Software Testing Interview Questions for Freshers (₹3–4 LPA)

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

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

An urgent patch released outside the normal schedule to fix a critical production defect, followed by regression testing and merge back to the main branch.

Verify inserted, updated and deleted rows match UI actions, check constraints, duplicates, NULLs and totals with COUNT and SUM queries.

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

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

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

Allowed and disallowed formats, size limits, empty file, duplicate names, special-character names, cancel upload, slow network and multiple files.

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.

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

Code is built and tested automatically on each change; tests are quality gates that stop faulty builds from moving forward.

Checking the application works across browsers, devices, operating systems, screen sizes and network conditions.

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

DELETE removes selected rows and can be rolled back; TRUNCATE quickly removes all rows and resets the table.

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

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

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

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

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).

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.

Log and track bugs, link them to stories, build dashboards and filters with JQL, manage sprints and generate reports.

Success, failure and pending flows, timeouts, refunds, double-click payments, every method (UPI, cards, net banking), rounding, security (no card data stored) and reconciliation with bank reports.

For a field accepting 1–100: valid class 1–100 (test 50), invalid below 1 (test −5), invalid above 100 (test 150). One value represents each class.

Alpha is done in-house by internal teams before release; beta is done by a limited group of real users in their own environment.

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

The observation that a small number of modules contain most defects, so testing should focus on those areas.

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

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

Break the work into modules and test cases, use past velocity or three-point estimation (optimistic, likely, pessimistic), add time for test data, environment issues, retesting and regression, and keep a risk buffer.

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

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.

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

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

Testing that is continuous and collaborative within each sprint, with testers working alongside developers and product owners from the start.

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.

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

INNER returns matching rows, LEFT keeps all left rows, RIGHT keeps all right rows and FULL keeps all rows from both tables.

GET retrieves data and has parameters in the URL; POST sends data in the body to create or process something.

Measuring speed and stability: load (expected users), stress (beyond limits), spike (sudden surge), endurance (long duration) and scalability testing.

Test 17, 18, 19, 59, 60 and 61.

Valid transfer, insufficient balance, daily limit, wrong beneficiary, OTP failure, network drop mid-transaction, duplicate click and statement update.

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

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

Testing shows presence of defects, exhaustive testing is impossible, test early, defects cluster, the pesticide paradox, testing is context-dependent and absence-of-errors is a fallacy.

A regular review where QA, development and product assess new bugs and decide severity, priority, owner and target release.

A set of steps with inputs and expected results. Components: ID, title, preconditions, steps, test data, expected result, actual result and status.

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

Smoke tests run on every build for quick feedback; full regression runs less often, such as nightly or before release.

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

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

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

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

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

The extent of requirements or code exercised by tests. Measure requirement coverage with a traceability matrix and code coverage with tools.

Valid login, invalid login, forgot password, locked account and session handling are the main scenarios to cover.

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