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The latest News and Information on Software Testing and related technologies.

Top Banking-as-a-Service (BaaS) Providers in 2027

‍ Banking-as-a-Service (BaaS) enables fintech companies to integrate regulated banking capabilities through APIs and licensed banking partners. These capabilities include account management, payment processing, card issuance, and embedded financial services. Selecting reliable banking as a service providers is becoming increasingly important as regulatory scrutiny and operational risks reshape the industry.

Hot Sauce Releases - Better Together: Meet Sauce Labs AURA

AI-generated code is growing exponentially. Verified releases are growing linearly. AURA (AI-Unified Release Assurance) is Sauce Labs' agentic AI platform that closes that gap: authoring, running and analyzing tests at AI speed, with human oversight, inside the tools your team already uses. In this on-demand session, Steven Spadaccini and Trent Yoxall walk one control plane through four doors.

AI Workspace + Cursor: Generating a consistent test base from your code

Prompting your agentic IDE to write tests gives you different steps and different results every time. The result is inconsistent and low-quality test cases. Combine AI Workspace's agentic workflows with your Cursor IDE to generate a consistent, reusable test base straight from your code repository. In this walkthrough, Product Marketing SVP Ryan Yackel will show how Tricentis generates test cases from a GitHub repo, stores them in qTest, and runs tests against a desktop application.

Benefits and Challenges of Omnichannel Banking for Financial Institutions (2026)

‍An omnichannel banking experience connects digital and physical interactions through shared customer information and workflows. It preserves application progress, service history, and relevant context as customers switch banking channels. For financial institutions, this continuity helps address fragmented service delivery and disconnected sales processes. Customers can progress between mobile applications, contact centers, and branches without restarting completed steps.

Regression Testing vs Integration Testing: Key Differences

Here is a situation most backend teams have lived through. A developer changes how the user service formats dates. It is a tiny change: one line, a cleaner ISO format, every unit test still green. The pull request gets approved in five minutes. Two days later, the billing service starts failing to generate invoices, because it was still expecting the old date format from the user service. Two kinds of testing could have caught that, and they are the subject of this post.

Why AI Coding Agents Are Breaking Your Software

While AI coding agents increase initial build speed, they often lack context about real-world user behavior, leading to downstream production bugs. Watch to learn how to move beyond basic agent-on-agent reviews and set up a true "Quality Factory" using: Check out our demos or get started free: speedscale.com.

API Regression Testing: Catch Breaking Changes Early

API regression testing re-runs your API tests after every code change so existing endpoints keep returning what clients expect. A solid setup checks response shapes, auth, and latency, mocks external dependencies, and runs a fast suite on each pull request with the full suite nightly. Keploy, an open-source tool, generates that suite and its dependency mocks from real API traffic, so teams get regression coverage without writing scripts.

gRPC Mocks, Tests and Contract Checks From a .proto

Change one field in a.proto from double to string, and nothing complains. The code compiles, the deploy goes green, and a service still built from the old contract keeps answering with a double. Here’s what Go’s protobuf runtime does when a client on the new contract reads that answer: No error. risk_score comes back empty, and the nine bytes of the double are tucked away as unknown fields.

Inside Kraken: Regression Testing With Traffic Replay

A readiness check should make a release safer. During one release validation, ours kept Kraken’s traffic replays stuck in Initializing until they timed out. The operator was asking Kubernetes for EndpointSlices. Its installed permissions did not allow that request. The code needed a real cluster, the generated permissions, and a replay trying to start before that mistake became obvious. Kraken put those pieces together during release validation.