JP Morgan Chase Software Testing Interview Questions & Answers

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.

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

Sprint planning (estimate test effort), daily stand-up (status and blockers), sprint review (demo) and retrospective (improve). Testers clarify acceptance criteria early and test within the sprint.

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

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

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

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

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.

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

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

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

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.

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.

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

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

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

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

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

The number of defects per size of software, for example defects per thousand lines of code or per module, used to compare quality.

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.

SDLC is the full software development life cycle; STLC is the testing life cycle: requirement analysis, test planning, test design, environment setup, execution and closure.

A scenario is a high-level thing to test (user logs in); test cases are the detailed steps and data that verify it.

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

Unit, integration, system and acceptance testing, moving from individual components to the complete product in front of users.

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

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

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

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

Moves to the chosen floor, doors open and close, door sensor stops closing on obstruction, overload alarm, emergency button, behaviour in a power cut, max capacity and the floor display.

Keep tests modular, prioritise by risk, use exploratory testing, automate stable parts and keep close contact with product owners.

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

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.

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

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

A bug is behaviour that deviates from agreed requirements; an enhancement is a new or improved capability beyond the current requirements.

Using experience to guess where defects likely hide, such as empty fields, special characters or unexpected sequences, and designing tests for them.

Valid card and PIN, wrong PIN, three failed attempts, amount above balance, amount above daily limit, invalid denomination, machine out of cash, network failure and receipt printing.

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

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

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

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

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

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

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.

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

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.

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

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).

Test on real devices and OS versions, interrupts such as calls, battery, network changes, gestures, permissions and app store guidelines.

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