Tech Interview Questions for 2026: The Master Index of Every Cornerstone Guide We've Written

What a tech interview actually looks like in 2026

A tech interview in 2026 is not one interview. It is a four- to eight-week pipeline of four to five distinct rounds, each with its own format, evaluation criteria, and failure modes. The candidate who treats the pipeline as a single test loses to the candidate who treats each stage as a separate skill.

The stages have not changed in a decade. What changed is the bar inside each stage. As of the 2025-2026 hiring cycle, AI-assisted interview fraud forced major employers to reintroduce in-person legs that had been dropped during the pandemic. The BLS Field of Degree data for Computer and Information Technology still shows the market absorbing the 2023 contraction, which means tighter pipelines, more rounds, and more candidates per opening than the 2021 bubble.

Most new grads going into 2026 interviews are over-prepared on LeetCode and under-prepared on every other stage. The behavioral round kills more loops than the coding rounds. The system design vocabulary check kills more loops than the design depth. The "tell me about yourself" opening kills more loops than the algorithm reasoning. This index exists because the failure modes are spread across the pipeline, not concentrated in one stage.

The avatar I write this for is Jordan Patel. 23, May 2025 BS CS grad, 3.4 GPA, 487 applications, 14 interviews, 0 offers, 11 months post-grad, $1,847 in checking, parents asking about loan repayment. His refrain: 600 LeetCode problems done, bombed the Meta phone screen, "the engineer was nice tho." The pipeline is brutal because every stage is its own skill and most candidates only drill one. The 14 interviews Jordan got through were enough to teach him that the recruiter screen is its own muscle, the OA is its own muscle, the behavioral is its own muscle. He didn't learn that until interview 7 or 8.

What follows is the master directory: every cornerstone guide on this site, grouped by what you're actually prepping for. Use it as a hub. Bookmark the sections relevant to your loop.

The 5-stage tech interview pipeline

Most tech interview loops at mid-tier and larger employers run five stages. Smaller startups compress to two or three. Consultancies expand to six. The shape is consistent enough that prep can be scoped against it.

Stage 1: Online assessment (OA)

A 60-120 minute coding test on a third-party platform, taken at home with a deadline of 5-7 days. The most common platforms in 2026: HackerRank, CodeSignal (general coding assessment), Codility, and CoderPad for live-coding warmups. The OA is the first technical filter, and it kills the largest share of applicants because it's automated. No human reads your resume until you pass.

Format varies by platform. HackerRank typically asks two to three medium algorithm problems. CodeSignal's General Coding Assessment is a 70-minute timed test with four problems of escalating difficulty. Codility's tests are short and benchmark-based. Most OAs allow you to pick your language; some restrict to a curated list of three to five.

What this stage tests: can you write code that passes hidden test cases under time pressure with no interviewer present. The 2026 quirk is that anti-cheat is heavier: webcam recording, tab-switching detection, paste-blocking on some platforms.

Cornerstones:

• HackerRank tech interview guide
• CodeSignal GCA tech interview guide
• Codility tech interview guide
• LeetCode assessments tech interview guide
• Online interview assessment platforms hub

Stage 2: Recruiter screen

A 20-30 minute call with a recruiter. The recruiter is filtering on three things: do your resume claims hold up to one round of follow-up, do you have work authorization, is your comp expectation in their band. As of 2026, identity verification (a government ID on camera or a third-party verification service) often happens at this stage to address AI-driven interview fraud.

This is not a technical stage. Bombing the recruiter screen is rare for strong candidates but common for candidates with resume gaps they haven't rehearsed an explanation for. Have a clean answer for: why you're looking, why this company, what salary range you're targeting, when you can start.

Cornerstones:

• CS new-grad interview loop hub
• Tell me about yourself interview answer
• Why should we hire you answer
• Cold email recruiter for CS new grads
• Referrals for CS new grads, cold to warm

Stage 3: Technical phone screen

45-60 minutes, one or two coding problems on a shared editor (CoderPad is the most common, occasionally a HackerRank live session or the employer's in-house tool). The signal is whether you can code AND talk at the same time. Silent coding is the #1 anti-pattern in this round. The interviewer is testing communication under live observation, not just correctness.

The bar is one Medium problem solved cleanly in 35-40 minutes with narration, or two Easy/Medium problems solved in 20-25 minutes each. Hitting a wall and recovering is fine. Hitting a wall and shutting down kills the round.

Cornerstones:

• Technical phone screen tactics for CS new grads
• CoderPad live interview guide
• Karat technical interview guide
• Code interview io tech interview guide
• Hatchways tech interview guide

Stage 4: Onsite (virtual or in-person)

Three to six rounds of 45-60 minutes each, the longest day of the loop. The 2026 breakdown for new-grad onsites: two pure coding rounds (Medium + Medium-to-Hard), one system-design-lite round, one behavioral round, occasionally one project deep-dive or culture round.

The major 2026 shift documented in Entrepreneur magazine on August 18, 2025: Google, Cisco, and McKinsey simultaneously reintroduced in-person rounds. The reversal, worth millions in candidate-travel cost, was driven by AI interview fraud and the gap between remote-interview performance and first-90-days job performance. Many onsites in 2026 require at least one in-person leg, sometimes the entire day.

Virtual onsites still happen, mostly via Zoom, Google Meet, or Microsoft Teams. The platform matters because anti-cheat behaviors differ by platform.

Cornerstones:

• Zoom tech interview guide
• Google Meet tech interview guide
• Microsoft Teams tech interview guide
• Webex tech interview guide
• Panel interview survival guide

Stage 5: Final round

Often the hiring manager or skip-level. 45-60 minutes. Lower technical depth, higher behavioral depth, plus comp negotiation positioning. Some employers run the final as a culture-fit conversation; others run it as a project deep-dive ("walk me through the most interesting thing you built"). The final is rarely the round where you bomb, but it can be the round where you accidentally talk yourself out of a strong offer by under-pricing your range.

Cornerstones:

• Final round interview tips
• Second round interview questions
• Best questions to ask your interviewer
• How to negotiate a CS new-grad offer
• Multiple CS new-grad offers playbook

Tech interview questions by language and framework

Most tech interviews let you pick your language for the coding round. The choice signals what stack you've shipped on. Below are the language-specific cornerstone guides. Pick the one matching the role you're targeting.

Python interview questions

If you're prepping for a Python interview round, the Python interview questions guide covers 50+ questions across data structures, OOP, decorators, generators, async/concurrency, the GIL, and the standard library. Python is the most-tested language across SWE, data engineering, ML, and DevOps roles in 2026. The guide includes a 6-step prep plan, a role-by-role question breakdown (SWE vs. data engineer vs. ML engineer), and a one-page idiom cheat sheet for the morning of the interview.

.NET / C# interview questions

For roles at enterprise employers, Microsoft-shop startups, and Fortune 500 IT departments, the .NET interview questions guide is the prep hub. Covers C# language fundamentals, the .NET runtime (CLR, garbage collection, async/await), ASP.NET Core, Entity Framework, dependency injection, and the 2026-specific concepts most new grads underprepare for (LINQ deferred execution, IDisposable patterns, configuration providers). If your interview round is in C#, start here.

Angular interview questions

Frontend roles at enterprise employers and large product teams often test Angular specifically. The Angular interview questions guide covers components, services, RxJS observables, change detection, dependency injection, and the standalone-component model that became default in Angular 17+. Most Angular interviews mix language fundamentals with framework specifics; the guide structures both.

Selenium interview questions

For QA engineering, test automation, and SDET roles, the Selenium interview questions guide covers WebDriver fundamentals, locator strategies, waits (implicit vs. explicit vs. fluent), the Page Object Model, Selenium Grid, integration with TestNG and JUnit, and the headless browser patterns that became standard in CI pipelines. Test automation roles are growing as employers ship more, and Selenium remains the dominant browser-automation framework in 2026 despite Playwright's rise.

Tech interview questions by data and infrastructure

Data and infrastructure roles have their own interview shape. Heavier on SQL, system design, and domain knowledge, lighter on LeetCode-hard algorithms. These cornerstones cover the role-specific question banks.

Data analyst interview questions

For data analyst roles at product companies, e-commerce employers, and consulting firms, the data analyst interview questions guide covers SQL (window functions, joins, CTEs, optimization), statistics fundamentals (hypothesis testing, A/B testing, confidence intervals), Excel/Sheets, dashboards, and the case-study format common at product companies. Most data analyst loops in 2026 are SQL-heavy with a take-home analytical exercise.

Data scientist interview questions

If you're targeting data science roles at FAANG, product companies, or AI-first startups, the data scientist interview questions guide covers statistics depth, ML model design (when to use which algorithm), experimentation (A/B test design, sample size, interpretation), SQL at moderate depth, Python with pandas/NumPy, and the product-sense round that separates data scientists from data analysts in the FAANG hierarchy.

Machine learning interview questions

For ML engineer, applied scientist, and research engineer roles, the machine learning interview questions guide covers ML fundamentals (bias-variance, overfitting, regularization), deep learning (architectures, training dynamics, optimization), system design for ML systems (feature stores, model serving, online vs. batch inference), and the coding round that tests implementing ML primitives from scratch (logistic regression, k-means, attention).

Data engineer interview questions

For data engineer roles at FAANG, fintech, and any company with serious data infrastructure, the data engineer interview questions guide covers SQL at depth (window functions, query optimization, indexing), data modeling (star vs. snowflake, normalization), pipeline design (batch vs. stream, idempotency, backfills), distributed systems (Spark, Kafka, Airflow), and the system-design round oriented around data infrastructure.

Power BI interview questions

For BI analyst and data analytics roles at enterprise employers, the Power BI interview questions guide covers DAX (measures, calculated columns, time intelligence), data modeling in Power BI, M language and Power Query, performance optimization, the difference between import and DirectQuery modes, and the report-design questions that come up when interviewing for visualization-heavy roles.

AWS interview questions

For cloud engineering, DevOps, and SRE roles, the AWS interview questions guide covers core services (EC2, S3, VPC, IAM), infrastructure-as-code (CloudFormation, CDK, Terraform), networking, security, cost optimization, and the architecture-decision questions that come up in solutions-architect interviews. AWS remains the dominant cloud platform in interview questions, but the guide also references the GCP and Azure equivalents where relevant.

Kubernetes interview questions

For DevOps, SRE, and platform engineer roles, the Kubernetes interview questions guide covers core primitives (pods, deployments, services, ingress), networking (CNI, service mesh basics), storage (PVs, PVCs, storage classes), scheduling, RBAC, and the troubleshooting questions that test whether you've actually operated a cluster vs. only read the docs.

Tech interview questions by role (non-coding)

Not every tech-adjacent role is a pure coding interview. These cornerstones cover the role-specific interview shapes that mix technical depth with business judgment.

Business analyst interview questions

For business analyst, product analyst, and operations-analyst roles, the business analyst interview questions guide covers SQL fundamentals, requirements gathering, stakeholder communication, the case-study format, basic statistics, and the soft-skills questions that weight heavier for analyst roles than for engineering roles.

Program manager (technical) interview questions

For technical program manager roles at FAANG and large engineering organizations, the program manager interview questions guide covers cross-functional leadership scenarios, technical depth at the architecture-conversation level (not coding), program structure (roadmaps, milestones, risk management), the behavioral round, and the case-study round common at FAANG-tier TPM loops.

Engineering manager interview questions

For engineering manager and tech-lead-manager roles, the manager interview questions guide covers people management scenarios, technical depth at the architecture-review level, performance management, hiring and team building, and the leadership-philosophy questions common at mid-to-senior manager loops. The guide is oriented toward IC-to-manager transitions and lateral manager moves.

Coding-specific resources

For the coding-round prep that cuts across every role, these cornerstones cover the curated problem sets, cheat sheets, and tactical drills.

LeetCode 75 vs Blind 75 vs NeetCode 150

The LeetCode 75 vs Blind 75 vs NeetCode 150 comparison guide settles the question every CS new grad asks: which curated problem set should I actually drill? Covers the strengths and weaknesses of each, which roles each maps to, and a hybrid prep plan for candidates with 4-8 weeks before their first round. Combined search volume on the underlying keyword cluster is one of the largest in the CS-interview-prep space.

Mock interview practice

The mock interview practice guide for CS new grads covers the format-specific muscle that timed solo problem-solving never builds: narrating under observation, recovering from a stuck moment, balancing speed and correctness. Includes a comparison of mock-interview services and an AI-driven mock approach.

Timeboxed 30-day prep

The timeboxed 30-day prep guide for CS new grads is the one-month plan structured by week and day, designed for someone who has a known interview date and four weeks to ramp from cold to ready.

System design and behavioral (cross-cutting)

Two skill categories show up in almost every tech interview loop regardless of language or role. The cornerstones here are universal.

System design basics for new grads

The system design basics for new grads guide covers the vocabulary-level expectations of a new-grad design round. Load balancers, caches, databases, queues, the read-vs-write tradeoff, basic scaling patterns. You won't be asked to deep-dive into consensus algorithms at the new-grad level; you will be asked to have a coherent conversation about a system, name the right primitives, and identify the bottleneck under a given load. The guide includes three worked examples at the new-grad depth: design a URL shortener, design a chat app, design a notification system.

STAR vs SOAR vs CAR vs PAR behavioral frameworks

The STAR vs SOAR vs CAR vs PAR behavioral frameworks guide covers the four most common storytelling frameworks for behavioral rounds. STAR (Situation, Task, Action, Result) remains the canonical default; SOAR adds Reflection; CAR drops the Task; PAR is the shortest. Picking the right framework for your story is a small lever; structuring your stories before the interview is a large one.

Behavioral interview questions master

The behavioral interview questions master guide covers 40 behavioral questions across 8 themes (leadership, conflict, failure, initiative, teamwork, pressure, customer focus, personal growth), each with a STAR-format sample answer. Pair this with the framework guide above: the framework teaches you how to structure; this guide teaches you which 5 stories to prep so any of those 40 questions lands in your story bank instead of forcing you to improvise.

Tell me about yourself

The tell me about yourself interview answer guide covers the opening question that kills more interviews than the closing question. A bad answer here puts the interviewer in a skeptical posture for the rest of the round. The guide includes three template structures and worked examples for new grads, career changers, and lateral movers.

Why should we hire you

The why should we hire you answer guide covers the closing question variant that asks you to summarize your candidacy in 90 seconds. The pattern is fit + skill + evidence, in that order.

Weakness interview question

The weakness interview question answer guide covers the "what's your biggest weakness" question that still appears in maybe 30% of behavioral rounds. The dishonest "I'm a perfectionist" answer kills the round; the honest "I struggle with X and here's how I'm working on it" answer passes.

Platform-specific guides (assessment + video tools)

Different employers use different interview platforms. The platform matters because the anti-cheat behaviors, screen-share constraints, and IDE quirks differ enough to affect your performance.

HackerRank tech interview guide

The HackerRank tech interview guide covers the most-used OA platform in 2026. Covers the editor's quirks, the test-case format, the timed-vs-untimed distinction, the language-selection trade-offs, and the anti-cheat behaviors (tab-switching detection, paste-blocking, webcam recording). If you have a HackerRank OA scheduled, start here.

CodeSignal GCA tech interview guide

The CodeSignal GCA tech interview guide covers the General Coding Assessment: a 70-minute timed test with four problems of escalating difficulty, scored as a single number out of 850. The scoring rubric is unusual and the time pressure is brutal; the guide includes a question-by-question strategy.

HireVue tech interview guide

The HireVue tech interview guide covers the async-video interview format common at enterprise employers and Fortune 500 IT departments. You record yourself answering pre-recorded questions with strict time limits; an AI scores the responses. The format-specific muscles (camera framing, pacing, eye contact with the lens) are the prep priorities.

Karat technical interview guide

The Karat technical interview guide covers the outsourced technical-interview service used by many employers as their phone-screen vendor. Karat's interviewers follow a strict rubric. Knowing the rubric (and the unusual prompts that come with it) is the prep edge.

CoderPad live interview guide

The CoderPad live interview guide covers the most-used live-coding platform in 2026. The editor is more limited than your IDE; the anti-cheat is moderate; the experience is mostly indistinguishable from a Google Doc with syntax highlighting. The guide covers the platform-specific quirks worth knowing.

Codility tech interview guide

The Codility tech interview guide covers the OA platform common at European employers and benchmark-driven recruiting. Codility's tests are shorter and more benchmark-focused than HackerRank's; the scoring is also different (percentile-based vs. raw score).

Replit for hiring tech interview guide

The Replit for hiring tech interview guide covers the live-coding platform Replit launched for technical interviews. Less common than CoderPad but growing.

VidCruiter tech interview guide

The VidCruiter tech interview guide covers another async-video platform similar to HireVue but used more often at consultancies and mid-market employers.

Spark Hire tech interview guide

The Spark Hire tech interview guide covers a third async-video platform with a slightly different question structure and time-limit model.

Hatchways tech interview guide

The Hatchways tech interview guide covers the project-based assessment platform used by some employers as a take-home OA replacement.

CodeInterview.io tech interview guide

The CodeInterview.io tech interview guide covers the live-coding platform used as a CoderPad alternative at some employers.

Honest-prep guides (the AI-cheating economy)

A separate cornerstone cluster covers the question every CS new grad has now Googled at 2am: is using AI in interviews detectable, and is it cheating? The honest-prep cornerstones address it head-on.

Can interviewers detect AI during a Zoom interview

The can interviewers detect AI during a Zoom interview guide covers what's actually detectable, what's not, and how the detection landscape changed in 2025-2026 as more employers added in-person rounds specifically because of AI-fraud concerns.

CS interview cheating economy

The CS interview cheating economy guide covers the broader market context: the rise of stealth-overlay tools, the employer response (in-person reversion, identity verification), and what this means for honest prep in 2026.

Honest interview prep vs cheating

The honest interview prep vs cheating guide draws the line between prep tools (legitimate) and proxy tools (career-risk). The frame is: practice with AI, walk in earned.

The 30-day tech interview prep plan

A focused four-week plan for CS new grads with one month before their first round. Adjust if your timeline differs. If you have less than three weeks, drop the system-design depth and double the time on coding mocks. If you have eight weeks or more, double the algorithm-pattern coverage and add a second language to your toolkit.

1. Week 1: Drill data structures and algorithm patterns. Pick a curated problem set, Blind 75 or NeetCode 150, and solve 30-40 problems by category. Arrays, hashmaps, two pointers, sliding window, binary search, BFS, DFS, dynamic programming. Time yourself: 20 minutes per Medium, 35 per Hard. The goal is pattern recognition, not memorization. By the end of week 1 you should be able to identify the pattern within the first 90 seconds of reading a new problem.

2. Week 2: Master your interview language end-to-end. Pick one language and go deep. For Python: decorators, generators, the GIL, context managers, comprehensions, the collections module. For Java: streams, generics, the collections framework, equals/hashCode, threading basics. For JavaScript or TypeScript: closures, prototypes, async/await, type narrowing. Practice writing 5-10 problems from week 1 in your chosen language, using idioms rather than literal translations from another language.

3. Week 3: System design vocabulary + behavioral story building. Half the week on system design at the new-grad level. Load balancers, caches, databases, queues, the read-vs-write tradeoff. Watch three to five system-design walkthroughs and try to reproduce the diagram from memory. Half the week on behavioral stories. Write 8 STAR-format stories covering leadership, conflict, failure, ambiguity, initiative, and learning. Each story 2-3 minutes when told out loud.

4. Week 4: Timed mock interviews + platform-specific drills. Run three to five mock interviews on the actual platforms you'll be tested on. HackerRank for OAs, CoderPad for live rounds, the company's specific tooling if you can find out. Narrate your reasoning out loud throughout. Use a peer, a paid mock service, or an AI-driven mock. The first mock feels brutal; by the fifth the pattern is automatic.

5. Morning of the interview: cheat sheet warmup. Five to ten minutes of review on a one-page cheat sheet you wrote yourself during prep. Top 20 idioms in your language with complexity, the five behavioral story openings, the system design checklist. The act of writing the sheet from memory was the prep; the sheet itself is the warmup. Don't drill new problems the morning of. You'll just rattle your confidence.

Common tech-interview mistakes

The seven mistakes that show up most in post-loop debriefs from new grads in the 2025-2026 hiring cycle. The pattern across all of them: candidates over-prepare on the visible parts of the loop and under-prepare on the structural parts.

Optimizing for memorization over reasoning. Drilling 600+ LeetCode problems but never practicing narration. The 2026 bar isn't "recall the optimal solution." It's "talk through a problem you've never seen, ask clarifying questions, recover from a wrong first approach." Memorization-only candidates bomb the phone screen at a high rate.

Treating the behavioral round as the easy round. It isn't. The behavioral kills more loops than the coding rounds combined at most mid-tier and large employers. Untrained candidates ramble. Trained candidates have eight STAR stories ready and route the right one to the right prompt within 10 seconds.

Under-preparing for system design at the new-grad level. New grads either skip system design entirely (assuming it's "senior stuff") or over-prepare for the wrong depth. The new-grad bar is vocabulary plus a coherent conversation. Load balancer, cache, database, queue. Read-heavy vs. write-heavy. Bottleneck identification. That's the floor.

Picking the wrong language for the round. Some candidates write Java in their Python interview because Java is what they used for class projects. The interviewer reads the idiom mismatch instantly. If you're going to interview in a language, drill that language's idioms. Use the language you've shipped on, not the language you took the class in.

Skipping the morning warmup. Cold-starting on a phone screen with no warmup costs you the first 10 minutes. By the time your brain is in the right mode, you've burned a third of the round. A 10-15 minute warmup with a familiar problem the morning of the interview is one of the highest-ROI prep moves and the most-skipped.

Not asking clarifying questions. Diving into code in the first 30 seconds is a signal that you're guessing at the problem. Strong candidates ask 2-3 clarifying questions before writing the first line. Edge cases. Input constraints. Whether the input is sorted. What the expected output format is. Asking the right questions buys time and signals careful engineering.

Going silent when stuck. The single biggest difference between candidates who pass and candidates who fail the phone screen is what happens at the 15-minute mark when the first approach hits a wall. Strong candidates narrate their stuckness out loud. "Okay, my first approach was BFS, but the constraint on space rules that out. Let me think about whether a two-pointer would work here." Weak candidates go silent. Interviewers can't grade silence; they grade the audible reasoning trail.

Honest call from watching new grads do this: pick the two mistakes from the list above that match your weakest area and audit your last three mock interviews for them. Fix those two before adding the others. Most candidates have two consistent failure modes, not seven.

Key terms glossary

OA (Online Assessment)

A timed coding test taken at home through a third-party platform like HackerRank, CodeSignal, or Codility. Typically 60-120 minutes with one to three coding problems. The first technical filter in most large-employer pipelines.

Phone screen

The first live technical round, usually 45-60 minutes on a shared editor with one to two coding problems. Tests whether you can code and talk at the same time. The most common round to bomb because candidates practice silent solo coding instead of narrated live coding.

Onsite

The longest day of the loop. Three to six rounds of 45-60 minutes each, covering coding, system design, behavioral, and sometimes a project deep-dive. In 2026, often requires an in-person leg due to AI-fraud concerns at large employers.

STAR

Situation, Task, Action, Result. The most common behavioral-story framework. A STAR story should run 2-3 minutes told aloud and cover all four parts without rambling.

BFS / DFS

Breadth-First Search and Depth-First Search. The two foundational graph-traversal algorithms. BFS uses a queue and explores level by level; DFS uses a stack (or recursion) and explores depth first. Almost every graph problem reduces to one or the other.

DP (Dynamic Programming)

A problem-solving pattern that breaks a problem into overlapping subproblems and memoizes results. The hardest pattern most new grads encounter in interviews. Recognizable when the brute-force solution has exponential recursion that repeats work.

ARR (Annual Recurring Revenue)

The total subscription revenue normalized to a one-year period. Comes up in product-sense rounds, behavioral rounds at SaaS employers, and system-design rounds for revenue-critical systems.

TPS (Transactions Per Second)

A common load metric in system design rounds. New-grad bar: name a TPS figure, reason about whether one server can handle it, identify the next bottleneck. Senior bar: pick the right architecture and capacity plan.

Bigtable / Cassandra / DynamoDB

NoSQL distributed databases optimized for scale. Names that come up in system design as the "wide-column store" answer. New-grad bar: know the category and one example. Senior bar: explain the consistency tradeoffs.

Sharding

Splitting a database across multiple servers by some partition key. The standard scaling answer for write-heavy workloads. New-grad bar: know it exists and why. Senior bar: pick the right shard key and explain rebalancing.

Caching

Storing computed results so repeated requests don't redo the work. Comes up in every system design round. Two questions interviewers love: what's the cache invalidation strategy, and what happens when the cache is cold.

Load balancer

The component that distributes incoming requests across multiple servers. The first primitive in almost any system design diagram. New-grad bar: name it and know it's between client and servers. Senior bar: pick the right algorithm (round-robin, least-connections, consistent hashing).

Idempotency

The property that running the same operation multiple times has the same effect as running it once. Critical in distributed systems and data pipelines where messages can be re-delivered. Comes up in design rounds for payment systems, API design, and ETL pipelines.

CAP theorem

Consistency, Availability, Partition tolerance. In a distributed system you can only have two of the three at any one time. The standard system-design vocabulary check at the new-grad level. Be ready to name the theorem and pick a side for a given scenario.

Big-O notation

The notation describing how an algorithm's time or space scales with input size. O(1) constant, O(log n) logarithmic, O(n) linear, O(n log n), O(n squared), O(2 to the n) exponential. Stating the Big-O of your solution before the interviewer asks is one of the cleanest signals of interview maturity.

Related guides

• CS new-grad interview loop hub: the parent pipeline guide covering every stage of the loop in detail.
• Timeboxed 30-day prep: the day-by-day version of the prep plan above, for candidates who have a known interview date.
• Mock interview practice: how to drill the live narration muscle that solo problem-solving doesn't build.
• Final round interview tips: tactics for the closing round of the loop, including comp negotiation positioning.
• How to ace an interview mega guide: the broader interview-skills hub spanning tech and non-tech rounds.

About the author: Alex Chen is the founder of InterviewChamp.AI, building AI interview prep for the new-grad CS market and writing about the modern interview gauntlet from the inside.