# regression Published articles for regression. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## Build Trust on a Short Software Project DevFeed: [Build Trust on a Short Software Project]() Original publisher: [Read original article]() Author: Viviana Rosas Published: 2026-09-17T12:00:17Z Content type: opinion Language: en Sources: [Atomic Object]() Topics: [trust](), [Software](), [Testing]() Tags: [client](), [progress](), [project](), [project-communication](), [project-team-management](), [regression](), [testing](), [the-software-life](), [trust]() ### AI overview This article explains how software teams can build client trust during short projects. It recommends frequent feedback and check-ins, making progress visible, and using a limited regression test suite focused on important functionality. ### Source excerpt On a short project, clients need evidence not only that work is happening, but that the team knows when to continue, when to change direction, when to raise concern, and how to leave others capable of carrying the work forward. 1. Close the Feedback Loop - Show Responsiveness. It's extremely important to get feedback quickly [...] The post Build Trust on a Short Software Project appeared first on Atomic Spin. ## Libreboot 20241206, 11th revision released! (fixes to GRUB regressions) DevFeed: [Libreboot 20241206, 11th revision released! (fixes to GRUB regressions)]() Original publisher: [Read original article]() Author: Leah Rowe Published: 2026-09-17T04:32:50.666044Z Content type: release Language: en Sources: [News about Libreboot releases and development]() Topics: [libreboot](), [releases](), [coreboot](), [systems]() Tags: [bios](), [canoeboot](), [coreboot](), [cve](), [free-software](), [grub](), [libre](), [libreboot](), [open-source](), [opensource](), [regression](), [release](), [uefi]() ### AI overview Libreboot 20241206 revision 11 is announced as a stable-release revision containing fixes for regressions introduced in revision 10, including GRUB and filesystem-driver issues that could prevent very large files from loading or systems from booting. ### Source excerpt Article: Libreboot 20241206, 11th revision released! (fixes to GRUB regressions) Web link: https://libreboot.org/news/libreboot20241206rev11.html ## Using acceptance tests to catch regression bugs in legacy code before production DevFeed: [Using acceptance tests to catch regression bugs in legacy code before production]() Original publisher: [Read original article]() Author: Valentina Jemuović Published: 2026-09-16T07:33:58Z Content type: tutorial Language: en Sources: [Optivem Journal]() Topics: [Testing](), [Requirements](), [legacy]() Tags: [automated](), [bugs](), [e2e](), [legacy-code](), [regression](), [requirements](), [testing](), [ui](), [unit-tests]() ### AI overview This hands-on article explains why automated unit and end-to-end tests may still allow production bugs in legacy code. It presents acceptance test-driven development (ATDD), where requirements and tests describe the same observable behavior, making coverage clearer and reducing dependence on UI steps. ### Source excerpt You automated, and manual regression testing is still there. Those two facts have the same cause. ## How automated testing improves development of complex features DevFeed: [How automated testing improves development of complex features]() Original publisher: [Read original article]() Author: Dan Lew Published: 2026-09-15T13:16:49Z Content type: opinion Language: en Sources: [Dan Lew Blog]() Topics: [Testing](), [coding](), [Concurrency](), [Database]() Tags: [automated](), [concurrency](), [database](), [regression](), [testing]() ### AI overview The author contrasts manual testing with automated testing while developing job cancellation in a work queue. Automated tests help expose concurrency and regression risks, cover corner cases, and simulate mid-execution cancellation more reliably. ### Source excerpt It's hard for me to overstate how much my coding has improved since embracing automated testing. And yet, I used to think of it as a waste of time! This post is for my former self, demonstrating why I embrace the practice now. Allow me to demonstrate with ## Mobile UI Testing with Claude Code, Cursor and Codex DevFeed: [Mobile UI Testing with Claude Code, Cursor and Codex]() Original publisher: [Read original article]() Author: Ashish Kharche Published: 2026-09-01T10:00:00Z Content type: tutorial Language: en Sources: [mobile.dev - Medium]() Topics: [Testing](), [Mobile](), [Model Context Protocol](), [Android](), [iOS](), [Emulator](), [simulator]() Tags: [agent](), [android](), [chromium](), [claude-code](), [cli](), [codex](), [cursor](), [emulator](), [ios](), [maestro](), [mcp](), [mobile](), [regression](), [simulator](), [testing](), [yaml]() ### AI overview This tutorial explains how Claude Code, Cursor, Codex, and other MCP-enabled coding agents can use Maestro MCP to explore mobile app interfaces on iOS Simulators, Android emulators, physical Android devices, and Chromium, then save the tested steps as reusable Flow files. The saved Flows can be rerun through an agent or the CLI, including in CI, to detect UI changes. ### Source excerpt Have Claude Code, Cursor or Codex run a UI test on an iOS Simulator or Android emulator, then save it as a Flow and run the same test again. ## Release candidate: Godot 4.7.2 RC 1 DevFeed: [Release candidate: Godot 4.7.2 RC 1]() Original publisher: [Read original article]() Author: Thaddeus Crews Published: 2026-08-03T12:00:00Z Content type: release Language: en Sources: [Godot Engine Official]() Topics: [Godot](), [releases](), [Windows](), [Wayland]() Tags: [pre-release](), [regression](), [release](), [releases](), [update](), [wayland](), [windows]() ### AI overview Godot announces the Godot 4.7.2 RC 1 maintenance release candidate, following Godot 4.7.1. The release primarily includes regression fixes and other improvements across the editor, core, input, GUI, multiplayer, and platform-specific functionality. ### Source excerpt What happens when you stabilize stability? Let's find out! ## July 2026 Updates #1 for XCP-ng 8.3 LTS DevFeed: [July 2026 Updates #1 for XCP-ng 8.3 LTS]() Original publisher: [Read original article]() Author: Philippe Coval Published: 2026-07-28T14:32:38Z Content type: release Language: en Sources: [XCP-ng Blog]() Topics: [Security](), [Vulnerabilities](), [Memory Leaks]() Tags: [2026](), [iso](), [leak](), [lts](), [regression](), [release](), [security](), [update](), [updates]() ### AI overview This release provides security and maintenance updates for XCP-ng 8.3 LTS. It updates Xen to address multiple security advisories, fixes a XAPI regression that caused VBD leaks, and includes minor changes needed to build an updated installer ISO. ### Source excerpt This release batch contains a security update for Xen. This update also brings a fix for a XAPI regression causing VBD leaks. Other minor changes were needed to build an updated XCP-ng 8.3 LTS installer (ISO). ## Maintenance release: Godot 4.7.1 DevFeed: [Maintenance release: Godot 4.7.1]() Original publisher: [Read original article]() Author: Thaddeus Crews Published: 2026-07-14T12:00:00Z Content type: release Language: en Sources: [Godot Engine Official]() Topics: [Godot](), [releases](), [Development]() Tags: [android](), [crash](), [maintenance](), [regression](), [release](), [releases](), [version-control]() ### AI overview Godot 4.7.1-stable is the first maintenance release for Godot 4.7. It includes 78 fixes submitted by 42 contributors, addressing regressions and crashes across areas such as the 2D and 3D editors, animation, GUI, input, and Android. ### Source excerpt The first 4.7 maintenance release has arrived! ## Leveraging PyFixest for High-Cardinality Marketplace Modeling at Instacart DevFeed: [Leveraging PyFixest for High-Cardinality Marketplace Modeling at Instacart]() Original publisher: [Read original article]() Author: Benjamin Knight Published: 2026-06-29T16:06:24Z Content type: article Language: en Sources: [Instacart]() Topics: [benchmarking](), [math](), [Algorithms, Complexity](), [Software](), [Programming](), [Routing (disambiguation)]() Tags: [benchmarking](), [bias](), [cardinality](), [data-science](), [delivery](), [efficiency](), [estimator](), [fixed-effects-model](), [instacart](), [linear-regression](), [measurement](), [memory](), [precision](), [pyfixest](), [regression](), [routing](), [speed](), [statistics](), [techniques]() ### AI overview This Instacart article explains why ordinary least squares regression becomes computationally impractical for marketplace experiments with high-cardinality categories. It presents the mathematical basis for using Fixest and Pyfixest, discusses switchback experiment designs for addressing treatment spillover, and describes benchmarks comparing processing speed, memory efficiency, and estimator precision. ### Source excerpt Benjamin S. Knight Scaling Marketplace experiments requires specialized statistical techniques. We examine why standard ordinary least squares regression (OLS) becomes computationally intractable when controlling for high-cardinality categories. We then dive into the underlying math and demonstrate how modern packages -- specifically Fixest and Pyfixest -- bypass these limitations. We conclude by benchmarking these methods to show their real-world impact on processing speed, memory efficiency, and estimator precision. At Instacart we strive to give our customers access to all the fresh foods and ingredients that they would normally get from a trip to the grocery store, but without the hassle of driving, finding parking, waiting in line, etc. Instacart's Marketplace team is responsible for surfacing customers' orders to shoppers, aligning Instacart's delivery windows with shoppers' projected availabilities as efficiently as possible. This entails a careful balancing act. If we offer delivery windows that are sooner / more popular, then we risk overextending shoppers' ability to fulfill those orders on time. If we are too conservative in our delivery option offerings, then we risk losing potential orders. Accurately measuring the impact of changes in our batching and routing algorithms requires thoughtful experiment design and software. Better predictions of future demand / time-to-fulfill allow Instacart to offer more convenient delivery windows.Experimentation on Marketplace One of our primary concerns in Marketplace is treatment spillage. For example, if we adjust our batching algorithm and increase the rate at which multiple orders are combined into batches in Brooklyn and Queens, then we face a real risk of also influencing the rate of batch creation / completion in Staten Island, the Bronx, and Manhattan. In this case the treatment impacts the control group -- a classic source of measurement bias as a consequence of violating the Stable Unit Treatment Value Assumpt ## Performance engineering as a habit, not a project DevFeed: [Performance engineering as a habit, not a project]() Original publisher: [Read original article]() Author: fidelitas.io Published: 2026-05-16T16:00:00Z Content type: tutorial Language: en Sources: [fidelitas.io]() Topics: [Benchmark](), [ci](), [Code](), [systems]() Tags: [benchmark](), [benchmarks](), [build](), [ci](), [cloud](), [code-review](), [engineering-practice](), [git](), [hardware](), [latency](), [observability](), [performance](), [performance-engineering](), [regression](), [runner](), [slo]() ### AI overview The article argues that teams should treat performance engineering as a recurring engineering habit rather than a temporary project. It recommends measuring every pull request, comparing results with the previous day, and making performance regressions fail the build as part of CI. ### Source excerpt Most performance work is reactive: the bill goes up, the dashboard turns red, somebody opens an investigation ticket. Here's how to make it boring instead. ## Crystal 1.20.2 is released! DevFeed: [Crystal 1.20.2 is released!]() Original publisher: [Read original article]() Author: Johannes Müller Published: 2026-05-15T00:00:00Z Content type: release Language: en Sources: [Crystal]() Topics: [Crystal](), [releases](), [bug](), [changelog]() Tags: [bug-fixes](), [regression](), [release](), [release-notes](), [releases]() ### AI overview Crystal 1.20.2 is a patch release that fixes two regressions, including an issue that could eventually cause loss of randomness in the 1.20 release branch. Pre-built packages are available through GitHub Releases and official distribution channels. ### Source excerpt We are announcing a new Crystal release 1.20.2 with a couple of regressions fixed. ## Crystal 1.20.1 is released! DevFeed: [Crystal 1.20.1 is released!]() Original publisher: [Read original article]() Author: Johannes Müller Published: 2026-04-29T00:00:00Z Content type: release Language: en Sources: [Crystal]() Topics: [Crystal](), [releases](), [changelog](), [Kernel]() Tags: [github](), [installation](), [regression](), [release](), [release-notes](), [releases](), [tls]() ### AI overview Crystal 1.20.1 is a patch release that fixes regressions from Crystal 1.20.0. It includes nine changes by two contributors, and pre-built packages are available through GitHub Releases and official distribution channels. Kernel TLS is disabled by default because of production issues, while a randomness-related regression was also fixed. ### Source excerpt We are announcing a new Crystal release 1.20.1 with a couple of regressions fixed. ## Crystal 1.19.2 is released! DevFeed: [Crystal 1.19.2 is released!]() Original publisher: [Read original article]() Author: Julien Portalier Published: 2026-04-27T00:00:00Z Content type: release Language: en Sources: [Crystal]() Topics: [Crystal](), [releases](), [changelog](), [Development](), [HTTP]() Tags: [changelog](), [contributors](), [github](), [installation](), [language](), [regression](), [release](), [releases](), [support]() ### AI overview Crystal 1.19.2 is a patch release that fixes two regressions. It includes three changes since Crystal 1.19.1, updates HTTP parsing behavior to reject requests containing both conflicting headers, and fixes a regression that could eventually cause loss of randomness. Pre-built packages are available through GitHub Releases and official distribution channels. ### Source excerpt We are announcing a new Crystal release 1.19.2 with two regressions fixed. ## Modularizing SOLR Query Creation for Multi-Market Scale DevFeed: [Modularizing SOLR Query Creation for Multi-Market Scale]() Original publisher: [Read original article]() Author: Naman Parikh Published: 2026-03-03T12:18:55Z Content type: tutorial Language: en Sources: [Walmart Global Tech]() Topics: [Code](), [configuration](), [implementation](), [Testing](), [debug]() Tags: [article](), [code](), [complexity](), [configuration](), [developer](), [errors](), [exceptions](), [implementation](), [information-retrieval](), [modular-monolith](), [monolithic-architecture](), [regression](), [software-architecture](), [software-engineering](), [technical](), [testing]() ### AI overview This article describes modularizing a 12,000-line SOLR query creation implementation used across multiple markets. It explains how separating query concerns, adding market-specific configuration, and using stronger typing aimed to reduce coupling, regression risk, and runtime errors. ### Source excerpt Introduction When the SOLR query logic expanded into a 12,000-line monolithic implementation, each modification introduced significant risk, making every change feel akin to defusing a critical system. Adding a market-specific override required yet another if block, compounding complexity and slowing time-to-market. In this article, we will deep dive how we broke that SOLR query creation logic, enabling clean configuration per market, stronger typing, reducing technical debts and dramatically reduced runtime errors. Image generated with DALL-E via ChatGPTThe Problem: When SOLR Queries Creation Logic Become Technical Debt The SOLR query logic class was handling filtering logic, boosting logic, boost functions, pagination etc. All the parameters related to SOLR query was getting generated using single class. Overthe time, this core class handled various logics related to different type of queries: Primary search queries Item insertions via business tools Item insertions via semantic sources Thousands of lines tangled edge-case handling, scoring tweaks, and boosting logic. This unscalable approach: Blocked rapid iteration for new markets Tight Coupling: All query-handling logic lived in one massive class, making it difficult to cleanly separate concerns. Market-specific changes could unintentionally affect unrelated logic, requiring exhaustive regression testing. High Risk of Unintended Consequences: Changing business requirements (such as supporting different filtering or boosting strategies for a new market) entailed changing existing code that already served other markets. Developers had to be extremely cautious, as a bug or oversight could break unrelated functionality. No Configuration Flexibility: There was no clear system for externalizing market-specific configuration. Instead, all logic changes happened directly in code, preventing business users or product managers from making simple market changes without developer intervention. Increased Runtime exceptions ## Introducing Visual Testing in Maestro DevFeed: [Introducing Visual Testing in Maestro]() Original publisher: [Read original article]() Author: Dan Caseley Published: 2026-03-02T07:00:00Z Content type: release Language: en Sources: [mobile.dev - Medium]() Topics: [Testing](), [Command-line interface]() Tags: [cli](), [maestro](), [regression](), [screenshot](), [screenshot-testing](), [screenshots](), [testing](), [visual-regression-testing](), [visual-testing]() ### AI overview Maestro's Visual Testing compares screenshots with saved baselines to detect unexpected visual changes. The article explains assertScreenshot, takeScreenshot, cropOn, and thresholdPercentage, and describes use cases including shared design-system components, dependency upgrades, dark mode, and complex layouts. ### Source excerpt Available in CLI v2.2.0, Maestro Studio, and Maestro Cloud ## Workload Capture & Replay DevFeed: [Workload Capture & Replay]() Original publisher: [Read original article]() Published: 2026-02-09T23:00:00Z Content type: article Language: en Sources: [Dennis Felsing]() Topics: [Tooling](), [Docker Compose](), [synthetic-data]() Tags: [blog-post](), [docker-compose](), [regression](), [state](), [synthetic]() ### AI overview This article introduces workload capture and replay tooling for reproducing production issues. It records a Materialize instance's state, recent queries, and ingestion rates, then replays them in a Docker Compose environment using synthetic data. ### Source excerpt When customers hit issues in production, it can be an effort to locally reproduce them, especially when external sources are involved. Reproducing issues is useful not just to figure out the root cause, but also to verify the fix and add a regression test. The newly introduced workload capture & replay tooling records a Materialize instance's state as well as recent queries and ingestion rates, then replays them in a Docker Compose environment with synthetic data. In this blog post I'll show how it works and talk about some of the challenges and future work. Read the rest of the blog post over on the Materialize blog. ## Keycloak JS 26.2.3 released DevFeed: [Keycloak JS 26.2.3 released]() Original publisher: [Read original article]() Author: Keycloak Team Published: 2026-02-05T00:00:00Z Content type: release Language: en Sources: [Keycloak Blog]() Topics: [Keycloak](), [bug](), [OAuth](), [Routing (disambiguation)](), [version](), [Angular](), [React]() Tags: [angular](), [bug](), [idm](), [kerberos](), [keycloak](), [keycloak-js-release](), [ldap](), [oauth](), [openid-connect](), [react](), [regression](), [release](), [routing](), [saml](), [sso](), [version]() ### AI overview Keycloak JS 26.2.3 fixes a regression introduced in version 26.2.2 that URL-encoded path-style URL fragments after the OAuth callback when using fragment response mode, breaking hash-based routing. The issue affected Angular, React, and other client-side applications. ### Source excerpt Highlights This release of Keycloak JS addresses a regression that was introduced in version 26.2.2 affecting applications that use hash-based routing in combination with the fragment response mode. Bug Fixes URL hash fragments are now preserved correctly with 'fragment' response mode A regression was introduced in version 26.2.2 that caused URL fragments with path-style routing (e.g., #/admin/maintenance/scripts) to be URL-encoded after the OAuth callback, breaking applications that use hash-based routing. This issue affected Angular, React, and other applications that rely on the hash portion of the URL for client-side routing. keycloak/keycloak-js#241 Upgrading Before upgrading refer to the migration guide for a complete list of changes. ## Improving Frontend Regression Testing with Chromatic DevFeed: [Improving Frontend Regression Testing with Chromatic]() Original publisher: [Read original article]() Author: Stephen De Vaux Published: 2026-01-30T01:00:49Z Content type: article Language: en Sources: [Kogan.com]() Topics: [Front end](), [Testing](), [Storybook](), [Remix](), [browser](), [ci](), [Automation](), [pull-requests](), [Developer experience](), [unit test]() Tags: [automation](), [browser](), [ci](), [developer-experience](), [frontend](), [pull-requests](), [regression](), [remix](), [storybook](), [testing](), [ui](), [unit-test](), [visual-regression-testing]() ### AI overview The article explains how Kogan integrated Chromatic into a Remix-based frontend testing workflow to detect visual regressions that traditional unit tests may miss. It describes Chromatic's Storybook integration, browser screenshots, baseline comparisons, CI workflow, and the differences between UI Review and Visual Tests. ### Source excerpt After recently migrating our frontend to Remix, we took the opportunity to reassess how we approach frontend testing, particularly regression testing. While we already had unit test coverage, we identified a gap when it came to validating UI changes. This is where Chromatic became a part of our frontend testing strategy. This post outlines why we introduced Chromatic and how it fits into a Remix-based workflow. Even when application functionality remains unchanged, subtle visual regressions can still be introduced. Changes to spacing, typography, layout, or component states can easily slip through without being caught by traditional tests. What we needed was a way to automatically detect meaningful UI changes while still fitting into our existing development workflow. At the same time, it was important to avoid introducing a fragile or high-maintenance testing setup, one that adds overhead without delivering proportional benefit. Our implementation with Chromatic attempts to balance automation, reliability, and developer experience as a practical addition rather than an extra burden. Why Chromatic? Chromatic provides visual regression testing on top of Storybook. Instead of testing components purely through assertions, Chromatic renders components in a real browser environment and captures screenshots. These are then compared against a known baseline to highlight visual changes. The key reasons we chose Chromatic were: Automated visual diffs that are easy to review Integration with Storybook, which we already use for component development CI-friendly workflow that fits well into pull requests Chromatic offers two closely related features for reviewing UI changes: UI Review and Visual Tests. While they have some overlap of functionality, they serve different purposes and are designed for different levels of enforcement. UI Review is enabled by default, whereas Visual Tests are an optional feature. UI Review generates snapshots that highlight differences against a bas ## How Evals Help Build Reliable AI DevFeed: [How Evals Help Build Reliable AI]() Original publisher: [Read original article]() Published: 2026-01-18T00:00:00Z Content type: article Language: en Sources: [Mutt0-ds Notes]() Topics: [Artificial Intelligence](), [test](), [Test-driven development]() Tags: [agent](), [ai](), [development](), [evals](), [orchestration](), [prompt](), [regression](), [tests]() ### AI overview The article explains how eval-driven development can help teams build more reliable AI tools. It describes evals as non-deterministic tests that pair questions with expected behavior and can detect regressions after changes to prompts, agent logic, tool definitions, or orchestration code. ### Source excerpt I finished 2025 with a negative AI post, so let's start 2026 with a positive one. I'm leading a project for an AI-based tool, and something... ## Segmented models for personal income estimation at Mercado Libre DevFeed: [Segmented models for personal income estimation at Mercado Libre]() Original publisher: [Read original article]() Author: Samuel Vazquez Published: 2026-01-08T20:44:23Z Content type: article Language: en Sources: [Mercado Libre Tech]() Topics: [data](), [personalization](), [datasets](), [big-data]() Tags: [big-data](), [business](), [classification](), [data](), [dataset](), [estimations](), [personal-income](), [personalization](), [regression]() ### AI overview Mercado Libre describes a "silver shotgun" approach for heterogeneous real-world data: segmenting data across contexts, training specialized models for each segment, and combining their predictions. The article presents personal income estimation as an application supporting more personalized financial products and discusses how geographic scale changes the importance of features such as home GPS location. ### Source excerpt Before we dive in, let's give a huge shout-out to Julio Avila Torreblanca and Alejandro Hernandez Cuevas for their exceptional work in developing this system. Thanks also to Enrique Miranda for reviewing the text and providing valuable feedback. Introduction Real-world data is rarely homogeneous. The same feature can mean different things depending on the city, neighborhood, urban density, or user segment. When we force a single global model to explain all those regimes, we usually pay with lower performance. At Mercado Libre, we take a different approach: instead of looking for a "silver bullet," we use a "silver shotgun." This pattern segments the data in several ways, trains specialized models per segment, and combines their predictions into a single estimate. Motivation: Financial inclusion is a significant opportunity In Mexico, only 63% of adults have a formal bank account, only 37% have a credit product, and less than 16% have a bank credit card [1]. About 45% of employed people have a formal source of income, while the rest work in the informal sector [2]. This gap presents a great opportunity for Mercado Libre to enter a growing market. Hyper-personalization is key to our mission to democratize financial inclusion across Latin America (LatAM). To offer great credit products, such as credit cards, we need a reliable estimate of a person's income. Big data, big problems Imagine we want to build a personal income estimation model for people visiting a very small local park. Every day, our dataset would grow by a few hundred entries for children playing, people exercising, and dog walkers, among other activities. Because people in the park live just a few blocks away, home location would have a limited effect (same neighborhood means low GPS variance). The features with the biggest impact on estimated income would likely be age and occupation. If we scale the problem to an entire city, home GPS location will have a bigger effect on the estimate. Each neighborho ## Using an AI Agent to Investigate Mobile Regressions with Git Diffs DevFeed: [Using an AI Agent to Investigate Mobile Regressions with Git Diffs]() Original publisher: [Read original article]() Author: Matt McKenna Published: 2025-10-29T11:00:22Z Content type: opinion Language: en Sources: [Matt McKenna]() Topics: [Git](), [AI Agent](), [debugging](), [Language models]() Tags: [agent](), [agentic-ai](), [ai](), [ai-agent](), [android](), [debugging](), [git](), [ios](), [mobile-development](), [regression]() ### AI overview The article argues that AI agents can help investigate difficult mobile regressions by analyzing the diff between a known-good and known-bad commit. This can reduce the need for repeated builds required by git bisect, while still requiring developers to test and confirm suspected causes. ### Source excerpt I love git bisect If you don't know it, git bisect is basically a binary search for bugs. You have an issue that did not exist before, so you grab two commit hashes, one good and one bad, and build, repro, build, repro until you find the exact commit... ## Bootstrap 5.3.7 DevFeed: [Bootstrap 5.3.7]() Original publisher: [Read original article]() Author: Mark Otto Published: 2025-06-17T15:22:00Z Content type: release Language: en Sources: [Bootstrap.com]() Topics: [Bootstrap](), [Documentation](), [Astro](), [JavaScript](), [Sass](), [Visual Studio Code]() Tags: [accessibility](), [configuration](), [dependency](), [documentation](), [integrity](), [javascript](), [migration](), [npm](), [regression](), [release](), [updates](), [vscode]() ### AI overview Bootstrap v5.3.7 is a patch release with fixes related to the migration to Astro, documentation, accessibility, JavaScript popovers and tooltips, Sass output, and recommended VSCode configuration. The release notes also mention a recent regression expected to be addressed in another patch release. ### Source excerpt Bootstrap v5.3.7 was just released with some follow-up fixes from our migration to Astro, plus a handful of small fixes. We expect to have another patch release shortly due to at least one recent regression, so stay tuned for that. In the mean time, here are some highlights! Docs Fixed broken "View on GitHub" URLs Corrected HTML content generated by the "Download examples" button Refined sanitizer documentation for clarity and completeness Improved accessibility in the "On this page" table of contents and section heading anchor links Relocated ads to the right sidebar to minimize content reflow Added a new section on the Download page for the Intelissence extension Clarified the "Via JavaScript" usage example for Accordion Collapse Made internal documentation improvements to support future maintenance (no visible user impact) Mention CDN integrity and crossorigin attributes in introduction page Enhance floating labels placeholder usage description Add example of showing dynamic range value with output Sass Consolidated multiple 'none' values in the box-shadow Sass mixin for cleaner output JavaScript Fixed popover and tooltip behavior with a trigger: "hover click" configuration Build tools Added recommended VSCode extensions and settings configuration to the repository Read the GitHub v5.3.7 changelog for a full list of changes (including a ton of documentation and dependency updates) in this release. ## Postmortem: Delayed Start Compute Operations DevFeed: [Postmortem: Delayed Start Compute Operations]() Original publisher: [Read original article]() Author: Em Sharnoff Published: 2025-05-21T18:44:44Z Content type: article Language: en Sources: [Blog -- Neon Docs]() Topics: [incident](), [Amazon Web Services](), [Database](), [VPC](), [Kubernetes](), [Query (disambiguation)](), [monitor]() Tags: [aws](), [capacity](), [configuration](), [databases](), [engineering](), [incident](), [kubernetes](), [monitor](), [outage](), [production](), [proxy](), [rate-limiting](), [recovery](), [regression](), [vpc]() ### AI overview Neon's postmortem explains two AWS/us-east-1 incidents that prevented customers from creating or starting inactive databases for 5.5 hours. An expensive control-plane database query overloaded the database, delayed suspension of inactive databases, drove pod counts beyond planned capacity, and exhausted subnet IP addresses. Neon mitigated the incidents through AWS CNI reconfiguration, control-plane database scaling, rate limiting, traffic redirection, and planned Kubernetes architecture changes. ### Source excerpt Summary On two occasions in the past week, Neon customers in AWS/us-east-1 were unable to create or start inactive databases, for a total period of 5.5 hours. Customers with running databases were unaffected. The root cause related to our ability to assign IP addresses to new dat... ## Go "Vuln Sleighing" with Chainguard this Holiday Season DevFeed: [Go "Vuln Sleighing" with Chainguard this Holiday Season]() Original publisher: [Read original article]() Published: 2024-12-20T00:00:00Z Content type: article Language: en Sources: [Chainguard: Unchained]() Topics: [chainguard](), [Go](), [chainguard images](), [vulnerability](), [Security](), [Parser](), [systems]() Tags: [bitnami-helm-chart](), [chainguard](), [chainguard-images](), [container-images](), [cve](), [cves](), [go](), [helm-charts](), [regression](), [sboms](), [security](), [vulnerabilities](), [vulnerability]() ### AI overview Chainguard describes remediating two recent Go toolchain vulnerabilities by recompiling hundreds of packages and rebuilding scanned images. The article also recounts fixing a Bitnami Helm repository regression so Chainguard Images customers could continue using more secure images. ### Source excerpt Chainguard remediated two Golang CVEs just in time for Christmas. Read how we did it, with a poem in the style of "'Twas the night before Christmas." [Next page]()