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ProgrammingDEV Community ·

Kruskal–Wallis Test: A Nonparametric Method for Comparing Three or More Groups

The Kruskal–Wallis test is a nonparametric statistical technique for comparing three or more independent groups. It serves as an alternative when data fails to meet the assumptions required for a one-way ANOVA, and it is applicable in fields such as education, business, psychology, and healthcare. The test checks whether group distributions differ, and it requires independent groups, ranked outcomes, and independence of observations. Its output is an H statistic and a p-value; a p-value below a threshold like 0.05 suggests at least one group differs, but does not identify which ones, so follow-up tests may be necessary.

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ProgrammingDEV Community ·

Web HIG advises 24px minimum tap targets and 44px for primary touch actions

The Web HIG guidance states that interactive targets must be at least 24 by 24 CSS pixels, matching WCAG 2.2 Level AA, while primary touch actions should ideally measure 44 by 44 pixels. The clickable area, not the visible icon, is what counts, so small icons can be made easier to hit by adding padding. Tightly packed controls such as close buttons, table row actions, and pagination links are common problem areas, since a miss can trigger the wrong action. The guidance notes that people with tremors or limited dexterity, not just touch users, benefit from larger targets. Developers are advised to measure the clickable element's box in browser developer tools and test primary actions by hand on a phone.

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ProgrammingDEV Community ·

Push-sync design for Google Sheets and n8n avoids full re-reads on every run

Cron workflows that read an entire Google Sheet each run incur heavy costs, since the Sheets node downloads everything before narrowing results, which becomes slow at around 50,000 rows. The article notes the Visualization query endpoint can read a single column cheaply but is only suited to queries, not synchronization. The recommended alternative inverts the flow: the sheet pushes row edits to n8n via an installable Apps Script trigger, and n8n maintains a projection of the data. Row numbers are used only for diagnostics because they shift when rows are sorted or deleted, while identity is keyed on an ID column. Invalid payloads are logged and rejected with a 422 response, since the script caller fails silently by default.

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ProgrammingDEV Community ·

How to Find the Project Behind a Port on macOS Using lsof

A common problem for developers is opening localhost:3000 and finding the wrong app, since every dev server appears as node in process lists. The article explains that macOS lacks Linux's pwdx command, but lsof can reveal the working directory of the process listening on a given port. It walks through using lsof with the -sTCP:LISTEN flag to isolate the server, then the cwd descriptor to print the folder it was launched from. The guide also covers retrieving the full command line with ps, the start time, and the git branch, and offers a reusable shell function called whoport to combine these steps. It further notes that the same approach helps distinguish multiple worktrees or servers running in the same repository.

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ProgrammingDEV Community ·

Guide to two-stage retrieval and reranking for balancing recall, precision, and latency

The guide explains how to separate candidate retrieval from relevance reranking in search-and-generation systems. It describes a funnel in which a fast first stage pulls a broad set of candidate passages and a slower reranker narrows them to the most relevant few. A table maps common symptoms, such as low answer relevance, high latency, token budget overruns, and missed clauses, to likely root causes and checks. The article also outlines component responsibilities, latency targets, and deterministic filtering rules, along with a sample function for tuning top-N and top-k within token and latency limits. It closes with monitoring practices such as tracking hallucination rates and keeping configuration documentation in sync.

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ProgrammingDEV Community ·

How to Structure Product Demos That Convert, Plus a Review Checklist

This guide explains how product demos, which are short focused presentations of a product solving a real problem for a specific buyer, can be made more persuasive. It recommends showing the outcome first, then only the few steps needed to reach it, so viewers do not lose track. The article outlines the main demo formats, including live sales demos, recorded walkthroughs, interactive tours, and short social clips, each suited to different stages of the buying journey. It also explains that demos help buyers see the product working for someone like them, which both builds interest and filters out poor-fit prospects early. Finally, it offers practical advice on recording and polishing demos, such as using realistic sample data and keeping the screen readable.

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ProgrammingDEV Community ·

Fixed vs random effects in Python: what a Hausman test rejection really means

A DEV Community tutorial walks through choosing between fixed and random effects panel models using the wage_panel dataset from linearmodels, covering 545 individuals over eight years. The author computes a Hausman statistic by hand, getting chi-squared of 112.118 with 3 degrees of freedom and p near zero, which rejects the random effects assumption. The piece cautions that such a rejection only suggests RE is inappropriate and does not prove fixed effects is correct, since time-varying confounders remain. It also notes that fixed effects cannot estimate coefficients on time-invariant variables and that the classic Hausman test assumes homoskedastic errors, so the Mundlak regression-based approach is suggested for clustered standard errors. The author also mentions an online panel regression tool they are affiliated with.

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ProgrammingDEV Community ·

Databricks Interview Questions Lean Toward Classic System Design, Not AI

An analysis of 29 reported Databricks system design questions finds that 24 are classic system design problems, while only 5 concern AI systems or ML. The most frequently reported questions are coding problems, several of which appear at no other company tracked in the dataset. The coding screen is a 60-minute live session in a runnable editor, drawing repeatedly from a small set of four problems. Candidates identify concurrency as the hardest part of the interview loop, with seven questions testing it. The comparison suggests that candidates preparing for AI labs like OpenAI or Anthropic will still need to study classic system design for Databricks.

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ProgrammingDEV Community ·

LinguaPal: Multi-Agent AI App Offers Personalized English Tutoring

LinguaPal is a web application that uses Google Gemini and five specialized AI agents to help learners practice English. It covers reading, pronunciation, listening, writing, and spelling through lessons matched to CEFR proficiency levels. The app adjusts difficulty over time, analyzes voice input, and gives personalized feedback. It also uses a spaced repetition system built on SQLite, based on the SuperMemo SM-2 algorithm, to schedule review. The project was submitted under the AI and Machine Learning category, with its source code and a demo video publicly available.

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ProgrammingDEV Community ·

Entry-level developer hiring in 2026 favors debugging, AI judgment, and shipped projects

Junior software roles are shrinking as AI now handles many routine coding tasks, but companies are still hiring new engineers who can show different signals. The article outlines a seven-stage roadmap for landing a first developer job, starting with fundamentals like debugging and reading existing code. It stresses using AI tools responsibly, meaning reviewing and fully understanding any generated code rather than depending on it. It also recommends building one or two real, deployed projects with users and tests, and citing a 2026 survey in which many juniors ranked problem-solving as the top hiring skill.

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ProgrammingDEV Community ·

Four Plex Media Server CVEs fixed by one upgrade to version 1.43.3.10861

CISA groups four identifiers under Plex Media Server, three of which are request-handling flaws enabling SSRF or URL injection and one that allows arbitrary file writes. The flaws affect versions below 1.43.3.10861, which is listed as unaffected. Prerequisites vary, with one flaw requiring no credentials and others needing a token, an account, or admin rights. The file write flaw is rated with total technical impact, while the request flaws are rated partial. Users are advised to upgrade, restrict search and timeline endpoints to trusted networks, limit admin accounts, and monitor plugin directories for new shared objects.

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ProgrammingDEV Community ·

Seven Confluence Alternatives Compared for Large Enterprise Migration

Replacing Confluence at a large organization involves more than moving pages, since teams must keep information findable, maintain it collaboratively, manage access, and preserve links and ownership. The article compares seven alternatives across knowledge structure, permissions, collaboration and version history, migration suitability, and AI readiness. It presents the comparison as a shortlist that should be checked against representative content and actual access rules before any broad rollout. Each candidate is matched to use cases, such as ONES.com for connecting knowledge with project work, SharePoint for Microsoft 365 shops, and GitBook for developer documentation. The guide emphasizes testing migration of links, attachments, and permissions with a sample before committing.

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ProgrammingDEV Community ·

Researchers Map Inner Circuits of AI Models to Make Them More Transparent

Large language models perform complex reasoning, yet even their builders often cannot trace how a given answer was produced, which is a serious concern in high-stakes fields like healthcare and defense. A new discipline called mechanistic interpretability aims to reverse-engineer a trained model's neurons, weights, and attention heads into understandable algorithms and logic circuits. Techniques such as sparse autoencoders are being used to isolate specific internal features tied to concepts like deception, geography, or code syntax. Proponents argue this approach could detect hidden deceptive behavior before deployment and enable targeted edits to models without full retraining. Overall, the field is presented as a way to keep increasingly capable AI systems transparent and aligned with human values.

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ProgrammingDEV Community ·

Google's Content API for Shopping retirement: what custom Merchant Center integrations must change

Google retired version 2.1 of the Content API for Shopping on August 18, 2026, and requests from projects without an active extension now intermittently fail with HTTP 410 and a content_api_sunset error. All requests are expected to stop working in early 2027. The article notes that managed ecommerce platforms usually handle the migration, so the guidance targets teams maintaining custom scripts or feed services. Developers are advised not to retry failed calls and to log the sunset reason explicitly, since silent failures can leave product data stale in Merchant Center. The migration requires enabling the Merchant API, registering the Google Cloud project with the Merchant Center account, creating an API-input data source, and updating method names, product ID formats, and price structures. The author also promotes a free static scanner and a paid diagnostic service offered by their company.

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ProgrammingDEV Community ·

ggufit: A One-File CLI That Checks If a Local GGUF Model Fits Your GPU's VRAM

A developer grew frustrated with discovering out-of-memory failures only after downloading large local language models, so they built ggufit, a standard-library-only Python script. The tool reads a GGUF file's header to determine its real architecture and quantization, then estimates whether the model fits a chosen GPU. It accounts for KV cache at a given context length and compares requirements against usable VRAM after driver and OS reserves. Users can also check models before downloading by supplying parameter count and quantization manually, and the tool offers suggestions such as shorter context or partial CPU offload when a model won't fit. The project is MIT-licensed and hosted on GitHub.

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ProgrammingDEV Community ·

memgraph: a zero-dependency CLI that tracks decisions, sources and contradictions

A developer describes a team problem: a queue decision was reversed last month and no one could explain the original reasoning. They present memgraph, a zero-dependency Node.js command-line tool that records decisions and facts, links them to sources, and marks contradictions and superseded decisions. The tool answers why a decision was made, whether anything is stale or contradictory, and what the team currently believes. Its check command exits with an error code when problems are found, so it can run in continuous integration. The project is MIT-licensed, requires Node.js 18 or later, and is available on GitHub.

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ProgrammingDEV Community ·

Laser rangefinder module prices range from $70 to $5,000, with key cost jumps at 1535 nm

A survey of 59 published laser rangefinder module prices, from $70 to $5,000, shows how cost relates to capability. Entry-level 905 nm short-range modules start around $70 to $100, while the cheapest long-range 905 nm units sit near $200. Costs jump sharply from roughly $300 to $900 and above because 1535 nm modules require InGaAs detectors, higher eye-safety margins, and thermal management. The article also notes that range figures depend on target reflectivity, minimum range, interface type, and what is included in the package, so per-unit prices alone can mislead buyers. Volume pricing is quoted per order and varies by model.

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ProgrammingDEV Community ·

Kotlin's Null Safety Makes Missing Data Part of the Type System

The article argues that many hard-to-reproduce crashes stem from code that assumes data will always be present, such as an optional profile field or an empty API response. It explains that Kotlin addresses this by encoding nullability directly in its type system, so a nullable variable cannot be accessed as if it were guaranteed to have a value. Safe-call syntax lets developers read nullable properties without triggering crashes, returning null when the value is missing. The elvis operator provides a fallback value when a null should be replaced with a default, such as a regular name in place of a nickname. Together, these features shift developers from remembering manual null checks to expressing in code which data may be absent.

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ProgrammingDEV Community ·

6pm 2.0.0 adapts its layout to the iPhone Duo's folding hinge

Apple's iPhone Duo goes on sale on October 23, and the team behind the daily money app 6pm built support for its fold using the iOS 27.1 SDK. The developers used UIHingeInteraction and reserved-region APIs to read the hinge state, angle, and screen divisions, then bridged that data into React Native through a small Swift Expo module. A pure layout function decides between phone, rail, spread, and stand arrangements based on the fold's posture. The update is set to ship in version 2.0.0 on the App Store on November 6, and the project's source code is available under an Apache 2.0 license.

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ProgrammingDEV Community ·

SlothAI: Open-Source, Offline AI Tools That Run Locally via Ollama

SlothAI is an open-source web companion that runs open-weight models such as Llama 3.2 locally on a user's hardware through Ollama, avoiding recurring cloud subscriptions and remote data sharing. It bundles six micro-tools aimed at everyday tasks, including summarizing long texts, drafting polished emails, making quick decisions, reorganizing to-do lists, writing bedtime stories, and generating reply options. The project is built with plain HTML, CSS, and vanilla JavaScript without frameworks, keeping it under 40 KB, and it streams model output in real time. Setup requires cloning the repository, starting a local server, and running the model through Ollama. The developers present privacy as the main advantage, since personal data stays on the user's machine instead of going to third-party servers.

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