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The article examines the drawbacks of writing raw CSS, explains how preprocessors, naming conventions, modular approaches, CSS‑in‑JS, and atomic‑CSS frameworks like Tailwind and UnoCSS address redundancy, maintenance, and scalability, and provides best‑practice recommendations for modern front‑end development.
This article presents a comprehensive AI-driven solution for automatically generating functional test cases, detailing the AI background, design scheme, core components such as PRD parsing, test‑point generation, test‑case creation, knowledge‑base construction, implementation results, and future development directions.
This article explains the need for automated, module‑level code impact analysis in large‑scale projects, outlines a multi‑step technical solution—including dependency‑graph construction, change detection, CI/CD integration, caching and optimization—and demonstrates how it improves testing coverage, system complexity assessment, and overall stability while reducing manual effort.
This article provides a detailed technical walkthrough of the DSearch search engine evolution, covering the RCU‑based 1.0 index architecture, the segment‑merge enhancements in 2.0, and the async non‑blocking graph framework introduced in 3.0, together with performance benchmarks and implementation details.
Meng, a former Tencent and Alibaba engineer, led Dewu’s one‑stop large‑model training and inference platform, cutting integration costs, creating a shared GPU pool and CI/CD pipeline, building a Milvus vector‑database, and driving self‑directed learning that boosted business value, user experience, and set a roadmap for future RAG and cloud‑native optimizations.
The article explains Anthropic’s Model Context Protocol, outlines its architecture, and provides a step‑by‑step guide to creating a Spring AI‑based MCP server in Java—including adding the starter, defining @Tool‑annotated services, packaging the jar, configuring the Cline plugin, and demonstrating advanced tools such as Elasticsearch queries.
GreptimeDB solves front‑end observability challenges with a distributed architecture (frontend, datanode, flownode, metasrv), transparent two‑level caching, elastic scaling, and an SQL‑based flow engine for real‑time multi‑granularity aggregation and approximate counting, delivering millisecond query latency and cost‑effective storage.
The article presents the Business Parameter Configuration Center (BPCC), a declarative platform that automatically generates front‑end pages and corresponding CRUD services, detailing its layered architecture, core concepts such as elements, dimensions, parameters and schemes, SDK query flow, priority rules, multi‑selection handling, import/export workflow, and outlining scenarios where BPCC is unsuitable.
The unified exchange mall middleware platform consolidates disparate points‑redemption and lottery flows into a four‑layer architecture—business, gameplay templates, domain models, and downstream services—offering standardized APIs, dynamic RPC routing, Redis‑based inventory control, anti‑fraud safeguards, and built‑in monitoring, thereby cutting development costs, enhancing maintainability, and ensuring system stability.
In 2024 DGraph upgraded its architecture by splitting single clusters into multiple business‑specific clusters, adopting a sharded active‑active topology, and replacing its 1:N thread‑pool with an M:N grouped execution model that uses atomic scheduling, while parallelizing FlatBuffer encoding, streamlining SDK conversions, adding DAG debugging, timeline analysis, and dynamic sub‑graph templates to boost scalability, stability and developer productivity.
