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ProgrammingDEV Community ·

TabGen: Free Windows App Converts Plain-English Prompts Into Tableau Dashboards

TabGen is a free, locally-run Windows application that generates editable Tableau .twbx workbook files from plain-English descriptions and user-supplied data files such as CSVs, Excel sheets, or database connections. Users bring their own OpenAI or Anthropic API key, which is held only in session memory and never written to disk, while actual data rows remain on the user's machine. Unlike MCP server-based approaches, TabGen uses a deterministic pipeline that profiles data, validates field names against the real schema, and assembles a complete workbook from proven templates, reducing errors like hallucinated field names or broken calculations. The resulting workbook opens directly in Tableau Desktop or the free Tableau Public for further editing and publishing. The app requires no configuration, bundles its own Python runtime, and is available at tableaugen.com.

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ProgrammingDEV Community ·

How to Diagnose and Fix Flaky Tests in Microservice CI Pipelines

Flaky tests in microservice environments silently drain developer productivity by blocking pull requests, eroding trust in CI pipelines, and obscuring real defects with intermittent failures. The most common root causes include race conditions, non-deterministic data from shared databases or random seeds, external service instability, and overly large integration tests with too many moving parts. Engineers are advised to treat test flakiness like a production incident — measuring impact, isolating scope, and addressing the highest-impact causes first. Reliable diagnosis involves capturing detailed CI metadata, re-running failing tests in identical environments, and isolating dependencies through lightweight service virtualization. Long-term prevention relies on deterministic test data, proper timeout handling, strategic use of mocks, CI quarantine patterns, and ongoing test health dashboards.

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ProgrammingDEV Community ·

Linux Kernel Flaw CVE-2026-43502 Lets Local Attackers Gain Root Access

A critical local privilege escalation vulnerability, dubbed ZcopyReaper and tracked as CVE-2026-43502, was publicly disclosed in September 2026 in the Linux kernel's RDS zerocopy send path. The flaw stems from improper memory reference handling during send operations, which can lead to memory corruption and ultimately kernel-level code execution. A local attacker — such as one who has gained initial access via phishing or a stolen credential — could exploit it to obtain full root privileges on the affected host. On multi-tenant systems, the risk is especially severe, as a single compromised account could expose all tenants sharing the server. Users are advised to apply the relevant kernel patch through their distribution's update channel and reboot immediately, or alternatively block the RDS kernel module from loading if patching is not immediately possible.

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ProgrammingDEV Community ·

Engineer Argues Code Quality Over Speed Is Key When Using AI Coding Agents

A software engineer writing on DEV Community argues that working with AI coding agents requires a disciplined, hands-on philosophy rather than passive code generation. He follows a strict four-step framework: make code correct first, then maintainable, then fast, and finally clean — always in that order. His approach stems from concern that today's LLMs, including GPT-5 and GPT-6, tend to produce low-quality, bloated code without careful human oversight. He emphasizes that early-stage codebases demand especially close attention, as poor patterns introduced early are compounded by the relentless output of coding agents. In an era where writing code is no longer the bottleneck, he contends that a software engineer's greatest value lies in the judgment to reject substandard code and remain accountable for what ships.

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ProgrammingDEV Community ·

Running a Local AI Stack on RTX 3090 Cost Just €2 in Electricity Over 30 Days

A developer running a local AI stack — including a permanent Whisper transcription service and an embedding model on an NVIDIA RTX 3090 — measured actual electricity costs over 30 days and found the GPU drew only €2.00 worth of power. The low cost is explained by the nature of inference workloads: the GPU averaged just 25 watts, sitting mostly idle at around 35 watts and spiking to roughly 120 watts only briefly during active transcription. The Whisper ASR service accounted for €1.76 of the total, while the embedding model cost just 23 cents for the entire month. The author notes that the dominant cost of local LLMs is hardware amortisation — an RTX 3090 purchased used for €800–1,200 works out to roughly €25 per month over three years — not electricity. The key takeaway is that a home inference stack behaves like a mostly idle appliance rather than a continuously loaded training rig.

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ProgrammingDEV Community ·

Java 25 Flexible Constructor Bodies Eliminate Need for Static Factory Workarounds

Java has long required developers to use static factory methods to validate arguments before calling super(), leading to verbose and cluttered domain code. Java 25 LTS will standardize flexible constructor bodies through JEP 492, expected in 2026, allowing pre-construction logic to run directly inside constructors. The feature enables validation, argument transformation, and defensive copies to be placed in a constructor prologue before super() is invoked. The compiler enforces safety by prohibiting any reference to 'this' until after super() executes, preventing uninitialized object leakage. This change aims to restore idiomatic object-oriented instantiation and reduce boilerplate by eliminating static factories created solely for pre-super validation.

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ProgrammingDEV Community ·

TypeSafe AI's Jev Model Makes Decisions Without Generating Any Text

TypeSafe AI, founded by former OpenAI researcher Diogo Almeida, launched a model called Jev on September 15 that performs structured decision-making without generating any text. Backed by $40 million in funding led by DCVC after two years in stealth, Jev accepts a state and predefined questions, returning calibrated yes/no, multiple-choice, or scale-score outputs in 70–500 milliseconds. The company claims it is 20–200 times faster and up to 400 times cheaper than frontier large language models on decision tasks, priced at $0.042 per million input tokens with free output. Within 48 hours of release, developers used Jev for tasks such as browser-operation decisions and context compression, highlighting strong early community adoption. The launch has prompted broader discussion about how many calls inside AI agent systems never actually required language generation at all.

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ProgrammingDEV Community ·

System One's Jev Is a Decision-Only AI Model Built for Fast, Cheap Classification

System One has developed Jev, an AI model that functions as a classification system rather than a large language model (LLM). Unlike LLMs, Jev does not generate text responses; instead, it outputs binary decisions — essentially yes or no — making it free from hallucinations. The model is trained using a method called Reinforcement Learning for Calibrated Decisions (RLCD), which is designed to improve decision accuracy. Jev is reported to be significantly faster and more cost-effective than conventional LLMs. Its primary use cases include AI automation pipelines and any application where precise, reliable classification decisions are critical.

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ProgrammingDEV Community ·

Why websites block scrapers and how anti-bot systems actually work

Websites use layered anti-bot systems that go far beyond simple request checks, examining browser behavior, timing, and subtle technical signals to distinguish real users from automated scripts. A common pitfall for scrapers is receiving a fake success response — the site returns a block page while reporting no error, meaning collected data can appear complete but actually be worthless. Mimicking browser headers or using automated browsers offers partial protection, but dedicated detection systems are trained to identify the telltale patterns these tools leave behind. The most reliable approach is using a genuine, unmodified browser guided quietly to collect data, leaving nothing artificial for detection systems to flag. Maintaining consistent data access over time is considered the harder and more valuable challenge, since anti-bot measures are updated continuously and a working method today may fail within weeks.

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ProgrammingDEV Community ·

Dual AWS autoscaling policies caused fleet oscillation; single occupancy metric fixed it

A fleet of stateful EC2 worker instances experienced erratic scaling behavior after two independent autoscaling policies — one tracking average CPU and another monitoring per-instance free slots — began conflicting with each other. Each policy reacted to its own metric without awareness of the other, causing the fleet to scale up and down in a self-defeating loop. The root cause was identified as an emergent distributed-systems problem rather than a bug in either individual policy. The fix was not to tune the timing of either policy, but to replace both with a single Target Tracking policy using CloudWatch Metric Math to compute real-time slot occupancy across the fleet. Consolidating to one scaling authority with one capacity-reflecting metric eliminated the oscillation entirely.

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ProgrammingDEV Community ·

Developer builds post-work AI pricing system using a calibrated judge model

A developer experimented with a usage-based API pricing model where cost is determined after the work is completed, rather than by token or call count. They used a lightweight model called Jev to assess the complexity of each AI-generated answer and assign a price based on probability distributions across three work tiers. Instead of rounding probabilities into fixed buckets, the system charges the statistical mean, allowing prices to reflect nuanced output quality more accurately. A grounding check was also incorporated, multiplying the expected price by how well the answer was supported by actual source material. The project highlighted that calibrated probability distributions carry more pricing information than discrete tiers, and that verification checks require relevant context to produce meaningful results.

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ProgrammingDEV Community ·

How One Ed-Tech Platform Built a Reliable ETL Pipeline for 25M+ Student Records

An education technology platform engineered a distributed ETL pipeline capable of processing over 25 million records per sync cycle across more than 120 school districts, each with distinct data volumes and failure characteristics. The core challenge was not raw throughput but verifiable correctness — a job could complete without errors yet still deliver an incomplete dataset, making silent data loss a real operational risk. Engineers elevated reconciliation, observability, and auditability to first-class pipeline requirements rather than treating them as post-incident tasks. The architecture was designed around the assumption that partial failures — from network outages to restarting workers — are inevitable at this scale, so every failure mode needed to be detectable, safe to retry, and fully explainable. The resulting system provides a granular audit trail for every district sync, tracking records received, validated, processed, and rejected at each pipeline stage.

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ProgrammingDEV Community ·

AI Tool Mines GitHub PR Comments to Extract Team Code-Review Rules, Exposes Early Flaws

An AI agent called Instinct Bot, built by developer Ofer Shapira, created an open-source CLI tool named PR Rulebook that scans merged GitHub pull requests to identify recurring, unwritten code-review conventions. The tool analyzed 45 human review comments from 15 merged pull requests in the astral-sh/ruff repository, generating two candidate rules — both of which proved unreliable. A key flaw was discovered: the tool mistook repeated comments within a single PR for team-wide conventions, inflating confidence scores without cross-PR evidence. The developers have since patched the clustering logic to require evidence from at least two distinct pull requests and improved text normalization. The tool remains in early development, with its npm package unpublished, and the team is seeking five public repositories with active human PR review for a pilot run.

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ProgrammingDEV Community ·

Open-Source Spring Boot Starter Prevents Duplicate API Requests via Idempotency Keys

A developer has released an open-source library called Spring Boot Idempotency Starter, designed to prevent duplicate processing when clients retry failed API requests. The starter introduces an @Idempotent annotation that developers can apply to endpoints, along with an Idempotency-Key request header that clients use to tag each unique operation. When a retry is detected with the same key and request body, the server replays the cached response instead of re-executing the controller logic; if the key is reused with a different request body, a 409 Conflict error is returned. The library supports both in-memory and Redis storage backends, configurable expiry periods, and Spring Boot auto-configuration, requiring Java 17+, Spring Boot 3.x, and Maven 3.8+. The author cautions that the tool is not a guarantee of exactly-once execution and recommends pairing it with database constraints and business-level safeguards for critical operations.

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ProgrammingDEV Community ·

Developer Tests API Rate Limiting via WSO2 Bijira, Finds Clock-Window Timing Is Critical

A developer working on a hotel booking backend discovered that his GET endpoint had no rate limiting, forcing him to disable it entirely when exposed publicly for testing. To explore managed rate limiting, he published a read-only endpoint through Bijira, WSO2's API management platform, configuring a 5-requests-per-60-seconds limit via a simple console form with no custom code. Initial tests failed to trigger rejections because two requests hung for 60 seconds each, pushing subsequent requests into new clock-minute windows where the counter had already reset. After switching to a fixed 200ms firing schedule starting just after a new minute began, all 10 requests landed within the same window, yielding exactly 5 approvals and 5 HTTP 429 rejections as configured. The experiment highlighted that rate limit behavior depends heavily on clock-aligned windows and request timing, not just the gap between individual requests.

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ProgrammingDEV Community ·

Remove White Video Backgrounds in Browser Using Canvas API and WebGL

Web developers often struggle with videos that have white backgrounds, since standard formats like MP4/H.264 do not natively support alpha transparency. A browser-based approach using the Canvas API or WebGL in JavaScript can solve this without desktop software like Premiere Pro or After Effects. The technique involves drawing video frames to an HTML5 canvas, reading pixel data, and setting the alpha channel to zero for white or near-white pixels. A smooth falloff threshold can be applied to off-white edges to prevent jagged borders, with the process looped frame-by-frame via requestAnimationFrame(). Free online tools that run the same logic locally in the browser are also available for those who prefer a no-code solution.

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ProgrammingDEV Community ·

How One Developer Built a CI/CD Pipeline and Discovered Its Real Complexity

A computer science student who previously used managed platforms like Vercel and Render decided to implement a CI/CD pipeline from scratch using GitHub Actions, which reshaped their understanding of the technology. They learned that Continuous Integration automatically verifies and builds new code, while Continuous Deployment pushes that validated code to a live server. GitHub Actions offered key features including configurable events, parallel jobs for frontend and backend, and ephemeral hosted runners on Ubuntu, Windows, or macOS. Because their home server sits behind CGNAT and lacks a public IP, direct SSH access from GitHub Actions was impossible, ruling out a standard deployment approach. The developer solved this by registering their own server as a self-hosted runner, letting GitHub Actions orchestrate jobs while the local machine handles actual deployment execution.

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ProgrammingDEV Community ·

AI Tools Build Frontends, Not Websites — Developer Explains the Real Gap

A web developer writing on DEV Community describes a recurring pattern in 2025 where clients present AI-generated sites and question professional development fees. The developer responds not with arguments but with four practical questions covering hosting, contact form functionality, DNS configuration, and database connectivity. According to the developer, none of the clients asked this year could answer all four questions, and most could answer none. The core issue is that AI tools produce polished frontends that work in preview environments but lack the backend infrastructure — servers, email routing, DNS setup, and data storage — needed to function as real, publicly accessible products. The developer emphasizes this is not a criticism of clients but a reflection of how convincingly complete AI-generated interfaces appear before deployment realities emerge.

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ProgrammingDEV Community ·

Open-Source Java Library Converts Sinhala Script to Latin Characters

A developer has released Sinhala Transliterator, an open-source Java library designed to convert Sinhala script into Latin characters using predefined mapping rules. The library supports Sinhala vowels, consonants, and diacritics, and can be integrated into Maven-based Java projects via a simple dependency. Transliteration differs from translation — it represents text phonetically in another script without changing its meaning. Potential use cases include displaying Latin-script versions alongside Sinhala text and building Sinhala text-processing tools. The project is licensed under Apache License 2.0, and the developer is actively seeking feedback on accuracy and edge cases through GitHub.

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