Testing
Billing bugs are the most expensive bugs in SaaS. A mishandled subscription upgrade that charges users incorrectly, a webhook that processes twice, or a dunning flow that locks out paying customers — each of these can generate support tickets, chargebacks, and churn that costs far more than the engineering time to
Testing
White-label SaaS is a forcing function for good multi-tenancy. When a customer runs your product under their own brand, on their own domain, with their own colors and logo, any configuration leak becomes immediately visible. Their customers see a broken experience with the wrong logo, wrong colors, or the wrong
Testing
Your onboarding flow is the most important user journey in your SaaS product. It's where first impressions form, where users decide whether your product is worth their time, and where the majority of churn is determined. Yet it's also where testing is most commonly neglected — teams
Testing
Feature flags in single-user apps are already tricky. In multi-tenant SaaS, they're an order of magnitude harder. You're not just controlling whether a feature is on or off — you're controlling which tenants see which features, often with different rollout percentages, different target rules, and
Testing
Data isolation bugs in multi-tenant SaaS are catastrophic. When tenant A can see tenant B's data, you don't get a bug report — you get a breach notification, a legal team, and customer churn. The failure mode is silent: everything looks fine until someone notices records they
Testing
WeasyPrint converts HTML/CSS to PDF in Python, making it popular for invoice generation, report rendering, and document exports in Django/Flask apps. Testing WeasyPrint output involves extracting text from the generated PDF bytes, comparing page structure, and doing visual regression checks against PNG renderings. This guide covers the full
Testing
LLM regressions are silent killers: the app still returns a response, but the quality degraded after a prompt change, model upgrade, or context window modification. Traditional regression tests that assert exact string equality fail immediately with LLMs. This guide covers behavioral regression testing, prompt versioning, LLM-as-judge evaluation, and CI gates
Testing
Apache PDFBox is an open-source Java library for reading and writing PDFs. Unlike iText (commercial license for production use), PDFBox is Apache-licensed. It's ideal for testing PDFs regardless of how they were generated — iText, wkhtmltopdf, Puppeteer, or any other tool. This guide shows how to parse, compare, and
Testing
AI agents call external APIs — search engines, databases, Slack, GitHub, payment processors. Mocking these in tests is essential: real APIs are slow, rate-limited, non-deterministic, and sometimes irreversible. This guide covers four mocking strategies for agentic systems: HTTP interception, tool-level mocking, record/replay, and in-process fakes. An AI agent that manages
Testing
Golden master testing (also called characterization testing) captures what your code currently does and stores it as a baseline. You then refactor with confidence — if the output changes, the test fails. It's not about proving your code is correct; it's about proving a refactor didn'
Testing
iText 7 is the most widely used Java PDF generation library. Testing iText-generated PDFs requires writing to an in-memory stream, parsing the output with iText's PdfReader, and asserting on text content, layout, fonts, and structure. This guide covers JUnit 5 patterns for all of these. Key Takeaways Write
Testing
AI agent workflows are harder to test than traditional software because the intermediate steps (which tools get called, in what order, with what arguments) are non-deterministic. This guide covers deterministic testing strategies: behavioral assertions over tool calls, golden dataset testing, state-based verification, and contract testing for agent-tool interfaces. AI agents