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Baidu Intelligent Testing

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Latest from Baidu Intelligent Testing

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Baidu Intelligent Testing
Baidu Intelligent Testing
Jun 19, 2018 · Information Security

Comprehensive Guide to Android App Security, Reverse Engineering, and Protection Techniques

This article presents a detailed overview of Android app security threats, the essential components of an Android project, the full APK build and decompilation process, and a range of reverse‑engineering tools and protection strategies—including Smali analysis, SO manipulation, and signing bypass—to help developers safeguard their applications against piracy and data tampering.

APKAndroidApp Security
0 likes · 13 min read
Comprehensive Guide to Android App Security, Reverse Engineering, and Protection Techniques
Baidu Intelligent Testing
Baidu Intelligent Testing
Jun 5, 2018 · Artificial Intelligence

Applying Deep Learning for Automated UI Bug Detection in Mobile Apps

To address the rising cost of manual UI testing on diverse mobile devices, the article presents a deep‑learning‑based solution using PaddlePaddle that automatically detects UI style bugs such as misaligned controls, text overlap, and blank spaces through data‑driven model training, image preprocessing, and classification.

AutomationPaddlePaddleUI testing
0 likes · 10 min read
Applying Deep Learning for Automated UI Bug Detection in Mobile Apps
Baidu Intelligent Testing
Baidu Intelligent Testing
May 8, 2018 · Artificial Intelligence

Interview with Baidu QATC Chair Yang Fei on AI Testing Challenges and the Future of QA

In this interview, Baidu QATC chair Yang Fei discusses his career, the evolving scope of quality assurance from code to AI model testing, key challenges such as service quality and model interpretability, practical approaches for defect discovery, continuous evaluation pipelines, and advice for QA professionals' personal growth.

AIBaiduCareer Development
0 likes · 7 min read
Interview with Baidu QATC Chair Yang Fei on AI Testing Challenges and the Future of QA
Baidu Intelligent Testing
Baidu Intelligent Testing
May 4, 2018 · Operations

Common Architectural Design Risks and Mitigation Strategies for System Stability

This article analyses fifteen typical architectural design risks—such as duplicate interactions, high‑frequency calls, redundant requests, non‑reentrant interfaces, unreasonable timeouts, retry misconfigurations, IP direct‑connect, cross‑datacenter calls, weak/strong dependencies, third‑party reliance, cache penetration, cache avalanche, and coupling issues—explaining their definitions, impacts, detection methods, and concrete mitigation measures with real‑world Baidu cases to help engineers improve system stability.

Testingarchitecturebackend
0 likes · 27 min read
Common Architectural Design Risks and Mitigation Strategies for System Stability
Baidu Intelligent Testing
Baidu Intelligent Testing
Apr 16, 2018 · Operations

Online Load‑Testing Practices for Baidu Nuomi Marketing Activities

This article presents a comprehensive case study of Baidu Nuomi's online load‑testing methodology for high‑traffic marketing events, covering capacity estimation, test planning, execution, anti‑attack measures, platform architecture, and lessons learned to ensure system reliability and performance under peak loads.

Load Testingcapacity planningonline testing
0 likes · 16 min read
Online Load‑Testing Practices for Baidu Nuomi Marketing Activities
Baidu Intelligent Testing
Baidu Intelligent Testing
Apr 3, 2018 · Operations

Evolution of Baidu's System-Level Testing Platform

This article reviews the six‑year evolution of Baidu's system‑level testing technology, describing how the testing approach progressed from manual testing through automated scripts, platform integration, cloud‑based testing, and finally a modular, service‑oriented testing platform to support large‑scale continuous integration.

AutomationTesting Platformsoftware quality
0 likes · 12 min read
Evolution of Baidu's System-Level Testing Platform
Baidu Intelligent Testing
Baidu Intelligent Testing
Mar 28, 2018 · Fundamentals

Common CPU Performance Pitfalls in C/C++ Programs and Their Diagnosis

The article examines common CPU performance pitfalls in C/C++ programs—such as excessive memset, inefficient string copying, improper container usage, lock contention, and heavy I/O logging—provides concrete code examples, compares profiling tools, and recommends best practices to reduce CPU consumption.

Lockscpu-profilingmemset
0 likes · 14 min read
Common CPU Performance Pitfalls in C/C++ Programs and Their Diagnosis