The Ant Group invites submissions to its inaugural ISSTA 2025 workshop on reliable, secure, and trustworthy software systems, covering topics such as software reliability, AI-driven testing, model interpretability, LLM verification, runtime analysis, and visualization, with deadlines from March to June 2025.
This comprehensive guide walks software testers through the transition from basic functional testing to advanced automation, performance, and DevOps roles, offering a detailed learning roadmap, practical tips, and curated resources to boost skills, increase marketability, and secure higher‑pay positions in the testing industry.
This comprehensive guide compiles expert answers to common interview questions covering software testing strategies, API automation, performance testing, Linux system administration, Docker and Kubernetes fundamentals, CI/CD pipelines, and effective team management practices, providing valuable insights for candidates and hiring managers alike.
This article shares the author’s real‑world experience with equivalence class partitioning, explaining the concept, illustrating how to apply it to both numeric and non‑numeric game scenarios, and offering practical tips for writing robust test cases and avoiding common pitfalls in QA work.
KuJiaLe's testing team curates ten influential 2024 technical articles covering AI‑driven test case generation, AI‑assisted code review, lead tester training, Greasemonkey efficiency, custom mock platforms, private vs. public LLMs, FastGPT knowledge bases, CI bottleneck solutions, front‑end release strategies, and construction‑drawing regression testing.
This article presents a curated list of 50 common software testing interview questions covering API automation frameworks, performance testing, essential Linux commands, and efficiency‑boosting tools and methods, providing concise answers to help candidates demonstrate their technical expertise.
The article proposes a scenario‑driven, combinatorial testing approach for business‑finance settlement systems that models variable factors, uses t‑way (especially 2‑way) coverage to capture most defects, and leverages tools such as Hexawise and allpairspy to generate minimal yet sufficient test cases, dramatically lowering pre‑release risk.
The article explains how to transform abstract software requirements into executable specifications using scenario‑based BDD, outlines story‑granularity practices, describes a requirement‑instantiation workshop, and details automated verification techniques to improve DevOps efficiency and software quality.
This article outlines how test managers can protect project stability and quality by defining clear testing goals, selecting appropriate test types, planning resources, strengthening requirement management, enforcing strict testing processes, driving automation, integrating CI/CD, applying quality gates, managing defects, fostering team collaboration, monitoring metrics, and promoting knowledge sharing.
This guide outlines systematic steps for gathering environment and error details, reproducing bugs across different setups, analyzing logs and source code, narrowing down problem areas, and effectively communicating with developers, product managers, testers, on‑site staff, and customers to resolve software issues.
This article explains the definitions, goals, and real‑world applications of unit testing, integration testing, and system testing, illustrating each type with clear Python code examples that demonstrate how to verify functionality, interfaces, and overall system behavior in software projects.
This article outlines comprehensive strategies for test managers, covering daily responsibilities, building and motivating efficient test teams, handling conflicts, time‑critical testing, cross‑department coordination, performance evaluation, risk management, communication with non‑technical stakeholders, QA throughout the software lifecycle, tool selection, process optimization, and emerging testing trends.
This article explains mock technology for software testing, demonstrates how to implement a mock service using Flask and MySQL, and provides code examples for setting up mock data and handling requests.
This comprehensive guide covers the essential concepts of software testing, including basic testing types, test case design techniques, defect management, testing tools, test processes, methodologies, and software development lifecycle models, providing clear definitions and practical advice for each topic.
The DeWu Tech Salon in Shanghai gathered over 220 participants and featured four expert talks on AI‑driven testing, simulation automation, precise testing platforms, and ad‑algorithm gray‑scale interception, offering concrete strategies and measurable gains for improving software quality and development efficiency.
This article compiles 30 essential interview questions covering fundamentals, API pagination, HTTP status codes, JSON schema validation, CORS, test automation frameworks, pytest parametrization and fixtures, mocking, coverage testing, load and stress testing, Locust and JMeter usage, security testing such as SQL injection, XSS, OAuth2, JWT, CI/CD concepts with Jenkins, GitHub Actions, Travis CI, Docker, and Python code quality tools like static analysis, black formatting, unit testing, refactoring, and technical debt management, each accompanied by concise explanations and runnable code snippets.
This guide explains how test developers can efficiently complete diverse testing tasks by understanding task requirements, communicating details, classifying tasks, using visual and questioning techniques, preparing appropriate tools, executing work with structured processes, and reflecting on outcomes to turn experience into reusable skills.
This article describes how KooJiaLe, a leading 3D design company, built an AI‑powered platform that uses large language models to automate test case generation, detailing its workflow, generation modes, editing features, export options, optimization efforts, results, and remaining challenges.
An AI-driven test case generation platform at KuJiaLe leverages multiple large language models, offering three input methods, online editing, and dual export options, while addressing stability, length limits, and security challenges to improve testing efficiency and achieve over 80% success rate.
The QECon Global Software Quality and Efficiency Conference in Shanghai on September 20‑21 will explore how AI—especially AIGC, LLMs, and large models—enhances software development, testing, and performance, featuring expert talks on multi‑device quality assurance and practical test‑shift strategies, highlighting innovative opportunities and real‑world value.
This guide presents a comprehensive set of software testing metrics—including workload deviation, execution and pass rates, coverage, defect detection and lifecycle—to help teams quantitatively assess development progress, test effectiveness, and overall product quality.
Shadow testing is a parallel deployment strategy that minimizes the risk of system changes, safeguards user experience, validates performance and data integrity, and provides a controlled environment for comprehensive testing, supported by a suite of modern tools and real‑world case studies.
This article explains how comprehensive testing—from early shift‑left practices and lifecycle coverage to automated unit, integration, and end‑to‑end tests—ensures software quality, reduces costs, and supports rapid development, illustrated with real‑world case studies and practical design techniques.
This article introduces the pytest-httpserver plugin for launching a simple HTTP server during tests, provides installation instructions, and walks through ten practical examples covering GET, POST, headers, query parameters, request counting, error codes, redirects, file uploads, timeouts, and client certificate verification.
The article explores Heidegger’s concept of "Bestand" (resource), explains how it transforms our view of objects into readily usable assets, and examines its impact on software testing—from automation tools and virtualized environments to CI/CD pipelines and outsourced test resources—highlighting both efficiency gains and potential quality blind spots.
This article explains idempotency testing, outlines common scenarios such as network requests and financial transactions, describes methods to detect duplicate requests, provides comprehensive coverage strategies, offers practical test‑case examples, lists relevant testing tools, and includes a JUnit code sample for implementation.
This article shares fourteen practical lessons learned from real‑world automation testing, covering when to automate, scope definition, tool selection, team coordination, ROI considerations, open‑source pitfalls, code reuse, and the balance between automated and manual testing.
This article explains how to evaluate the implementation cost of automated testing, break down human, time, and tool expenses, assess benefits such as time and cost savings, quality improvements, and test coverage, and calculate ROI using a clear formula and practical examples.
This article explores how large language models can automate test case generation, predict defects, analyze results, optimize strategies, execute intelligent testing, and assist compatibility checks, while providing practical tools, real-world case studies, and a step‑by‑step GPT‑4 testing workflow.
The article presents a comprehensive overview of Google’s code‑coverage system, describing its metrics, integration into the daily development workflow, underlying infrastructure, visualization tools, data‑driven analysis of five years of coverage data, and developer survey results that reveal adoption patterns and perceived usefulness.
The MTSC 2024 Shanghai conference gathered top testing experts to discuss AI‑driven testing, full‑chain 3D rendering ecosystems, UI automation for graphics software, and front‑end performance assurance, offering a comprehensive look at emerging quality‑assurance practices and future collaborations.
Smoke testing, also known as build verification or sanity testing, is a lightweight regression subset that quickly validates core functionality after each build, providing rapid feedback to catch critical issues early and maintain code stability throughout the development lifecycle.
This guide outlines a transparent, actionable software acceptance testing workflow—covering purpose, scope, startup, project initiation, test planning, design, case maintenance, review, functional verification, production line acceptance, archiving, and final summary—to ensure quality and compliance across product development, testing, and operations teams.
This guide presents a detailed five‑level competency framework for test development engineers, covering test analysis, design, planning, execution, reporting, project management, development, security, performance, automation, and related technical skills, with behavior grades and descriptions for each area.
This article outlines seven practical reasons why unit testing is crucial for developers, highlighting how automated tests provide fast feedback, improve code robustness, guide design, boost confidence, act as problem detectors, serve as reliable documentation, and accelerate learning of new APIs.
This article examines Google’s two‑decade testing culture, detailing the iconic “toilet test” posters, the development of a testing certification program, the shift toward developer‑driven automated testing pyramids, the challenges of scaling massive test suites, and the evolving role of test engineers within the broader quality engineering framework.
The article reviews typical code‑coverage goals such as 70‑80% for system testing, explains how factors like failure cost, resource constraints, testability, and development stage influence target selection, discusses why full coverage is often impractical, and summarizes major industry standards and coverage metrics used in safety‑critical domains.
This guide outlines comprehensive principles for generating, using, and cleaning test data across development, performance, and production environments, emphasizing independence, realism, security, proper permission controls, and systematic synchronization to ensure reliable and safe testing processes.
Test‑Driven Development (TDD) is a software development methodology that guides developers to write failing tests first, then implement minimal code to pass them, and finally refactor, offering benefits such as higher code quality, clearer requirements, safer refactoring, and reduced long‑term maintenance costs.
This article details the design and implementation of HuoLala’s Lingmu platform, which provides zero‑intrusive traffic recording, gRPC‑compatible replay, multi‑level diff noise reduction, and intelligent problem analysis to dramatically improve map service testing coverage, accuracy, and development efficiency.
The article chronicles Google’s Test Certified initiative from its early challenges in 2005 through the establishment of a multi‑level certification system in 2006, detailing its structure, certification process, scaling efforts, cultural impact, and the lessons learned for improving automated testing practices.
DeWu’s three‑year Quality Management System integrates a risk‑controlled iteration review mechanism, distinct testing and collaboration processes, metric‑driven “Quality Month” methods, and a suite of automation and monitoring tools to standardize, automate, and continuously improve product stability, efficiency, and innovation.
This guide outlines the progression of software testing engineers from junior to senior levels, detailing required education, experience, core testing and programming skills, and provides a structured learning roadmap covering fundamentals, test management, and specialized testing techniques.
Precise testing, a modern approach that defines clear test goals, leverages code analysis, coverage tools, and machine‑learning‑driven test selection, can dramatically improve software quality and efficiency, as demonstrated by case studies in finance, medical devices, and e‑commerce, while also reducing costs.
This article shares practical steps and key insights for conducting a project test retrospective, covering purpose clarification, mindset adjustment, documentation preparation, meeting facilitation, feedback collection, and lessons learned, illustrated with examples from the KE offline rendering cloud map project to help teams improve quality processes.
This article examines the challenges of fully reproducing test environments for bug verification and presents practical strategies—such as selective testing, containerization, and automated provisioning—to reduce resource consumption while maintaining software quality.
This article outlines the various roles, skill dimensions, and career stages in software testing and QA, offering guidance on progression from entry‑level positions to senior management and architectural roles while highlighting the differences between QA and testing responsibilities.
This article explains the concept of testing strategy, outlines its relationship with testing plans, defines the quality‑efficiency‑cost triangle, and provides practical steps and scenarios for designing, evaluating, and continuously improving testing strategies in software projects.
During a four‑month internship at ZhaiZhai, the author describes how they progressed from basic functional testing to mastering various test tools and platforms, gained deeper insight into the role of QA in project workflows, and identified future growth directions in testing methodology and code development.
The article analyzes the concept of test left‑shift, outlining its theoretical benefits and drawbacks, sharing practical pain points from NetEase Cloud Music, and presenting a comprehensive pre‑, during‑, and post‑shift automation and monitoring strategy to improve software quality and delivery speed.
This comprehensive guide explains the purpose, types, standards, entry and exit criteria, tools, step‑by‑step execution process, common challenges, practical recommendations, and best‑practice tips for acceptance testing, helping teams ensure software meets user expectations and release requirements.
The author reflects on why software testers frequently feel they have exhausted learning opportunities, identifies common misconceptions, and emphasizes that hands‑on practice, continuous coding, and real‑world feedback are essential to break the plateau and achieve meaningful growth.
This article explains the architectural distinctions between B/S and C/S models, compares cookies and sessions, outlines the purpose of testing, and provides practical test case designs for pens, triangles, shopping carts, databases, UI automation, weak‑network scenarios, and Python coding examples, offering a comprehensive guide for software testing fundamentals.
This article showcases a comprehensive collection of fourteen detailed diagrams illustrating various automation testing frameworks—including API, UI, mobile, JMeter, CI/CD pipelines, and DevOps practices—providing visual guidance for building robust test architectures across software development projects.
The 2023 software testing industry survey, based on real data from 51Testing, shows rapid growth in automation, AI, and cloud testing, highlights sector distribution, salary trends, preferred tools, future investment areas, and professionals' career outlook and skill development priorities.
A seasoned test developer shares a decade‑long journey, detailing the evolution from functional testing to test automation, the construction of a comprehensive quality assurance system, practical tools for repetitive problems, and personal reflections on perseverance, collaboration, and continuous learning.
This article compares six widely used test case management platforms, explains their target audiences and key features, evaluates their strengths and weaknesses, and offers guidance on selecting the most suitable tool based on team size, workflow requirements, integration needs, and budget constraints.
The 2023 Software Quality Assurance industry survey, based on nearly a thousand valid responses, analyzes testers' employment status, satisfaction, background, technical skills, personal growth paths, team structures, AI/LLM usage, and future industry trends, providing data‑driven insights for professionals and managers alike.
The 2023 testing industry questionnaire, with roughly 850 respondents, reveals employment status, satisfaction scores, career change intentions, demographic distributions, salary trends, technical skill priorities, AI adoption rates, team structures, process bottlenecks, and forecasts for the coming year, offering a comprehensive view of the sector’s health and direction.
This article details Shentong's systematic approach to improving test completeness, covering test case design, a custom Quality Keeper workflow, code‑coverage measurement, precise regression strategies, automation effectiveness, issue‑driven optimization, and future plans such as front‑end coverage and AI‑assisted testing.
This article analyzes six typical time‑related bugs—including timezone conversion, daylight‑saving anomalies, precision mismatches, comparison errors, storage pitfalls, and permission expirations—and provides concrete design and testing safeguards for developers.
The article examines how API automation testing can be measured and implemented effectively, arguing that coverage and pass‑rate targets vary by team context, emphasizing cost‑benefit analysis, prioritizing core interfaces, and focusing on reducing feedback cycles rather than chasing statistical metrics.
This article explains the core concepts, rhythms, and practical applications of Test‑Driven Development (TDD) and Behavior‑Driven Development (BDD), illustrating how the red‑green‑refactor loop and business‑focused scenarios improve code quality, design, and collaboration between developers and stakeholders.
The article analyzes how quality assurance costs scale with product ambitions, compares small‑startup and large‑enterprise testing setups, and explains why automation and testing platforms require sustained investment that only pays off when aligned with business value and cost‑effectiveness.
The article examines why software testers often bear the blame in development projects, lists typical accusations they face, and offers concrete communication strategies and twelve practical recommendations to improve testing practices, clarify responsibilities, and foster better collaboration with developers and product owners.
The article examines why highly skilled test engineers are vulnerable during layoffs, highlighting the mismatch between technical prowess and business value, the importance of workplace networking, resource alignment, evolving testing roles, and current market trends such as platform decline, role consolidation, and growth in automotive testing.
The article traces the evolution of software testing roles in China from the early 2000s PC era through mobile-driven diversification, platform shifts, and recent AI and automotive trends, highlighting how responsibilities, tools, and career expectations have transformed over a ten‑year span.
This article explains how mid‑level and senior software test engineers are defined, highlights the career‑advancing value of certification, and presents a detailed testing skill map covering automation, performance, and security testing techniques and tools.
The article examines the ongoing debate about the necessity of dedicated QA roles, explains why high‑quality projects require systematic testing performed by professionals, outlines appropriate QA‑to‑development staffing ratios, discusses training and management of QA staff, and offers practical guidance for test case management and overall project quality assurance.
This article examines chart‑related requirements from a software tester’s perspective, outlining testing points, typical problems, and concrete case‑based test‑case designs for line, pie, and radar charts to improve test quality and efficiency.
This article provides a comprehensive guide on how test engineers, test leads, and test managers can structure their year‑end summaries by focusing on work responsibilities, project and business insights, and future planning, while offering role‑specific examples, tables, and practical tips to make the summary both meaningful and impressive.
This guide outlines essential principles for effective test automation within DevOps, covering investment planning, test case selection, result consistency, design techniques, language choice, application awareness, robustness, high‑quality test data, exploratory testing, and alert system implementation.
UnitGen, a dataset generation framework derived from UnitEval, combines unified prompts, quality pipelines, and extensible thresholds with language‑specific context strategies and ArchGuard checks to produce both documentation and test datasets for private AI code‑generation models, leveraging the open‑source Chapi AST engine.
This article explains what test cases are, their objectives, essential components, execution process, and the three core principles—accuracy, conciseness, and completeness—that guide the creation of high‑quality, maintainable test cases for reliable software testing.
This article presents a comprehensive test summary of a six‑month project involving eight applications, detailing test objectives, planning, execution cycles, case counts, defect statistics, quality metrics, and management lessons that together delivered a 99.9% transaction pass rate and valuable insights for test leaders.
This article explains how the open‑source AutoDev plugin builds an end‑to‑end AI‑assisted coding solution that fine‑tunes open LLMs, constructs a Unit Eval dataset, engineers prompts for unit‑test generation, and enforces quality through a unified write‑evaluate pipeline.
This article examines why many testing teams skip bug root‑cause analysis, outlines typical scenarios where such analysis is needed, and presents a practical four‑step method—including recording, cause marking, role attribution, and improvement planning—to enhance software quality and team efficiency.
This article explores the evolution of software testing, defines no-code automation testing, outlines its benefits, compares code‑based and no-code approaches, and presents a curated list of 34 leading no-code testing tools for 2023, while also explaining how QA teams can leverage these tools and integrate them with platforms like LambdaTest.
This article explores how software test engineers can leverage ChatGPT for tasks such as requirement analysis, test case creation, defect reporting, functional test generation, API test case generation, and automation script writing, thereby improving testing speed, accuracy, and overall quality.
The article explains why influence is essential for software testers aspiring to leadership, outlines key personal traits, presents common challenges, and provides a four‑step framework—including non‑violent communication techniques and practical case studies—to help testers effectively drive change and resolve conflicts.
This document outlines a complete test plan, testing strategies, resource allocation, schedule, risk management, acceptance criteria, and deployment procedures for an e‑commerce Double‑11 promotion, emphasizing functional, interface, and performance testing to ensure system stability and high‑quality user experience.
Quality assurance is fundamentally about exhaustive falsification to lower online risk, while the testing process seeks optimal ROI by balancing defect discovery against resource investment; a tester’s value hinges on business risk, system maturity, and the ability to become increasingly irreplaceable through deep domain knowledge, proactive risk mitigation, and innovative, end‑to‑end quality solutions.
The article examines three major Alibaba service disruptions, analyzes how insufficient testing and a lack of psychological safety among engineers may have contributed to the failures, and suggests ways to improve testing practices and workplace transparency.
The article defines testability as the precondition for conducting testing at each software lifecycle stage, explains its manifestations during requirements, design, development, and release phases, and illustrates the concept with a performance‑impact example from an e‑commerce order‑detail scenario.
This article explores how software test engineers can leverage ChatGPT to improve efficiency across the testing workflow, including requirement analysis, test case creation, defect reporting, functional and API test generation, and automation script development, while providing code examples and practical tips for integrating AI assistance into testing processes.
This document presents a detailed overview of a software testing project, covering client‑server testing differences, a full test plan and test case examples, an automated testing framework built with Python, as well as personal reflections on strengths, job motivations, and future professional development goals.
This article examines the emerging “shift down” software delivery approach, explains the limitations of traditional shift‑left and shift‑right testing, and shows how integrating both through platform engineering can improve efficiency, security, and agility in modern cloud‑native environments.
This article examines how ChatGPT can be combined with fuzz testing to automatically generate test cases, detailing the research process, design, implementation, performance metrics, discovered bugs, limitations, and future plans for improving AI‑driven automated testing in a real‑world e‑commerce environment.
This article examines how well‑structured test planning, balanced testing costs, risk‑aware quality practices, and project‑wide efficiency measures can significantly improve the return on investment of software testing activities.
This article explains what unit testing is, why it’s essential, and provides a step‑by‑step guide for writing Java unit tests with JUnit, integrating them into Maven projects, and generating detailed coverage reports using IDE features and JaCoCo.
TestAgent is an open-source 7B test-domain LLM that delivers multi-language test-case generation, automatic assert completion, and a rapid deployment framework, offering industry-leading pass@1 scores, a ChatBot UI, and detailed setup instructions for diverse hardware environments.
The article argues that the essence of software testing is risk avoidance, explores why bugs arise from user expectations, outlines three core challenges—investment, recursion, and measurability—and proposes balanced semi‑automated testing strategies to reduce bugs while acknowledging the limits of full automation.
A full‑stack test engineer should combine solid testing fundamentals with programming, web and backend development, database, OS/network knowledge, automation tools, DevOps practices, agile collaboration, and continuous learning to effectively design, execute, and improve comprehensive software tests.
This article introduces XMind2TestCase, a Python‑based tool that converts XMind mind‑maps into test‑case files (CSV, XML, JSON), explains its installation, command‑line and web usage, and discusses the advantages and challenges of using mind‑maps for test case design in agile environments.
This article explains how to prepare the Spark API environment, define prompts for an AI model, and automatically generate valid and invalid equivalence classes and corresponding test cases for a subway ticket self‑service purchase system, complete with expected outcomes.
This article outlines JD Tech's comprehensive quality‑assurance framework for user‑growth projects, covering responsibilities, challenges, core values, a diversified strategy, standardized processes, tool platformization, continuous operations, and measurable metrics to ensure high‑quality delivery across the product lifecycle.
The report analyzes SonarQube‑detected defects in Projects A and B, classifying them by type and severity, revealing that code smells dominate while null‑pointer bugs are unexpectedly frequent, and discusses why some defects are quickly fixed versus others remaining unresolved, emphasizing early detection, design rigor, and robust testing.
This article presents a comprehensive set of software engineering principles—including obsessive code detail, entropy control, test‑driven design, domain‑driven modeling, and disciplined coding habits—to improve code quality, maintainability, and team collaboration across development projects.
Relying solely on defect counts as a KPI fails to reflect a software test engineer’s true performance, so a multi‑dimensional evaluation—including test coverage, defect severity, automation, efficiency, problem‑solving, and teamwork—provides a more objective, comprehensive and fair assessment.
This article explains how systematic test case creation, clear verification steps, and disciplined bug tracking improve testing efficiency, ensure comprehensive coverage of core system logic and data flows, and help teams identify root causes to continuously raise software quality despite limited resources.
