Tag: software testing
QA Automation Frameworks for Enterprise Applications
jivox team | | API testing, automated reporting, ci/cd testing, continuous integration, cross-browser testing, devops, end-to-end testing, enterprise QA, Enterprise software, flaky tests, Page Object Model, parallel testing, QA automation, Quality Engineering, regression testing, Screenplay Pattern, software testing, test automation, test data management, UI automationModern enterprise applications demand testing strategies that can keep pace with continuous delivery, distributed architectures, and increasingly complex deployment pipelines. Traditional manual testing approaches often become a bottleneck as engineering teams scale ...
AI Is Breaking Developers’ Traditional Game Testing Playbook
Anoop Tripathi | | AI game testing, AI-driven games, automated playtesting, crash reporting, dynamic NPCs, game automation, game development, game QA, gaming AI, GTA Online, LiveOps, NPC testing, player behavior, Quality Assurance, regression testing, Roblox, software testing, Square Enix, synthetic players, test automationGame testing has always been an unpredictability problem for developers. Players move in the wrong direction, trigger events out of order, or combine mechanics no designer anticipated. Even so, developers could usually ...
Dependency Mocking Approach That Gets More Accurate as Your Services Deploy More Often
Sancharini Panda | | API testing, CI/CD, Contract Testing, Dependency Mocking, devops, ebpf, integration testing, Keploy, microservices, Mock Drift, service virtualization, software testing, test automation, Testcontainers, Traffic-Based MockingTraffic-based dependency mocking turns frequent upstream deployments into opportunities to refresh mocks from real behavior and reduce integration test drift ...
Stop Chasing 100% Test Coverage: Why DevOps Teams Need to Test Smarter, Not More
Adonis Celestine | | AI testing, application security, CI/CD, continuous testing, devops, PRisMA, Product Risk Management, QA, QFD, Quality Assurance, Quality Functional Deployment, Rapid Risk Assessment, regression testing, release management, risk-based testing, RRA, software development, software quality, software testing, test automationEvery software team eventually runs into the same question: How much testing is enough? For years, the default answer has been "more." More automated tests. More regression suites. More environments. More devices ...
Test Creation Was Never the Bottleneck
Something specific happened to software delivery in the past two years. The 2026 survey data is unusually clear about what it was. Sonar's 2026 State of Code Developer Survey found that AI-generated ...
From the Horse’s Mouth: Anthropic Says AI Has Changed the SDLC
Alan Shimel | | agentic development, AI code review, AI coding agents, AI Governance, AI-assisted development, AI-native SDLC, Anthropic, autonomous agents, CI/CD, Claude Code, Code Generation, developer productivity, devops, internal developer platforms, platform engineering, software delivery, software development lifecycle, software engineering, software security, software testingAnthropic’s AI-native SDLC playbook argues that faster coding is shifting the bottleneck to planning, testing, governance, deployment and operations ...
Production Validation: The Missing Layer in Enterprise ReleasesÂ
Kawaljeet Singh Chadha | | auditability, business validation, business-critical systems, change management, data quality, deployment controls, DevOps governance, enterprise devops, Enterprise software, exception-handling, operational approval, production assurance, production readiness, production validation, reconciliation, regulated environments, release governance, release management, release readiness, software testingProduction validation adds a critical business-control layer between testing and deployment, combining data checks, exception review, approvals, reconciliation and operational readiness before a release reaches production ...
Waterfall 2.0: Controlling LLM-Driven Software Development with Stage-Gated Discipline
Georgy Starikov | | ADRs, Agile vs Waterfall, AI coding, AI development lifecycle, AI Software Engineering, AI-assisted engineering, architecture decision records, combi-shaper, engineering workflows, generative AI development, knowledge corpus, LLM engineering, LLM software development, MCP, Model Context Protocol, software architecture, software testing, system design, Waterfall 2.0Waterfall 2.0 reimagines classic stage-gated software development for the LLM era, combining fast AI generation with structured validation, cheap backtracking and a shared knowledge corpus ...
Why API Test Generation Is a Judgment Problem, Not a Code Generation Problem
Abhishek Saikia | | adaptive test coverage, AI API testing, AI quality engineering, AI test generation, API test generation, API testing, Automated testing, cross-field testing, DevOps Testing, fine-tuning, LLM testing, QA automation, RAG, software testing, test assertions, test coverageWhen we started using large language models for API test generation at KushoAI, the results were impressive on the surface. Tests appeared in seconds. Coverage breadth went up. The team was excited ...
Why Self-Healing Tests Need a Deployment Gate
Suneet Malhotra | | artificial intelligence, CI/CD, devops, Self-Healing Automation, software testing, test automationWhen an end-to-end test fails after a front-end change, the repair often looks routine. A class name changed. A button moved. A selector that used to be unique now matches two elements ...
How Test Management Tools Give Engineering Teams the Visibility They Need to Ship With Confidence
Sancharini Panda | | API testing, Automated testing, change-aware testing, CI/CD, code coverage, coverage visibility, deployment confidence, deployment risk, DevOps Testing, engineering teams, flaky tests, Keploy, Quality Assurance, regression testing, software delivery, software testing, test case currency, test case management, test coverage, test coverage gaps, test management tools, test traceabilityTest management tools do more than track results. Learn how they give engineering teams the coverage visibility needed to ship with confidence ...
Sandbox Testing for API-Heavy Systems: What Changes When You Don’t Own the Dependency
Sandbox testing works well when your team controls both sides of the integration. You define the service, you define the mock, you know exactly what the sandbox should return. That setup holds ...
