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AI-Driven Manual Regression: Test Only What Truly Matters With Wilhelm Haaker and Daniel Garay
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Manage episode 522065459 series 64613
Conteúdo fornecido por Joe Colantonio. Todo o conteúdo do podcast, incluindo episódios, gráficos e descrições de podcast, é carregado e fornecido diretamente por Joe Colantonio ou por seu parceiro de plataforma de podcast. Se você acredita que alguém está usando seu trabalho protegido por direitos autorais sem sua permissão, siga o processo descrito aqui https://pt.player.fm/legal.
Manual regression testing isn't going away—yet most teams still struggle with deciding what actually needs to be retested in fast release cycles. See how AI can help your manual testing now: https://testguild.me/parasoftai In this episode, we explore how Parasoft's Test Impact Analysis helps QA teams run fewer tests while improving confidence, coverage, and release velocity. Wilhelm Haaker (Director of Solution Engineering) and Daniel Garay (Director of QA) join Joe to unpack how code-level insights and real coverage data eliminate guesswork during regression cycles. They walk through how Parasoft CTP identifies exactly which manual or automated tests are impacted by code changes—and how teams use this to reduce risk, shrink regression time, and avoid redundant testing. What You'll Learn: Why manual regression remains a huge bottleneck in modern DevOps How Test Impact Analysis reveals the exact tests affected by code changes How code coverage + impact analysis reduce risk without expanding the test suite Ways teams use saved time for deeper exploratory testing How QA, Dev, and Automation teams can align with real data instead of assumptions Whether you're a tester, automation engineer, QA lead, or DevOps architect, this episode gives you a clear path to faster, safer releases using data-driven regression strategies.
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575 episódios
MP3•Home de episódios
Manage episode 522065459 series 64613
Conteúdo fornecido por Joe Colantonio. Todo o conteúdo do podcast, incluindo episódios, gráficos e descrições de podcast, é carregado e fornecido diretamente por Joe Colantonio ou por seu parceiro de plataforma de podcast. Se você acredita que alguém está usando seu trabalho protegido por direitos autorais sem sua permissão, siga o processo descrito aqui https://pt.player.fm/legal.
Manual regression testing isn't going away—yet most teams still struggle with deciding what actually needs to be retested in fast release cycles. See how AI can help your manual testing now: https://testguild.me/parasoftai In this episode, we explore how Parasoft's Test Impact Analysis helps QA teams run fewer tests while improving confidence, coverage, and release velocity. Wilhelm Haaker (Director of Solution Engineering) and Daniel Garay (Director of QA) join Joe to unpack how code-level insights and real coverage data eliminate guesswork during regression cycles. They walk through how Parasoft CTP identifies exactly which manual or automated tests are impacted by code changes—and how teams use this to reduce risk, shrink regression time, and avoid redundant testing. What You'll Learn: Why manual regression remains a huge bottleneck in modern DevOps How Test Impact Analysis reveals the exact tests affected by code changes How code coverage + impact analysis reduce risk without expanding the test suite Ways teams use saved time for deeper exploratory testing How QA, Dev, and Automation teams can align with real data instead of assumptions Whether you're a tester, automation engineer, QA lead, or DevOps architect, this episode gives you a clear path to faster, safer releases using data-driven regression strategies.
…
continue reading
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