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GitHubWhat automated software testing delivers
Every release risks breaking something that used to work. Manual regression testing catches some of it, but it is slow, repetitive and grows with every feature. Automated tests run the same checks in minutes, on every change, without getting tired or skipping steps.
The goal is not to automate everything. It is to automate the checks that are repeated often and matter most, so human testers can focus on exploratory testing, new features and usability.
Problems we solve
- Regression testing takes days before each release
- Bugs in old features reappear after unrelated changes
- An existing automated suite that is flaky and ignored
- Releases delayed waiting for QA sign-off
- No tests at all on a growing codebase
What’s included
Automation strategy
Which tests to automate, at which level, and in what order.
Web UI automation
Playwright, Cypress or Selenium for critical user journeys.
API automation
Fast, reliable tests of business logic through APIs.
Mobile automation
Appium, Espresso, XCUITest or Detox on real devices.
CI/CD integration
Tests on every pull request and before every deployment.
Flaky test clean-up
Stabilise and speed up existing suites.
The test pyramid in practice
A healthy suite has many fast unit tests, a solid layer of API and integration tests, and a smaller number of end-to-end UI tests for the most important journeys. Too many UI tests make suites slow and brittle; too few leave gaps where components meet. We design the balance for your product and team.
| Layer | Speed | What it covers |
|---|---|---|
| Unit | Milliseconds | Functions and components in isolation |
| API / integration | Seconds | Business logic, data and services working together |
| End-to-end UI | Seconds to minutes | Critical user journeys through the real interface |
Fixing flaky tests
Flaky tests — tests that pass and fail without code changes — destroy trust in automation. Common causes are fixed waits, shared test data, test order dependencies and unstable environments. We use resilient locators and automatic waiting, isolated test data, parallel-safe design and quarantine processes so the suite stays green for the right reasons.
Timeline and budget
| Scope | Typical timeline | Typical budget (USD) |
|---|---|---|
| Automation framework + critical journeys | 3–6 weeks | $8k – $25k |
| Ongoing automation engineer | Monthly | Rate card on request |
Typical ranges to help you plan. Your written estimate comes after a free discovery call.
Choosing test automation tools
| Layer | Popular tools |
|---|---|
| Unit tests | Jest, Vitest, PHPUnit, Pest, pytest, JUnit, xUnit |
| API tests | Postman/Newman, REST Assured, Supertest, pytest |
| Web end-to-end | Playwright, Cypress, Selenium |
| Mobile end-to-end | Appium, Detox, Maestro, XCUITest, Espresso |
| Visual regression | Playwright snapshots, Percy, Chromatic |
| Performance | k6, JMeter, Gatling |
We favour tools that use the same language as your application, so developers can read, run and maintain the tests themselves.
Is automation worth it for your project?
Automation has an upfront cost, so it pays back when tests run often. A rough guide:
- Automate stable, high-value flows that run on every release: login, checkout, core workflows, calculations, permissions.
- Automate anything repetitive across many data combinations, browsers or devices.
- Keep manual exploratory testing, usability judgements and features still changing weekly.
- Delay heavy end-to-end automation on a prototype whose design is not yet settled.
Track simple measures — test run time, flaky test rate, escaped defects and how long releases take — to see whether automation is paying off and where to invest next.
Running tests fast in CI
A test suite that takes an hour will be skipped or ignored. Keeping feedback fast is part of the job:
- Run unit and API tests on every commit; run the full end-to-end suite before merge or on a schedule.
- Parallelise tests across machines and shard large suites.
- Start only the services each test needs, using containers or mocks.
- Re-run only tests affected by a change where the tooling supports it.
- Quarantine flaky tests immediately and fix them, rather than letting failures become normal.
What we deliver in a test automation engagement
Automation strategy
A short document agreeing what to automate, at which level, with which tools, and what stays manual.
Framework setup
A maintainable framework with page objects or screen models, test data factories, environment configuration and reporting.
Prioritised test suite
Automated coverage of critical user journeys, APIs and integrations, ordered by business risk.
CI integration
Tests running on every pull request and nightly, with clear pass/fail signals and artefacts such as screenshots and traces.
Quality dashboard
Trends for pass rate, duration, flaky tests and coverage of critical journeys.
Handover & training
Conventions, documentation and pairing so your engineers can extend the suite confidently.
What to automate first
Automating everything at once is the fastest way to build a slow, fragile suite. We start where automation repays its cost quickest: tests that run often, protect revenue or are tedious and error-prone for people.
| Automate early | Automate later or keep manual |
|---|---|
| Login, sign-up and password reset | Rarely used admin screens |
| Checkout, payments and billing flows | Visual polish and layout judgement |
| Core API endpoints and integrations | Features still changing every week |
| Regression checks for past production bugs | One-off migrations and data fixes |
| Smoke tests after each deployment | Exploratory and usability testing |
How automation fits each stage of delivery
-
Pull requestminutes
Unit, component and API tests give developers fast feedback before code is merged.
-
Merge to mainminutes
A focused end-to-end smoke suite confirms the most important journeys still work together.
-
Nightlyup to an hour
The full regression suite runs across browsers or devices, with results waiting each morning.
-
After deploymentminutes
Smoke tests and synthetic monitoring check production immediately after each release.
Questions to ask an automation partner
- Which tests will you write at the unit, API and UI levels — and why that balance?
- How will you keep the suite fast as it grows?
- How do you handle test data, and how do tests avoid depending on each other?
- What is your policy for flaky tests?
- Who maintains the tests when features change?
- Will our developers be able to read, run and extend the tests without you?
Common automation pitfalls
- Recording scripts with a recorder tool and treating them as a framework; they break with every UI change.
- Automating unstable features before the design settles, which creates constant rework.
- Measuring success by the number of tests rather than by defects caught and confidence gained.
- Leaving automation to a separate team that developers never talk to; tests drift away from the product.
- Ignoring maintenance cost. As a rule of thumb, plan for ongoing time each sprint to update tests alongside features.
Automation complements, rather than replaces, manual exploratory testing and specialised checks such as performance and accessibility testing.
Keeping automated tests maintainable
Tests are code and deserve the same care as production code. We use clear naming, shared helpers for common steps, stable selectors such as data-test attributes instead of fragile CSS paths, and code review for every test change. When a feature changes, its tests change in the same pull request, so the suite never falls behind the product.
To build in-house capability, you can also hire QA automation engineers.
Related services
Part of QA & testing. Runs inside CI/CD pipelines. See also API testing and mobile app testing.
This page is part of QA & Software Testing Services — see the full overview for related services, approach and pricing.