How Android Developers Can Meet Google Play's 12-Tester Requirement Without Resets

·1 views

Since November 2023, Google requires Android app developers to complete a closed test with at least 12 active testers over 14 continuous days before an app can go live on the Play Store. The process is harder than it appears, as Google monitors genuine engagement rather than just app installs, meaning a lack of visible activity or tester drop-offs can still result in rejection. Developers are advised to recruit 14–15 testers to account for drop-offs, ship at least one update during the testing window, and track daily active usage rather than total installs. One effective strategy is reciprocal testing, where developers exchange testing duties with peers who face the same requirement, creating mutual incentive to stay engaged for the full two weeks. Communities focused on this kind of peer exchange, such as the Google Play Console Help forum, can help developers find committed testers beyond their personal networks.

Read the full story at DEV Community

This is an AI-generated summary. ShortSingh links to the original source for the complete article.

Discussion (0)

Refurbishing a Tektronix TDS7104 Oscilloscope

Article URL: https://tomverbeure.github.io/2026/08/23/Tektronix-TDS7104-Refurbishing.html Comments URL: https://news.ycombinator.com/item?id=49527232 Points: 4 # Comments: 0

0 comments Read more at Hacker News

ProgrammingDEV Community ·

GitHub Project Routes ChatGPT Planning to Codex Execution via Local Bridge

A public GitHub project called 'Codex with ChatGPT' separates the planning and code-review roles from actual code execution by assigning reasoning tasks to the ChatGPT web app while Codex handles file edits, shell commands, and test runs. The two tools communicate through a local C2C Bridge using structured state messages, with ChatGPT accessing repository context via nine read-only tools covering file reads, Git status, diffs, and test outputs. The project's security design keeps full file bodies and logs out of control-plane messages, and the bridge itself has no write, delete, shell, or commit capabilities, with sensitive paths blocked by default. Setup requires Git, Node.js 20 or later, and Cloudflare's tunneling tool, and uses OAuth 2.1 with one-time pairing codes for the publicly reachable endpoint. The project is an unofficial community effort and has not been endorsed or independently security-assessed by OpenAI.

0 comments Read more at DEV Community

ProgrammingDEV Community ·

EarthLink Network Built Its Entire Operation on AI, Letting Humans Retain Only Judgment

EarthLink Network made AI the operational foundation of its entire company, starting from the premise that all work should run on AI rather than selectively assigning tasks to it. Rather than drawing a human-AI boundary in advance, the company handed over all work to AI first and observed what remained. Through this process, routine tasks with fixed steps — such as data gathering, text cleanup, and repetitive formatting — migrated to AI naturally. What stayed on the human side was judgment: setting priorities, deciding what to drop, and taking responsibility. The company frames this outcome not as an ideology but as a practical conclusion derived from running the experiment and measuring results by convenience and efficiency.

0 comments Read more at DEV Community

ProgrammingDEV Community ·

Developer Ditches Needle2 for llama.cpp and Granite After Local Tool-Calling Tests

A developer building a semantic shell — which maps natural language commands to local filesystem tools — initially tested Needle2, a small model designed for tool calling and structured extraction. While Needle2 worked in basic scenarios, problems emerged as the tool set grew beyond a handful of options, since its retrieval-based shortlisting risked excluding the correct tool before final selection. The developer also found that small models are highly sensitive to tool descriptions, requiring precise, disambiguating language rather than brief documentation-style text. Concerns about whether confidence scores across candidate groups were globally comparable added further uncertainty. Ultimately, the need for native C++ integration without external processes led the developer to switch to llama.cpp paired with the Granite model.

0 comments Read more at DEV Community