# tag Published articles for tag. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## CVE-2026-76077 - ASN1SCC: Stack buffer overflow and out-of-bounds read in XER tokenizer NT() DevFeed: [CVE-2026-76077 - ASN1SCC: Stack buffer overflow and out-of-bounds read in XER tokenizer NT()]() Original publisher: [Read original article]() Author: CVEFEED.io; github.com Published: 2026-11-05T17:18:20Z Content type: news Language: en Sources: [Latest High/Critical Vulnerabilitiy Feed]() Topics: [Memory Safety]() Tags: [buffer](), [buffer-overflow](), [code-execution](), [comment](), [compiler](), [cpu](), [crash](), [cve](), [cve-2026-76077](), [decode](), [decoder](), [embedded-systems](), [input](), [lookahead](), [memory](), [open-source](), [stack](), [tag]() ### AI overview Before version 4.7.0.1, ASN1SCC's XER tokenizer NT() copies tag characters into a fixed 100-character stack buffer without a length check and reads input and lookahead bytes without checking the available buffer length. Crafted input with an overlong tag can overwrite stack data; truncated tags or unterminated processing instructions or comments can trigger out-of-bounds reads and may cause a CPU spin. The flaws may disclose adjacent memory, corrupt stack data, crash or hang the decoder, and potentially enable code execution. The issue is fixed in version 4.7.0.1. ### Source excerpt CVE ID :CVE-2026-76077 Published : Nov. 5, 2026, 5:18 p.m. | 1 hour, 45 minutes ago Description :ASN1SCC is an open source ASN.1 compiler for embedded systems. Prior to 4.7.0.1, the XER tokenizer NT() in asn1crt/asn1crt_encoding_xer.c, which is reached by all XER decode paths, copies tag characters into a fixed char Value[100] field without a length bound and reads input and lookahead bytes without checking the buffer count. A crafted XER message with an overlong tag can overwrite the tokenizer's stack frame, while a truncated tag or unterminated processing-instruction or comment sequence can read beyond the input and may cause a CPU spin. The flaws can disclose adjacent memory, corrupt stack data, crash or hang the decoder, and potentially permit code execution. This issue is fixed in version 4.7.0.1. Severity: 8.1 | HIGH Visit the link for more details, such as CVSS details, affected products, timeline, and more... ## How to Build a Python GUI Application With wxPython DevFeed: [How to Build a Python GUI Application With wxPython]() Original publisher: [Read original article]() Author: Mike Driscoll Published: 2026-10-31T14:00:00Z Content type: tutorial Language: en Sources: [Real Python]() Topics: [GUI](), [Python](), [Tutorial](), [pip](), [import]() Tags: [2](), [3](), [about](), [absolute](), [added](), [album](), [application](), [build](), [buttons](), [cross-platform](), [editor](), [gui](), [how-to](), [mp3](), [platform](), [python](), [tag](), [this](), [tutorial](), [with]() ### AI overview The tutorial builds a wxPython 4 GUI from a basic frame to an MP3 tag editor. It explains widgets, event loops and handlers, and why sizers are preferable to fixed coordinates for layouts that adapt when a window is resized. The finished example uses eyeD3 to load MP3 tags, wx.ListCtrl to display artist, album and title, a File menu and directory dialog to choose a folder, and a custom dialog to edit and save tags. wxPython uses native platform widgets when possible; PyQt and Tkinter draw their own, though PyQt is described as close to native. wxPython 4 supports Python 3, with version 4.3 requiring Python 3.10 or later. Installation may require development dependencies on Linux; macOS and Windows receive prebuilt wheels via pip. ### Source excerpt Build a cross-platform Python GUI with wxPython in this tutorial, from buttons and sizers to a working MP3 tag editor application. ## OCTOPUS: Towards A Tag Model for Cross-Query Reuse in Semantic Query Processing DevFeed: [OCTOPUS: Towards A Tag Model for Cross-Query Reuse in Semantic Query Processing]() Original publisher: [Read original article]() Author: GuangXue Zhang, Nada Lahjouji, Yiming Lin, Ashwin Colaco, Sharad Mehrotra Published: 2026-10-26T04:00:00Z Content type: article Language: en Sources: [arXiv: Databases]() Topics: [Large Language Model](), [Query (disambiguation)](), [Cache](), [AI Integration Strategies]() Tags: [cs-db](), [large-language-models](), [processing](), [query](), [query-processing](), [reuse](), [semantic](), [tag]() ### AI overview OCTOPUS stores each model-produced semantic judgment back in a database relation as a tag, where the DBMS can filter, index, and reuse it across queries. Its tag operators translate common semantic operators into units that set reuse granularity: prior judgments can help accept or reject tuples for later predicates, simplify tests, or order searches that stop early. In the SemBench movie scenario, OCTOPUS sent the model 10-108 times fewer rows than iPDB, ThalamusDB, Palimpzest, and LOTUS at broadly competitive quality; three of eight queries made no model calls. The abstract presents these as prototype results and says stored judgments retain provenance for auditing. ### Source excerpt arXiv:2610.32586v1 Announce Type: new Abstract: Large language models make it possible to pose semantic questions over diverse, multi-modal data. Recent systems give such workloads the declarative feel of a database through semantic operators: relational operators whose conditions a model judges. Most of them now run on a relational engine, yet almost none keeps what the model says past the query: every judgment is discarded on completion and paid for again the next time a query needs it. We present the tag model and tag operators, the right unit for semantic processing, and OCTOPUS, a prototype built as a middleware over DBMS. Two mechanisms are central. First, the tag: each semantic answer a model produces is written back to the relation as data, which the database engine filters, indexes, and stores as it would any other. Second, the tag operator: the unit into which common semantic operators are translated, which fixes the granularity of reuse. A model judges a tuple once, and later queries reuse that judgment as data: through relationships between predicates, a stored judgment can accept a tuple for a later predicate, eliminate one that cannot satisfy it, simplify its test, or order the search of a query that stops early. On the movie scenario of SemBench, our prototype sends the model 10 to 108x fewer rows than iPDB, ThalamusDB, Palimpzest, and LOTUS at broadly competitive quality, and three of its eight queries issue no model call at all. More broadly, a database that keeps its judgments lets its schema grow from the questions its users ask, so that each semantic answer is paid for once, stays consistent across queries, and can be audited through its provenance. ## Assisted-By: Nobody -- Zephyr Podcast #056 DevFeed: [Assisted-By: Nobody -- Zephyr Podcast #056]() Original publisher: [Read original article]() Author: Benjamin Cabé Published: 2026-10-23T18:32:56Z Content type: news Language: en Sources: [Zephyr Project]() Topics: [Zephyr RTOS](), [Embedded Systems](), [Linux](), [FOSDEM](), [AI Chat]() Tags: [ai](), [ai-assisted](), [blog](), [community](), [embedded](), [fosdem](), [linux](), [news](), [os](), [podcast](), [rc3](), [tag](), [zephyr]() ### AI overview Zephyr 4.5 is at release candidate 3, so this episode focuses on community updates. Linux developers plan to drop the Assisted-by tag requirement because it is unenforceable and inconsistently used; the tag may help reviewers anticipate mistakes, though some see it as advertising. Zephyr adopted the same rule, and whether to retain it is under discussion. A separate maintainer discussion considered requiring contributors to state how changes were tested. Other updates include a proposed Clang Thread Safety Analysis integration that can catch annotated locking mistakes at compile time when using LLVM, and a draft vendor-neutral basic_radio API for packet radios, with a first TI CC23x0 implementation. The I2C target library's per-register callbacks support behaviors such as clear-on-read status and write-1-to-clear bits. The episode also covers an upcoming FOSDEM embedded OS devroom, a Zephyr-based remote test-bench concept, and tools and projects including OpenDial, Ollama, and Zsign. ### Source excerpt 4.5 reaches RC3, FOSDEM 2027 gets an embedded OS devroom, Linux plans to drop its Assisted-by tag, and other community news. ## Saved Reader Layouts and Faster Admin Views DevFeed: [Saved Reader Layouts and Faster Admin Views]() Original publisher: [Read original article]() Published: 2026-10-23T00:00:00Z Content type: release Language: en Sources: [devfeed.tech Changelog]() Topics: [Miniflux](), [browser](), [Edge](), [Google Chrome](), [Django Admin](), [Cache]() Tags: [admin](), [aliases](), [automatic](), [browser-extensions](), [devices](), [drag-and-drop](), [edge](), [errors](), [ico](), [layouts](), [performance](), [responsive](), [scroll](), [tag](), [trending](), [uploads]() ### AI overview Readers can save a preferred layout for each feed; signed-in preferences sync across devices, while guest preferences stay in the browser. My feed adds a Columns workspace for up to twelve feeds, with customizable starters, drag-and-drop ordering, and per-column controls. Admin article and source pipelines and Overview pages load from saved projections and reports, with freshness and rebuild states shown in the UI. Other fixes cover ICO favicons, thumbnail regeneration, scroll preservation and trending pagination in Chrome and Edge, tag edits, and complete upload errors. The text also notes fewer repeated preference reads and recommendation rebuilds while keeping column requests and retained articles bounded. ### Source excerpt This release focuses on making daily reading and admin workflows feel more consistent and responsive. You will see more settings that reliably persist, faster-loading admin pages, and a set of fixes that smooth out browsing and editing. New in this release You can now save your preferred layout per feed, and keep it consistent across web and browser extensions. Signed-in preferences sync across devices, while guest preferences remain local to the browser. My feed now includes a Columns workspace that supports up to twelve independent feeds. You can personalize starters, reorder columns with drag and drop, and use per-column controls without losing your place while browsing. Performance and fixes Admin article and source pipelines, plus Overview pages, now stay responsive by loading from durable saved projections and reports. The admin UI also shows freshness and preparation states, so you can tell when data is updating or rebuilding. Reading also gets smoother with fewer repeated preference reads and less unnecessary recommendation rebuild work, while keeping column requests and retained articles bounded. Publisher logos now accept valid ICO favicons, so branding is no longer blocked by that format. Published article thumbnails can be regenerated from a saved original when derivatives need updating. Reader scroll position is preserved when opening previews and navigating across web, Chrome, and Edge. Trending articles load correctly in Chrome and Edge, including the first page and subsequent pages. My feed avoids unnecessary starter-column saves after manual column choices or intentional clearing has already been saved. Partial tag edits preserve omitted fields while still supporting empty aliases, disabled automatic matching, and explicit topic unlinking. Oversized or stalled uploads return complete errors instead of resetting the connection before the browser receives the response. ## Assign policy groups by stack and account tags DevFeed: [Assign policy groups by stack and account tags]() Original publisher: [Read original article]() Author: Dan Biwer Published: 2026-10-19T00:00:00Z Content type: release Language: en Sources: [Pulumi]() Topics: [policy-as-code](), [pulumi](), [pulumi-cloud]() Tags: [compliance](), [features](), [governance](), [infrastructure](), [policy](), [policy-as-code](), [product](), [pulumi](), [pulumi-cloud](), [tag]() ### AI overview Pulumi Cloud now lets policy groups automatically include stacks and cloud accounts based on tag matching rules. Membership updates as tags change, and teams can define the rules in the console or with the Pulumi Service Provider while keeping existing individually assigned members. ### Source excerpt Policy groups decide which policy packs apply to which stacks and cloud accounts. Until now, stacks and accounts were added to policy groups individually, so every new stack required opting into their correct group by hand. Policy groups membership can now be managed by tags, so new infrastructure gets the right policy coverage automatically as it's created. What's new Policy groups now support tag matching conditions. Every stack or cloud account whose tags match the condition joins the group, and membership stays current as tags change. Tag rules work alongside the stacks and accounts you add individually, so you can adopt them without restructuring your existing groups. To add one, open a policy group in Pulumi Cloud and select Match by tags. Or define it in code with the Pulumi Service Provider: import * as pulumiservice from "@pulumi/pulumiservice"; new pulumiservice.api.PolicyGroup("payments-production", { orgName: "my-org", name: "payments-production", mode: "preventative", stackMatchRule: pulumiservice.buildStackMatchRuleOutput({ rules: [{ conditions: [{ key: "env", value: "prod" }, { key: "team", value: "payments" }] }], }).matchRule, }); new pulumiservice.api.PolicyGroup("pci-accounts", { orgName: "my-org", name: "pci-accounts", mode: "audit", accountMatchRule: pulumiservice.buildAccountMatchRuleOutput({ rules: [{ conditions: [{ key: "env", value: "prod" }, { key: "compliance", value: "pci" }] }], }).matchRule, }); Example: enforcement by environment A common pattern is one policy group per environment tier, with stricter enforcement in production: A production preventative group with a rule matching env: prod, where critical policies are mandatory. A development preventative group with a rule matching env: dev, where the same packs are advisory. A new stack tagged env: prod joins your production policy group automatically, with no one editing the group. The same approach works for audit groups and cloud accounts, for example matching accounts tagged compl ## Jev and Laya for Context-Aware Data Classification in OpenMetadata DevFeed: [Jev and Laya for Context-Aware Data Classification in OpenMetadata]() Original publisher: [Read original article]() Author: Shawn Gordon Published: 2026-10-16T01:55:18Z Content type: article Language: en Sources: [HackerNoon]() Topics: [AI Context Management](), [ML model versioning](), [Prompt Engineering](), [AI Architecture](), [Open Source Models & Datasets](), [Machine learning](), [LLM observability]() Tags: [2](), [agent](), [ai](), [ai-agent](), [ai-model](), [apache](), [apache-2-0](), [audit](), [audit-trail](), [benchmark](), [benchmarks](), [context](), [data](), [explain](), [fine-tuning](), [future-of-ai](), [hackernoon-top-story](), [how-to-use-jev](), [jev](), [metadata](), [open-weights](), [openmetadata](), [tag](), [what-is-jev](), [what-the-heck-is-jev]() ### AI overview Jev is a fast decision model that returns choices, scores, or yes/no probabilities rather than generated text. The article proposes using it with OpenMetadata to classify columns and route uncertain results for human review, while noting that this integration has not been tested on real catalog data. It also discusses running and fine-tuning the Apache 2.0 Laya model locally to keep metadata inside a network, with limitations in accuracy, context length, and confidence calibration. ### Source excerpt Jev is an AI model that decides instead of writing. See how a decision model could tag data in OpenMetadata, and why open-weights Laya fits the job. ## Spring Boot 4.2.0-M2 available now DevFeed: [Spring Boot 4.2.0-M2 available now]() Original publisher: [Read original article]() Author: mhalbritter Published: 2026-09-25T00:00:00Z Content type: release Language: en Sources: [Spring]() Topics: [Spring Boot](), [project release](), [Maven Central](), [Release notes]() Tags: [announce](), [batch](), [boot](), [cloud](), [contributed](), [contribution](), [documentation](), [event-driven](), [issue](), [java](), [maven-central](), [microservices](), [questions](), [reactive](), [release](), [release-notes](), [serverless](), [spring](), [spring-boot](), [spring-boot-4](), [stack-overflow](), [stackoverflow](), [tag](), [upgrade](), [upgrades](), [web-applications]() ### AI overview Spring Boot 4.2.0-M2 is available from Maven Central. The release includes 141 enhancements, documentation improvements, dependency upgrades, and bug fixes. Highlighted additions are SSL bundle support for LDAP, including the embedded LDAP server's LDAPS support, and support for OpenTelemetry semantic conventions with shared OTLP endpoint, header, and compression configuration. The source points readers to the release notes for details and upgrade instructions. ### Source excerpt On behalf of the team and everyone who has contributed, I'm happy to announce that Spring Boot 4.2.0-M2 has been released and is now available from Maven Central. This release includes 141 enhancements, documentation improvements, dependency upgrades, and bug fixes. Notable new features include: SSL bundle support for LDAP, including LDAPS support for the embedded LDAP server. Support for OpenTelemetry's semantic conventions, alongside common OTLP endpoint, header, and compression configuration. Please see the release notes for more details and upgrade instructions. Thanks to all those who have contributed with issue reports and pull requests. How can you help? If you're interested in helping out, check out the "ideal for contribution" tag in the issue repository. If you have general questions, please ask on stackoverflow.com using the spring-boot tag. Project Page | GitHub | Issues | Documentation | Stack Overflow ## GitHub Desktop 3.6.7-beta1 DevFeed: [GitHub Desktop 3.6.7-beta1]() Original publisher: [Read original article]() Author: desktop-releases\[bot\] Published: 2026-09-16T16:21:51Z Content type: release Language: en Sources: [GitHub Desktop]() Topics: [GitHub Desktop](), [Git]() Tags: [branch](), [checkout](), [fetch](), [github](), [merge](), [open](), [remote](), [repository](), [spaces](), [tag]() ### AI overview GitHub Desktop 3.6.7-beta1 fixes the "Open in Cygwin" integration for repository folder names containing spaces or punctuation. It also handles branch, remote, and tag names beginning with a dash across fetch, push, checkout, merge, rebase, and worktree operations. ### Source excerpt Fixed Fix "Open in Cygwin" integration for repository folders whose names contain spaces or punctuation - #22883 Correctly handle branch, remote, and tag names that start with a dash across fetch, push, checkout, merge, rebase, and worktree operations - #22862 ## Google tag gateway: Now on Webflow DevFeed: [Google tag gateway: Now on Webflow]() Original publisher: [Read original article]() Author: Webflow Team Published: 2026-09-16T00:00:00Z Content type: release Language: en Sources: [Webflow Blog]() Topics: [webflow]() Tags: [2](), [2025](), [build](), [business](), [can](), [development](), [driving](), [easier](), [foundation](), [gateway](), [google](), [help](), [make](), [marketing](), [measurement](), [results](), [tag](), [understand](), [webflow](), [with](), [you-re]() ### AI overview Webflow says its native Google tag integration now activates Google tag gateway, routing conversion data through first-party website infrastructure. Existing native users can republish to enable it. For a new setup, add the Google tag ID in Site Settings -> Apps & Integrations, publish, then verify the gateway status is Active. For migration from custom code, save a backup, add the ID to the native integration, remove only the legacy tag-ID scripts (retain event snippets still in use), and test on the staging domain with Tag Assistant before publishing live. The source recommends Advanced Consent Mode with global default-denied settings or managing consent-based firing through Google Tag Manager. It reports average 14% conversion uplift and up to 7% lower CPA among adopters, with individual results varying. ### Source excerpt When you build on Webflow, you're creating experiences designed to help your business stand out and grow. Underpinning those experiences with a strong measurement foundation can help you understand what's driving results and make more informed marketing decisions. Now, Webflow makes it easier to strengthen your measurement foundation. ## JSON - The Fine Print: Part 2 - Emitting JSON DevFeed: [JSON - The Fine Print: Part 2 - Emitting JSON]() Original publisher: [Read original article]() Published: 2025-02-04T00:00:00Z Content type: tutorial Language: en Sources: [William Kennedy]() Topics: [JSON](), [encoding/json](), [Tutorial]() Tags: [api-layers](), [apis](), [common-serialization-errors](), [data-serialization](), [data-structure-separation](), [data-transmission](), [data-validation](), [encoding-json](), [go-json-types](), [go-language-serialization](), [go-language-validation](), [go-type-mapping](), [http](), [json](), [json-best-practices](), [json-go-mapping](), [json-marshaling](), [json-unmarshaling](), [json-validation](), [map](), [passing-serialized-data](), [rest-apis](), [schema-less-data-format](), [serialization](), [serialization-mistakes](), [serialization-protocols](), [streaming](), [struct](), [tag]() ### AI overview Go's `encoding/json` offers `Marshal`, which returns bytes, and `NewEncoder`, which writes to an `io.Writer`. For HTTP handlers, encoding before sending can expose encoding errors early enough to choose a failure status; streaming through an encoder may fail after the response has started, so such errors should be logged. The excerpt also contrasts quick map-based marshaling with structs, which define an outgoing schema, and notes that struct field tags customize JSON property names. ### Source excerpt Introduction In part 1 we took a high-level view on serialization and JSON. In this part, we'll roll our sleeves and start working with JSON, focused on emitting JSON. You might think this is a basic topic, but there is much more to it than just calling json.Marshal. json.Marshal vs json.Encoder The encoding/json package has two main APIs: Marshal and NewEncoder. The Marshal function returns a []byte while the NewEncoder function will write to an io.Writer. The question is: When should you use one API over the other? ## Migrate tag protections to repository rules DevFeed: [Migrate tag protections to repository rules]() Original publisher: [Read original article]() Author: Kevin Duck Published: 2023-10-18T20:57:48Z Content type: release Language: en Sources: [GitHub Changelog]() Topics: [Repository]() Tags: [bypass](), [cloud](), [commit](), [commits](), [deployments](), [enterprise](), [enterprise-cloud](), [github](), [github-enterprise](), [github-enterprise-cloud](), [metadata](), [protection](), [repository](), [repository-rules](), [rules](), [status](), [tag](), [tags]() ### AI overview Existing tag protection rules can be migrated with a few clicks into one repository ruleset or into separate rulesets for more granular control. Tag protections govern who can create, update, and delete tags. Repository rules also support required status checks, successful deployments, signed commits, configurable enforcement, bypass lists, and flexible targeting. GitHub Enterprise Cloud customers can pair metadata restrictions with tag protections to manage commit messages and tag names. ### Source excerpt We've now made migrating existing tag protection rules into repository rules easy. With a few clicks, you can take multiple tag protection rules and turn them into a single ruleset or turn each rule... ## Block ambiguous branch and tag names DevFeed: [Block ambiguous branch and tag names]() Original publisher: [Read original article]() Author: Kevin Duck Published: 2023-03-23T14:05:14Z Content type: release Language: en Sources: [GitHub Changelog]() Topics: [Git](), [GitHub]() Tags: [block](), [branch](), [git](), [github](), [tag]() ### AI overview GitHub blocks creation of new branch and tag names that begin with `refs/` because Git's hidden ref prefixes can make names such as `refs/heads/feature` ambiguous: they may refer to a visible name or a fully prefixed ref. Existing branches with these names can still receive updates. ### Source excerpt GitHub blocks branch and tag names which begin with refs/. Under the hood, all Git refs begin with a prefix (refs/heads/ for branches and refs/tags/ for tags). In typical use,... ## UI tests with Jetpack Compose and Appium x UIAutomator DevFeed: [UI tests with Jetpack Compose and Appium x UIAutomator]() Original publisher: [Read original article]() Author: Julien Salvi Published: 2022-12-05T13:01:16Z Content type: tutorial Language: en Sources: [Julien Salvi]() Topics: [ui-testing](), [UiAutomator](), [Test automation](), [Android Testing](), [Jetpack Compose](), [Software Testing]() Tags: [aircall](), [android](), [annotation](), [api](), [appium](), [automation](), [compose](), [framework](), [jetpack-compose](), [migration](), [production](), [qa](), [quality](), [semantics](), [tag](), [test](), [testing](), [tests](), [ui](), [ui-testing](), [uiautomator]() ### AI overview Aircall's existing Appium and UIAutomator tests located Views by resource ID, but could not find Compose components by their tags. To support the migration, add a semantics testTag to each Composable, enable testTagsAsResourceId at the top-level Composable, and change @AndroidFindBy to use a UiSelector with the component ID. UIAutomator's UiSelector can also locate elements by text or class name. The article says this approach let the team keep existing component IDs and avoid major QA-side rewrites; it reports validating the move to Compose, not broader results beyond Aircall's setup. ### Source excerpt At Aircall we are pushing a lot around quality thanks to our great QA team. Huge efforts are put on Android developer side with the unit tests and our QA engineers tackle everything around automation & UI tests. Before integrating our brand new design system made with Compose UI in production, we wanted to be sure that the transition to Compose would be painless with our automation framework and tools: Appium and UIAutomator. This article will explain how the Android team validated the move to Compose with our automation framework. Automation tests with View components The Aircall QA team has developed lots of automation tests that cover more than 90% of the use cases in the Android app. And to do so, they rely on Appium with the UI testing framework UIAutomator which is an instrumentation-based API and works with the AndroidJUnitRunner test runner. To locate a View-based component in the application, UIAutomator provides an annotation @AndroidFindBy where you need to specify the resource id of a UI element you want to identify. @AndroidFindBy(id = "myButtonId") protected WebElement myButton; But this method does work properly with Compose UI components. Indeed, when looking for a Composable with its dedicated tag, no elements are found in the screen. Now, let's have a closer look at the changes we had to make in order to smoothly add our new Compose code in the current codebase and not breaking everything on the automation side. UI tests with Compose UI and UIAutomator To unlock the UI testing with UIAutomator and Compose, we will have to take advantage of the semantics Modifier in each Composable we want to locate with the testTag property. In order to ease the migration, we are going to keep the same component IDs we were using with our View-based elements. Modifier.semantics { testTag = "myButtonId" } And at the top level Composable, we should toggle the configuration to map testTags to the resource IDs in the semantics Modifier. This will allow the automation f ## Position Statement for the 2022 W3C TAG Election DevFeed: [Position Statement for the 2022 W3C TAG Election]() Original publisher: [Read original article]() Author: Lea Verou Published: 2022-11-07T00:00:00Z Content type: opinion Language: en Sources: [Lea Verou's blog]() Topics: [W3C](), [Web platform](), [human computer interaction](), [User interface design](), [developer-relations](), [Front end]() Tags: [2020](), [2022](), [api](), [api-design](), [architecture](), [background](), [blog](), [css](), [css-wg](), [design](), [design-principles](), [design-reviews](), [developer](), [developer-community](), [developers](), [election](), [experience](), [personal](), [position](), [statement](), [tag](), [w3c](), [web-standards]() ### AI overview Lea reports that during her first two years on the W3C TAG she took part in more than 70 design reviews and, with Sangwhan Moon, led work to document Web Platform design principles that had previously existed mainly as working-group lore. With nearly a hundred review requests in the prior year, she argues published principles can help make reviews more consistent, transparent, and fast. She also started a project to publish a subset of principles for web developers designing compatible APIs, which she hoped to complete in a second term. Her priorities include keeping the TAG connected to developers and end users and promoting features that are usable, secure, privacy-preserving, and approachable. She cites experience in web development, CSS standards, HCI research and teaching, and developer education. The statement notes that she was re-elected. ### Source excerpt Update: I got re-elected!! Thank you for trusting me once more with this huge responsibility towards the Open Web. I will continue to do my best to justify the confidence the W3C membership has placed in me. 🥹 Context: In 2020, I ran for the TAG election for the first time and had the great honor of being elected by the W3C membership. This year, I'm running for re-election. The W3C Technical Architecture Group (TAG) is the Working Group that ensures that Web Platform technologies are usable and follow consistent design principles, whether they are created inside or outside W3C. It advocates for the needs of everyone who uses the Web and everyone who works on the Web. If you work for a company that is a W3C Member, please consider encouraging your AC rep to vote for me! My candidate statement follows. I'm Lea, and I'm running for re-election to the TAG to continue applying my usability research, CSS WG, and TAG experience to help W3C stay connected to the developer community, and to better serve their needs by ensuring web platform features are not only powerful, but also learnable and approachable, with a smooth ease-of-use to complexity curve. I wear many hats. My background spans almost two decades of web design & development experience, one decade of standards work in the CSS WG, nearly a decade of PhD level human-computer interaction research & teaching at MIT, and over a decade of educating web developers through talks, books, articles, and helping them through my dozens of open source projects, some of which are used on millions of websites. For those unfamiliar with my background, I encourage taking a look at my 2020 candidate statement. In 2020, I had the great honor of being elected to serve on the TAG by the W3C membership. In the two years I have served on the TAG, I participated in over 70 design reviews and helped prioritize API design in our reviewing. I have been publicly praised for the quality of design reviews I led. It is important that the TAG d ## GitHub Actions: larger Hosted Runners now support \`-latest\` tag DevFeed: [GitHub Actions: larger Hosted Runners now support \`-latest\` tag]() Original publisher: [Read original article]() Author: Kevin Duck Published: 2022-10-12T15:17:24Z Content type: release Language: en Sources: [GitHub Changelog]() Topics: [GitHub Actions](), [GitHub]() Tags: [actions](), [developers](), [github](), [github-actions](), [image](), [latest](), [latest-tag](), [support](), [tag](), [workflows]() ### AI overview GitHub Actions larger hosted runners now accept the `-latest` image label, which selects the latest generally available (GA) OS image. GitHub points to its runner-images repository for details about image versions and to separate announcement and beta links for more information about larger hosted runners. ### Source excerpt GitHub now supports using the -latest image label on your larger hosted runners. With the -latest label developers can be sure that their workflows use the latest available GA image... ## The push webhook payload provides a consistent head\_commit on tag creation DevFeed: [The push webhook payload provides a consistent head\_commit on tag creation]() Original publisher: [Read original article]() Author: phanatic Published: 2021-10-01T22:28:57Z Content type: release Language: en Sources: [GitHub Changelog]() Topics: [Prometheus Alertmanager webhook](), [Push Notifications](), [payload]() Tags: [commit](), [payload](), [tag](), [webhook]() ### AI overview GitHub's push webhook payload now consistently includes a `head_commit` object for newly created tags. The object contains the data for the commit referenced by the payload's `after` field, addressing cases where it previously contained data from a different commit. ### Source excerpt When a new tag is created, the push webhook payload will now always include a head_commit object that contains the data of the commit that the new tag points to.... ## Updated tag selector for GitHub Releases DevFeed: [Updated tag selector for GitHub Releases]() Original publisher: [Read original article]() Author: phanatic Published: 2021-08-25T17:00:11Z Content type: release Language: en Sources: [GitHub Changelog]() Topics: [GitHub](), [releases]() Tags: [and-best-practices](), [best-practices](), [component](), [design](), [error](), [field](), [for-devs](), [github](), [github-com](), [less](), [newsletter](), [release](), [releases](), [selection](), [selector](), [tag](), [technical](), [text](), [ui](), [updated]() ### AI overview GitHub's Release Creation UI now uses a dropdown selector for choosing a tag instead of a text field. The change is described as less error prone and more consistent with GitHub.com's design. ### Source excerpt The tag selection component on the GitHub Release Creation UI has been updated to now be a dropdown selector rather than a text field. This new component is less error... ## Snippets API: The first API for Square Online DevFeed: [Snippets API: The first API for Square Online]() Original publisher: [Read original article]() Author: John Elliott Published: 2021-05-17T10:00:00Z Content type: release Language: en Sources: [Square Corner]() Topics: [REST API](), [Userscripts]() Tags: [all](), [also](), [api](), [apis](), [app](), [application](), [apps](), [australia](), [authorization](), [bearer](), [build](), [business](), [call](), [can](), [code](), [first](), [insert](), [online](), [square](), [tag]() ### AI overview Square's Snippets API lets developers add JavaScript, HTML, or CSS to the of a Square Online seller's site, enabling additions such as popups, support chatbots, or SEO improvements. After the seller completes OAuth, an app calls the Sites API to find available sites, then POSTs the code snippet to the chosen site. The API is in early access and available to developers in the United States, Canada, United Kingdom, Australia, and Japan; no application process is required. The article invites developers to share feedback through Square's forums or Slack. ### Source excerpt Insert code directly into the tag of a Square Online site ## Position Statement for the 2020 W3C TAG Election DevFeed: [Position Statement for the 2020 W3C TAG Election]() Original publisher: [Read original article]() Author: Lea Verou Published: 2020-11-30T00:00:00Z Content type: opinion Language: en Sources: [Lea Verou's blog]() Topics: [Web Development](), [Web platform](), [W3C](), [Front end](), [CSS](), [web design](), [Developer Tools](), [inclusive design]() Tags: [2020](), [architecture](), [authoring](), [blog](), [browser](), [candidate](), [core](), [css](), [design](), [design-principles](), [designer](), [dev](), [dev-tools](), [developer](), [developers](), [development](), [election](), [personal](), [position](), [statement](), [tag](), [w3c](), [web-standards]() ### AI overview Lea Verou's statement presents her cross-disciplinary experience as a basis for making Web standards usable, learnable, and coherent. She cites work across HTML, CSS, JavaScript, DOM, and SVG; independent web development; open-source projects; long-term CSS Working Group participation and W3C staff experience; MIT research in programming language design and human-computer interaction; and more than a decade teaching web technologies. Her proposed TAG priorities include approachable declarative HTML and CSS alongside JavaScript APIs, greater platform extensibility building on Web Components and Houdini, recording explicit design principles, and helping specification authors improve proposals through TAG review. The statement also reports that she was elected. ### Source excerpt Update: I got elected!! Thank you so much to every W3C member organization who voted for me. 🙏🏼 Now on to making the Web better, alongside fellow TAG members! Context: I'm running for one of the four open seats in this year's W3C TAG election. The W3C Technical Architecture Group (TAG) is the Working Group that ensures that Web Platform technologies are usable and follow consistent design principles, whether they are created inside or outside W3C. It advocates for the needs of everyone who uses the Web and everyone who works on the Web. If you work for a company that is a W3C Member, please consider encouraging your AC rep to vote for me! My candidate statement follows. Hi, I'm Lea Verou. Equally at home in Web development, the standards process, and programming language design, I bring a rarely-found cross-disciplinary understanding of the full stack of front-end development. I have a thorough and fundamental understanding of all the core technologies of the Web Platform: HTML, CSS, JS, DOM, and SVG. I bring the experience and perspective of having worked as a web designer & developer in the trenches -- not in large corporate systems, but on smaller, independent projects for clients, the type of projects that form the majority of the Web. I have started many open source projects, used on millions of websites, large and small. Some of my work has been incorporated in browser dev tools, and some has helped push CSS implementations forwards. However, unlike most web developers, I am experienced in working within W3C, both as a longtime member of the CSS Working Group, as well as a W3C Staff alumnus. This experience has given me a fuller grasp of Web technology development: not just the authoring side, but also the needs and constraints of implementation teams, the kinds of problems that tend to show up in our work, and the design principles we apply. I understand in practice how the standards process at W3C addresses the problems and weighs up the necessary compromises ## Publishing a package no longer creates a release and other GitHub Package Registry updates DevFeed: [Publishing a package no longer creates a release and other GitHub Package Registry updates]() Original publisher: [Read original article]() Author: Mandy Campbell Published: 2019-09-06T17:05:31Z Content type: release Language: en Sources: [GitHub Changelog]() Topics: [NuGet](), [project release]() Tags: [actions](), [github](), [github-actions](), [nuget](), [package](), [packages](), [publishing](), [registry](), [release](), [tag](), [token](), [version]() ### AI overview Publishing a package in GitHub Package Registry no longer creates a release or tag. If its version matches an existing tag and release, the package is automatically associated with that release. GitHub Actions' `GITHUB_TOKEN` access has also been extended to NuGet packages: add the token as a password in `NuGet.config` to publish and consume them from Actions. ### Source excerpt When publishing a package in GitHub Package Registry, a release and corresponding tag will no longer be created. When publishing a package with a version corresponding to an existing tag... ## Finding Where's Waldo using Mask R-CNN DevFeed: [Finding Where's Waldo using Mask R-CNN]() Original publisher: [Read original article]() Author: Suresh Alse (noreply@blogger.com) Published: 2018-06-14T05:51:00Z Content type: tutorial Language: en Sources: [Life Plus Linux]() Topics: [Image](), [Neural Network](), [Algorithms](), [dataset](), [Image processing]() Tags: [algorithm](), [cnn](), [deep-learning](), [deeplearning](), [faster](), [mask](), [ml](), [model](), [tag](), [train](), [waldo]() ### AI overview The author reports that Mask R-CNN worked better for finding and masking Waldo than an initial two-class image-classification approach, which struggled with only about 20 Waldo images and severe class imbalance. They assembled 29 images from two sources, split them into 26 training and 3 validation images, and manually drew Waldo masks with the VIA tool. The model was trained for 30 epochs at 100 steps per epoch, using a COCO-trained Mask R-CNN as the starting model. The author says it works fairly well on images similar to ones it has seen, especially when image quality is good and Waldo is clearly visible; the very small dataset limits the result. ### Source excerpt When I was a kid, I really loved solving Where's Waldo. There were few books (it used to be called Where's Wally) in our school library on which I spent hours finding Waldo. For people who do not know what it is, basically Waldo - a unique character is hidden among hundreds of other characters and you have to find him in all the chaos in the image. Now that I am too old to be solving it and too busy to spend hours on such things, I decided to build a system that uses deep learning to automatically solve it and spent weeks to build it. I started off by treating this like a classification problem with two classes - Waldo and not Waldo, similar to Hot dog - not Hot dog . Once we can get the classification problem successfully solved, we can just apply a classification action mapping (CAM) layer to find Waldo's activations in the image and thus finding Waldo. However I couldn't find enough images of Waldo. I found this repo which has about 20 images. And as there are only 20 Waldo vs thousands of not-Waldo characters, there is very high imbalance in the classes. I still tried though. But the results weren't that great. When I looked if someone has already worked on it, I found a medium post which used Tensorflow's Faster R-CNN model to do this. But I didn't want to just find bounding boxes, I wanted to actually mask out Waldo in the image. But I got more images of Where's Waldo from it. Then I came across this paper on Mask R-CNN which sounded promising for this usecase. And it was indeed much better than my earlier approach: Waldo masked out in the image Original Image In this post I would like to share how I was able to get the data, tag it and train a model to be able to solve Where's Waldo. You can checkout my code on github here. Fork deepwaldo on Github Mask R-CNN The main idea here is to: Take the input image and pass it into a set of convolutional layers that sort of generates a feature map for the given image. Now, you take this feature map and pass it into a r ## Introducing Apollo Bot 🤖 DevFeed: [Introducing Apollo Bot 🤖]() Original publisher: [Read original article]() Author: Evans Hauser Published: 2018-03-08T21:27:00Z Content type: release Language: en Sources: [Apollo Blog]() Topics: [Open Source](), [Pull Request](), [Bot](), [Maintainers]() Tags: [announcement](), [apollo](), [bot](), [community](), [contributing](), [contributors](), [discussion](), [easier](), [easy](), [ecosystem](), [feature](), [flag](), [functionality](), [github](), [github-issues](), [graphql](), [growth](), [open-source](), [repositories](), [rest](), [tag]() ### AI overview Apollo Bot is introduced as a way to make contributing across Apollo's open source repositories easier. Its first feature lets contributors label issues and pull requests, providing quick information for contributors and maintainers and helping people find work that fits their interests or experience. The excerpt recommends looking for the has-reproduction flag when seeking issues to help with, or filtering for the feature tag to join discussions about Apollo Client's next generation. The article presents these labels as an initial step, with Bot functionality expected to expand as the team learns what contributors need. ### Source excerpt Two years ago, Apollo started as a tiny open source project with just a handful of contributors. Today it has expanded to many repositories supported by an incredible community: graphql-tag, apollo-angular, reason-apollo, apollo-android, apollo-link-rest to name a few. The existence of these projects and sustained growth are driven by community suggestions and feature contributions. ## Stockwell: flowchart for triage DevFeed: [Stockwell: flowchart for triage]() Original publisher: [Read original article]() Author: elvis314 Published: 2017-10-23T19:50:29Z Content type: article Language: en Sources: [Mozilla Automation]() Topics: [intermittent failures](), [alert triage](), [software-development]() Tags: [annotations](), [bug](), [bugs](), [development](), [intermittent-failures](), [intermittents](), [monitor](), [process](), [robot](), [simple](), [tag](), [testdev](), [treeherder](), [triage]() ### AI overview Tree sheriffs link test failures to bugs in Treeherder and Orange Factor, where an Orange Factor robot comments on bugs to support triage. Neglected Oranges surfaces failures meeting the team's threshold that lack a human comment in the past seven days. Triage adds information to help the person asked to prioritize a bug and decide what to do. Bugs with more than 200 failures in 30 days may receive a "[stockwell disabled-recommended]" whiteboard tag; the team monitors these and disables them where possible, while pushing harder on cases that are not trivial to disable. The author says this workflow has been effective across more than 1,000 bugs triaged that year, while acknowledging it is not a simple rule to disable every qualifying bug. ### Source excerpt I gave an update 2 weeks ago on the current state of Stockwell (intermittent failures). I mentioned additional posts were coming and this is a second post in the series. First off the tree sheriffs who maintain merges between branches, ... Continue reading -> [Next page]()