Meesho Software Testing Interview Questions & Answers

A grid mapping requirements to test cases and defects, proving every requirement is tested.

Evaluating how easy and pleasant a product is to use by observing real users complete tasks and noting confusion.

Test execution rate, pass percentage, defect density, defect leakage, defect rejection ratio, requirement coverage and automation coverage.

Assess impact and risk, discuss with product and dev, decide to fix, defer with a workaround or delay release, and document the decision.

Finding why a defect was introduced, such as unclear requirements or missed reviews, to prevent similar defects in future.

Re-check environment, data, browser and steps; check the logs; try the reporter's setup; add video and console logs; mark it 'cannot reproduce' only after discussing with the developer, and keep monitoring.

Re-check the requirement, reproduce with clear steps and evidence (screenshots, logs), discuss with the BA/PO and record the final decision.

Clear, concise, independent, repeatable, traceable to a requirement, with precise expected results and tested data.

Testing how a system moves between states based on events, for example an order going from placed to paid to shipped to delivered.

A clear title, steps to reproduce, expected vs actual result, environment/build, severity and priority, and evidence (screenshot, video, logs).

A language to query databases. Testers use it to verify data saved by the application, prepare test data and check backend results.

Check access with valid, expired and missing tokens, role-based permissions, error codes and that sensitive data is never exposed.

Defects found after release that testing should have caught; leakage % = defects in production / total defects x 100.

Static testing reviews documents and code without executing; dynamic testing executes the software to observe behaviour.

Mandatory fields, email format, password rules, duplicate email, terms checkbox, captcha, confirmation email and field length limits.

Verification: are we building the product right? (reviews, walkthroughs — no code run). Validation: are we building the right product? (actual testing against user needs).

The inputs used in tests. Prepare using valid, invalid and boundary values from production-like but masked data, spreadsheets or generators.

An API style using HTTP methods on resources identified by URLs, usually exchanging JSON and staying stateless.

An epic is a large body of work; stories are user-facing slices of it; tasks are technical work items; bugs are defects.

JIRA Query Language, used to search issues, for example project = ABC AND status = Open AND priority = High.

Valid login, wrong password, empty fields, case sensitivity, max length, SQL-injection strings, password masking, 'remember me', lock-out after N attempts and the forgot-password link.

A development model where each development phase has a matching testing phase, such as requirements with acceptance tests and design with integration tests.

Create a request with method, URL, headers and body, send it, check status and body, add test scripts and save it in a collection.

User Acceptance Testing — end users or the client verify that the system meets business needs in a production-like environment before go-live.

They let testers verify totals and counts per category, such as the number of orders per customer, and compare them with the UI or reports.

Peer review for clarity, coverage of requirements, correct expected results, test data and traceability, then update and baseline them.

A model with many fast unit tests at the base, fewer API or integration tests in the middle and a small number of UI tests at the top.

By business criticality, usage frequency, defect history, risk and dependencies, running high-priority cases first.

Functional testing checks what the system does (login, checkout). Non-functional testing checks how well it does it (performance, security, usability, compatibility).

Severity = impact on the system. Priority = urgency to fix. Logo misspelt on the homepage → low severity, high priority. Crash in a rarely used report → high severity, low priority.

Testing services directly without the UI, checking status codes, responses, security and performance. It finds issues early and is faster than UI tests.

A final document summarising what was tested, defects found and open, metrics, lessons learned and the recommendation for release.

Use mocks or stubs from the API contract such as Swagger, write test cases early and validate again when the real service is available.

Status code, response body and schema, headers, response time, error messages for invalid input, authentication (401/403) and that data is saved in the database.

Evaluating software to find defects and confirm it meets requirements. It reduces risk, protects users and saves the cost of fixing bugs after release.

Reproduce and assess impact, inform stakeholders, help developers fix and verify in staging, run regression and check monitoring after the hotfix, then do a post-mortem.

Add, remove, update quantity, price and tax calculation, coupon codes, stock limits, cart persistence after login and checkout navigation.

Send page, size, sort and filter parameters, then verify counts, order, boundaries (first, last, empty page) and invalid parameter handling.

Testing at the edges of input ranges, such as 17, 18 and 19 for an age limit of 18, since errors cluster at boundaries.

Positive cases use valid inputs to confirm expected behaviour; negative cases use invalid inputs to confirm the system handles errors gracefully.

Prioritising tests by the likelihood and impact of failure, so critical areas get the most coverage when time is limited.

The team selects stories for the sprint. QA helps estimate testing effort, clarifies acceptance criteria and flags dependencies and risks.

Designing tests from user flows described in use cases to verify complete real-world interactions.

Verifying the application works across different hardware, software and settings combinations.

Re-testing existing features after a change. Automate stable, repetitive, high-value flows that run every release.

Valid keyword, partial match, no results, special characters, very long text, empty search, case sensitivity, spelling errors, suggestions and speed of results.

Black box tests behaviour without code knowledge; white box tests internal logic and paths; grey box uses partial knowledge of the internals.

A human error causes a defect in the code, and when that defect is executed it produces a failure visible to users.

Smoke testing checks that the critical features of a new build work (broad and shallow). Sanity testing checks that a specific fix or area works after a change (narrow and deep).

A technique that tests all pairs of input values instead of every combination, greatly reducing test cases while catching most defects.

Shift left with early reviews, improve test design, automate regression, use better test data, add monitoring and learn from escaped defects.

Severity is impact on the system; priority is urgency of the fix. A crash in a rare report is high severity, low priority; a spelling mistake in the logo is low severity, high priority.

Internationalisation tests that the product can support many languages and formats; localisation tests that a specific locale is correct for text, currency, date and layout.

Basic operations, division by zero, decimals, large numbers, order of operations, clear and backspace, repeated operations and memory keys.

A shared checklist for when a story is complete, usually including code review, tests passing, no open critical bugs and documentation updated.

Check SQL injection, brute-force lockout, password masking, session timeout, HTTPS, cookie flags, error messages not revealing users and password reset flow.

Learning, test design and execution at the same time, without scripted cases — time-boxed sessions with a charter (e.g. 'explore checkout with coupons'), noting bugs and ideas. Great for finding edge cases.

TDD writes unit tests before code to drive design; BDD describes behaviour in business language scenarios that become automated acceptance tests.

Talk to developers and users, explore the product, review similar systems, create notes and mind maps, confirm assumptions and write test cases as you learn.

A team meeting at the end of a sprint to discuss what went well, what did not and what to improve next.

A defect that stops testing or release of a feature because no workaround exists, so it is highest priority.