images (Build Automation and Artifact Management owns that), release cadence and change governance (Release Management and Change Control owns that), or diagnosing a live production incident end to end (Performance Troubleshooting and Incident Response and the Observability topics own that).
Linux and Windows System Administration
Administering server operating systems: Linux fundamentals (shell, permissions, services), Windows Server roles and services, Active Directory/Group Policy, package management, and software updates. Covers day-to-day operational tasks and diagnostic tooling for keeping systems healthy. The practitioner surface for sysadmin and infrastructure roles.
Hashing and Hash Tables
How hash tables and hash-based structures work internally, and how to reason about their performance and correctness. Covers hash function properties (determinism, uniform distribution, speed, avalanche effect), cryptographic versus non-cryptographic hash choices, collision resolution (separate chaining, open addressing: linear probing, quadratic probing, double hashing, Robin Hood hashing, cuckoo hashing), load factor and amortized-cost resizing, and what makes an object hashable (the __hash__/__eq__ contract, immutability, custom composite keys). Covers hash-map-backed cache design (LRU and LFU eviction, TTL) and thread-safe concurrent hash maps (lock striping, CAS-based updates, safe concurrent resizing). Also covers hash-based structures beyond arrays and strings: consistent hashing for distributed routing and sharding, hash joins, hash-flooding and algorithmic-complexity security attacks and their mitigations, and probabilistic membership/cardinality structures such as Bloom filters, Cuckoo filters, Count-Min Sketch, and HyperLogLog. Excludes using a hash map purely as an optimization trick inside an array or string problem (two-sum, group anagrams, longest substring without repeating characters); that pattern belongs to Arrays, Strings, and Hashing. This topic is about the hash table itself: how it is built, how it fails under skewed or adversarial input, and how it scales.
Code Review and Working with Existing Codebases
Reviewing others' code and navigating unfamiliar systems: giving and receiving actionable review feedback, spotting correctness and design issues, and reading and understanding large or legacy codebases before changing them. Covers collaborative coding norms, incremental change in shared repositories, and verifying changes against existing behavior. The team-facing side of day-to-day engineering.