Curated interview practice questions with answers. These are practice scenarios, not a verified list of past interview questions.
About Cashfree Payments hiring for Software Testing roles
Cashfree Payments is a Bengaluru-based payments company that provides payment gateway, payouts, recurring payments and verification APIs for businesses. Merchants use it to collect online payments, send bulk payouts and automate payment workflows. It is regulated as a payment aggregator and hires software engineers, quality engineers, data analysts, product managers and support roles.
For Software Testing roles, this Cashfree Payments practice set focuses most on Test Case Design (7), Agile, SQL and API Testing (6), Bug Life Cycle and Jira (5), Performance and Security Basics (4). It has 5 easy, 30 medium, 5 hard questions, so you can start easy and work up to the harder ones.
Company type
Fintech
Headquarters
Bengaluru, India
Main India offices
Bengaluru
Cashfree Payments Software Testing interview process
Online coding assessment
Technical round 1 (DSA)
Technical round 2 (design or backend)
Hiring manager round
Typical pattern based on public candidate experiences. Rounds vary by role, team and year.
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01
The build arrived three days late but the release date has not moved. How do you prioritise execution?
Rank test cases by business risk and usage: critical flows like login, payment and data saving first, then new features, then high-risk regression from past defects, and cosmetic checks last. Run smoke testing immediately to avoid wasting time on a broken build. Share the reduced plan with the lead and product owner so they know what will not be covered, and get agreement on the remaining risk.
02
What is a sprint planning meeting and what does QA contribute?
Export the cases and group them by module and requirement. Mark duplicates, merge them into one well-written case, and retire cases for removed features. Check which cases have not been executed or failed in months and confirm whether they are still valid. Link the remaining cases to requirements so gaps are visible. Do it module by module with peer review, and set a rule that every story update also updates its test cases.
04
You notice full card numbers printed in the application logs. What do you do?
Treat it as a high-severity security defect, because storing full card numbers in logs breaks payment card security rules and creates a data leak risk. Do not copy the card numbers into the bug; use masked examples and the log location instead. Log the bug with restricted visibility and inform your lead and the security contact right away. After the fix, verify new logs are masked and confirm old logs are cleaned.
05
What automated accessibility tools exist and what are their limits?
Common tools are axe DevTools, Lighthouse in Chrome, WAVE and accessibility linters in CI. They quickly catch missing alt text, low contrast, missing labels and invalid ARIA. Their limit is that they find only roughly a third of WCAG issues. They cannot judge whether alt text is meaningful, focus order is logical, error messages make sense or a custom widget works with a screen reader, so manual testing is still required.
06
Leadership asks for a one-page quality update before a release. Which bug metrics do you report?
Keep it short and decision-oriented. Show open bugs by severity, the created versus resolved trend, blockers with owners and dates, defect leakage from the last release and modules with the most defects. Give a clear recommendation, such as ready, ready with known issues or not ready, with reasons. Use a shared dashboard for detail, and one slide or email summary for leaders who need only the risk picture.
07
Notifications arrive late, and some screens look broken, only on certain Android phone brands. Why can this happen and what do you test?
Android phone makers ship their own skins and settings on top of Android, so the same app can behave differently. Common problems are aggressive battery savers that kill background tasks and delay notifications, different permission screens, custom fonts and display scaling, camera differences and modified WebViews. Pick devices from the brands most used by your audience and test background work, notifications, camera and layout on each.
08
Product is running an A/B test on the checkout button. What does QA need to verify?
QA does not decide which version wins, but makes sure the experiment is trustworthy. Verify both variants work end to end, users are split in the agreed ratio, each user sees the same variant consistently across sessions, and analytics events fire correctly for each group. Also check that turning the experiment off returns everyone to the default. A broken tracking event can make the whole experiment's result wrong.
09
Why do performance reports use percentiles like p90 and p95 instead of averages?
An average hides slow requests. If 90 requests take 1 second and 10 take 10 seconds, the average is 1.9 seconds, which looks fine, but one user in ten waits 10 seconds. The p95 value means 95 percent of requests were faster than it, so it shows what most users actually experience, including the slow tail. Service level targets are usually written as percentiles, such as p95 under 2 seconds.
10
Write test cases for a coupon code field at checkout.
Apply a valid coupon and check the discount and final amount. Test invalid, expired and not-yet-active coupons. Check minimum order value, maximum discount cap and category restrictions. Verify one-time-use coupons cannot be reused and that only one coupon applies if stacking is not allowed. Check case sensitivity and leading or trailing spaces. Remove the coupon and confirm the total resets. Change cart items after applying and verify the discount is recalculated.
A performance baseline is a set of measurements of the current system under a known load, such as response times, throughput, error rate and resource usage. Every new build or release is compared with it to spot regressions. For example, if the checkout API had p95 of 800 milliseconds at 200 users last release and now shows 1.5 seconds, the change needs investigation. A benchmark compares against an industry or competitor standard.
14
What should a tester verify about HTTPS on a website?
Check every page and API uses HTTPS, and plain HTTP redirects to HTTPS. Verify the certificate is valid, not expired, and matches the domain, with no browser warnings. Look for mixed content, where an HTTPS page loads scripts or images over HTTP. Check login and payment forms submit only over HTTPS and that cookies holding session data have the Secure flag.
15
A report shows duplicate rows after a new release. How do you investigate in the database?
Run the report query with GROUP BY on the business key and HAVING COUNT(*) > 1 to find which records repeat. Then check whether the duplicates exist in the base table or are created by the query, usually a new join to a one-to-many table such as addresses. Compare the query before and after the release. Include the duplicate keys, the count and the suspected join in the bug report.
Test monitoring compares actual testing progress with the plan, using metrics like test cases executed, pass rate, open defects and effort spent. Test control is the action taken when monitoring shows a gap, such as re-prioritising tests, adding testers, changing the schedule or tightening entry criteria. For example, if half the time has passed but only a quarter of cases are executed, the lead must act and inform stakeholders.
17
The same bug keeps reopening across three sprints. What do you do?
Stop the retest loop and call a short session with the developer, lead and product owner. Check whether the fix addresses the root cause or only the symptom, whether everyone agrees on the expected behaviour and whether different environments or data are involved. Run a root cause analysis and agree on clear acceptance tests before the next fix. Add an automated regression check so it cannot silently return.
SELECT c.id, c.name, COUNT(o.id) AS order_count
FROM customers c
JOIN orders o ON o.customer_id = c.id
WHERE o.order_date >= CURRENT_DATE - INTERVAL '30' DAY
GROUP BY c.id, c.name
HAVING COUNT(o.id) > 3
ORDER BY order_count DESC;
21
Write a Postman test script that checks the status is 201 and the response contains an id.
pm.test('Status is 201', function () {
pm.response.to.have.status(201);
});
pm.test('Response has id', function () {
const body = pm.response.json();
pm.expect(body).to.have.property('id');
pm.expect(body.id).to.be.a('number');
});
Open the same record in two sessions, change different fields and save both, then change the same field and save both. Check the database to see which value won and whether data was silently lost. A good design uses optimistic locking, where the second save fails with a 'record changed, please reload' message because a version column changed. Also repeat with API calls fired together to catch timing issues the UI hides.
24
The sprint ends tomorrow and two stories are still in testing. What do you do?
Tell the Scrum Master and product owner today, not at the review. Focus testing on the acceptance criteria and the riskiest paths of the story with the most value, and ask a developer to help with test data or simple checks. If a story cannot be finished with quality, it should be carried over, not marked done with untested parts. Raise the cause in the retrospective, such as late handover.
List conditions and actions in a table and cover every combination of conditions (rules) — ideal for business rules like loan approval: salary > X AND credit score > Y → approve.
26
An automated test keeps failing because an element's ID is generated differently on every build. What do you do?
Stop using the dynamic ID. Look for a stable alternative: the element's role and visible name, its label, a stable attribute, or a relative locator based on a nearby fixed element. The best long-term fix is asking developers to add a data-testid attribute. Avoid partial matches on random strings, which can break again. Then update the locator in the page object so every test using it is fixed at once.
A deadlock happens when two transactions each hold a lock the other needs, so neither can continue. The database detects it and kills one transaction with an error. During testing it usually appears under concurrent load, for example two users booking the last seats at once, as random failures or 'deadlock detected' entries in logs. Testers report the exact actions and timing, and developers fix it with consistent lock order or shorter transactions.
29
A hotfix build arrives and you have only 15 minutes before deployment. How do you sanity check it?
Read the hotfix ticket to know exactly what changed. First verify the fix with the original reproduction steps and data. Then check the directly connected flows, for example if the fix is in coupon calculation, test applying, removing and paying with a coupon. Finish with a quick smoke of login and the main business flow. Report the result immediately, mentioning what was and was not covered.
30
A requirement says the page should load fast. How do you turn it into a test case?
The word fast is not testable, so ask the product owner for a measurable target, for example the page loads within 3 seconds on a 4G network for 95 percent of requests. Agree on the conditions: device, network, data size and whether it is first load or cached. Then write the test with those conditions and expected time. Record the agreed number in the story so the expected result is not open to opinion.
Valid keyword, partial match, no results, special characters, very long text, empty search, case sensitivity, spelling errors, suggestions and speed of results.
-- the active list query used by the app should return 0 rows here
SELECT u.user_id, u.email
FROM users u
WHERE u.is_deleted = 1
AND u.user_id IN (
SELECT user_id FROM active_users_view
);
Database testing checks that the data an application stores and reads is correct, complete and safe. It covers schema checks (tables, columns, data types), constraints and keys, data integrity after create, update and delete actions, stored procedures, triggers and views, transactions, and basic performance of heavy queries. For example, after placing an order in the UI, a tester queries the orders and order_items tables to confirm every value was saved exactly as entered.
A development model where each development phase has a matching testing phase, such as requirements with acceptance tests and design with integration tests.
A bug bash is a short, time-boxed session where people from across the team, including developers, product and support, test the product together to find as many issues as possible before a release. To run one, share a build, scope and test accounts, assign focus areas, give a simple bug template and a shared board, then triage findings at the end. It brings fresh eyes and finds usability issues formal tests miss.
38
Why should we hire you as a manual tester over someone with more automation experience?
Answer with strengths and honesty. For example: I am strong at understanding requirements, designing test cases with techniques like boundary values and finding bugs through exploratory testing, which automation depends on to be useful. I also write SQL and test APIs in Postman. I am learning Playwright and have automated a few smoke tests, so I can grow into automation while adding value from the first week.
39
What is the role of a manual tester in a software team?
A manual tester understands requirements, writes test scenarios and test cases, prepares test data, executes tests on each build, logs clear bug reports and retests fixes. They also do exploratory testing, join stand-ups and reviews, and give a quality status before release. Beyond finding bugs, a good manual tester represents the end user and raises usability or requirement gaps early, when they are cheap to fix.
Save filters for common views such as my open bugs, bugs ready for retest, blockers in the current sprint and bugs by fix version. Add them to a dashboard with gadgets like pie charts by priority, created versus resolved trend and a sprint bug list. Share the dashboard with the team so status is visible without manual reports. Testers start their day from the ready-for-retest filter.
Tips to crack the Cashfree Payments Software Testing interview
Revise backend fundamentals such as REST APIs, databases, transactions and idempotency, which matter greatly in payment systems.
Learn how payment gateways, UPI, refunds and payouts work at a high level to discuss product flows clearly.
Practise designing a simple payment or payout service, explaining failure handling, retries and reconciliation.
Keep a one-minute story ready for every project on your CV: problem, your part, tools, result.
Practise the hard questions on this page aloud; Cashfree Payments interviewers usually ask follow-ups on your first answer.
Frequently asked questions
How many rounds are there in the Cashfree Payments Software Testing interview?
Candidates usually go through 4 stages: Online coding assessment; Technical round 1 (DSA); Technical round 2 (design or backend); Hiring manager round. The exact rounds change with the role, team, location and your experience, so confirm the process with the recruiter.
Which topics should I prepare for the Cashfree Payments Software Testing interview?
This practice set leans on Test Case Design (7), Agile, SQL and API Testing (6), Bug Life Cycle and Jira (5), Performance and Security Basics (4). Revise those first, then practise explaining one or two of your own projects end to end, because most Cashfree Payments interviewers ask you to walk through real work.
Are these the exact questions asked at Cashfree Payments?
No. These are curated practice questions that match the skills and difficulty usually tested in fintech interviews like Cashfree Payments's. They are not a leaked or verified list of past questions.
Where does Cashfree Payments hire Software Testing professionals in India?
Cashfree Payments has large teams in Bengaluru. Openings and locations change often, so check the Cashfree Payments careers page and filter by city and experience.