This guide explains why Maven dependency analysis is essential, shows how to run mvn dependency:analyze, interprets warnings about used undeclared and unused declared dependencies, and offers practical tips for when and how to clean up your project's pom.xml safely.
This article explains why Maven dependency analysis is essential for Java backend projects, demonstrates how to run the analysis with Maven and IntelliJ IDEA, interprets the warnings about used undeclared and unused declared dependencies, and provides best‑practice timing, risks, and shortcuts for maintaining clean dependency trees.
The article explains how Google tackles the costly problem of dead code in its massive monorepo by using the Sesenmann automated deletion system, which leverages build‑system dependency graphs, activity signals, and graph‑analysis algorithms to safely identify and remove unused C++ code while addressing cultural resistance among engineers.
This article explains how to accurately test, record, and maintain art asset dependencies in Unity projects, describing the use of Unity's Select Dependencies interface, database design for storing direct and indirect relationships, and practical applications such as automated SVN integration, resource cleanup, and impact alerts.
Software Composition Analysis (SCA) identifies and tracks open‑source components across languages, matches them to vulnerability databases, and integrates risk detection into CI pipelines, helping organizations mitigate widespread flaws like Log4j2 while addressing challenges of diverse package formats, binary analysis, and accurate vulnerability correlation.
This article explains how ByteDance's distributed compilation and build caching solution dramatically reduces compile times for large iOS projects by analyzing dependency bottlenecks, employing distributed builds, caching mechanisms, and various optimization techniques such as inverted indexes and cross-task caches.
Google Open Source Insights researchers examined every Maven Central package version, revealing that over 8% of Java packages are affected by Log4j, most through transitive dependencies, and highlighting the complex, multi‑step remediation required across deep dependency trees.
This article explains how to use Webpack's stats object to generate a JSON report of module dependencies and compilation performance, enabling developers to visualize the dependency graph, identify impact of changes, and fine‑tune build speed and bundle size.
An in‑depth case study of Alibaba.com’s iOS client reveals how architectural decay—manifested as tangled module dependencies, slow builds, and outdated tooling—drains developer productivity, and outlines data‑driven, layered, and automated strategies—including dependency analysis, modular refactoring, and CI safeguards—to restore a healthy, scalable mobile codebase.
After a decade of growth, the iOS app with millions of lines and dozens of third‑party SDKs was re‑architected by converting selected static libraries into dynamic frameworks, employing lazy loading and dependency analysis to reduce download size and improve launch time, while addressing build and compatibility challenges.
This article reviews Midway's 2020 Serverless rollout, detailing how strong/weak dependency analysis, traffic‑model estimation, and multi‑layer traffic control were combined to achieve ten‑fold scale growth and robust stability for Node.js Serverless services across Alibaba's businesses.
This article explains how to leverage Webpack to perform comprehensive file dependency analysis for WeChat mini‑programs, covering the creation of dynamic entry files, custom loaders for wxss, wxml, wxs, and json, handling path issues, and preparing resources for efficient packaging.
The Gaode App full‑chain dependency analysis system parses source code across JS, C++, Android and iOS into ASTs, extracts forward and reverse dependencies, stores them for GraphQL queries, and uses the data to guide regression testing, API deprecation, migration trends, and package‑size optimization, improving codebase governance.
This article explains why modern iOS apps need modular dependency analysis, compares common approaches such as CocoaPods, header scanning, and symbol tools, and then details a source‑level LLVM‑based solution that uses Clang plugins to generate precise method‑level dependency metadata for each bundle.
The article outlines how to classify microservice-based systems into interface, web, and task categories, describes their architectural evolution, and provides a step‑by‑step methodology for identifying core (golden) functions and processes, distinguishing strong and weak dependencies, and implementing resilient disaster‑recovery strategies for large‑scale e‑commerce events.
This article explains how to classify microservice systems, trace their architectural evolution, and conduct thorough dependency analysis to identify strong and weak couplings, enabling reliable governance and disaster‑recovery planning for high‑traffic events such as 618 and Double‑11.
Based on an analysis of 47,251 dependency declarations from 3,862 popular GitHub Java projects, this article presents the 100 most widely used Java libraries, highlights the top 20, examines the rise of Spring components, and discusses notable JSON and other standout libraries.
