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Hosted by Fexingo · 🇺🇸 US · EN · 117 episodes
Established thought leaders with verified media credentials.
Lucas and Luna examine the discipline of software testing as a strategic function, not a checkbox. Each episode focuses on a specific testing practice — from unit test coverage metrics and integration test design patterns to the economics of test automation ROI and the psychology of flaky test triage. They walk through real-world case studies: how Stripe reduced regression defects by 40% with contract testing, the trade-offs between Selenium and Cypress for e-commerce checkouts, and why Google's test size taxonomy (small/medium/large) forces better architectural decisions. Lucas explains the math behind mutation testing scores and the diminishing returns of 100% code coverage; Luna challenges him on how to sell testing budgets to skeptical product managers and when manual exploratory testing still outperforms automation. They also explore testing philosophies — shift-left vs. shift-right, risk-based testing prioritization, and the role of AI in generating test oracles. The listener lea
Fexingo hosts Software Testing with Fexingo: QA, Automation, and Reliable Software Engineering, a business show with 117 episodes published.
Lucas and Luna discuss the hidden financial impact of flaky test results in continuous integration pipelines. They explore how a single unreliable test can waste over 100 developer-hours per month across a mid-size team,
When a major e-commerce site's redesign caused a 14% cart abandonment spike due to a CSS rendering bug in Firefox, the root cause wasn't logic errors — it was visual drift invisible to unit tests. In this episode, Lucas
Lucas and Luna explore mutation testing through the lens of a real-world disaster: a 2020 fintech bug that would have been caught by this technique. They walk through how mutation testing works, why it exposes weaknesses
Canary deployments are a software release strategy that rolls out changes to a small subset of users first, allowing teams to catch regressions before they affect everyone. In this episode, Lucas and Luna explore how com
Imagine catching a major security flaw before you even write the code. In this episode, Lucas and Luna explore how shift-left security testing is changing the game for engineering teams. They walk through a real case: a
Lucas and Luna explore monkey testing, a technique that unleashes random inputs to find crashes and edge cases conventional tests miss. They break down a real case from 2025 where a major streaming service caught a rare
In this episode of Software Testing with Fexingo, Lucas and Luna dive into contract testing—a practice that prevents breaking changes between services before they reach production. Lucas explains how a major fintech comp
Lucas and Luna explore how tracking test flakiness over time can act as an early warning system for release risk. Using a case study from a mid-sized e-commerce platform that reduced its flaky test rate from 12 percent t
In this episode of Software Testing with Fexingo, Lucas and Luna dive into property-based testing — a technique that generates hundreds of random inputs to find edge cases you never considered. They contrast it with trad
Lucas and Luna explore pairwise testing, a combinatorial technique that reduces the number of test cases needed while maintaining defect detection. They walk through a real example from a flight booking system with 10+ p
Lucas and Luna explore test impact analysis, a smart testing technique that runs only the tests affected by your code changes. They dive into how Facebook's CI pipeline uses dependency graphs to cut test execution time b
In this episode of Software Testing with Fexingo, Lucas and Luna explore a persistent pain point in QA: test documentation that quickly becomes outdated and useless. They anchor the discussion on a 2023 survey by SmartBe
Lucas and Luna dive into a dangerous habit in software quality: chasing high test coverage percentages. Lucas explains why code coverage numbers often mask untested logic paths, citing a 2024 study showing that 40% of 'c
Lucas and Luna dig into a surprisingly common CI problem: automatic test retries. When a failing test is re-run and passes, teams often mark it as 'flaky' and move on. But that pass might just be luck—the real defect rem
Lucas and Luna dive into a specific failure pattern that plagues production systems: database connection pool leaks. They explain how connection pooling works, why leaks happen due to unclosed connections or improper tim
Most test suites check code output but ignore what users actually see. In this episode, Lucas and Luna explore how visual AI testing — using tools like Applitools and Percy — catches pixel-level regressions in responsive
In this episode of Software Testing with Fexingo, Lucas and Luna explore how synthetic test data generated by generative AI is helping QA teams avoid privacy violations while maintaining realistic test coverage. They dis
In this episode of Software Testing with Fexingo, Lucas and Luna explore mutation testing — a technique that systematically introduces faults into your code to measure whether your tests actually catch them. They break d
In this episode of Software Testing with Fexingo, Lucas and Luna explore state-based testing, a technique that verifies system behavior across state transitions rather than just input-output pairs. They break down a real
Lucas and Luna dig into a real-world case from mid-2026: a mid-sized e-commerce platform lost an estimated 3.2 percent of checkout revenue because its new JavaScript framework caused a subtle rendering bug in older versi
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Software Testing with Fexingo: QA, Automation, and Reliable Software Engineering is hosted by Fexingo. The show is categorised under business and has published 117 episodes.
Software Testing with Fexingo: QA, Automation, and Reliable Software Engineering has published 117 episodes.
Software Testing with Fexingo: QA, Automation, and Reliable Software Engineering regularly covers business. It sits in the business category.
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Episodes of Software Testing with Fexingo: QA, Automation, and Reliable Software Engineering average 9 minutes. a focused format where a clear narrative arc and tight preparation matter most.
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