Cas2010 to-track-defects-or-not-to-track-defects-that-is-the-question
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This document discusses different perspectives on tracking defects in Agile development and proposes an alternative approach. It argues that defects should be treated like user stories with estimates and tests rather than using separate tracking tools. Within a sprint, any issues found should be visible on the task board as tests to be fixed. This maintains visibility while avoiding separate backlogs. The document shares a case study where this approach worked well but faced challenges with remote visibility and lack of automation. It concludes defects are best addressed by tracking tests, not bugs, and prioritizing visibility and automation.
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This document discusses challenges for testers in agile development environments. It outlines several strategies testers can use to address these challenges, including:
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Overview
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- Overview of Jupyter Notebooks, an open-source web application for creating and sharing documents with live code, equations, visualizations, and narrative text.
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- Hands-on examples and code snippets in Jupyter Notebooks to help you implement and test anomaly detection models.
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Throughout the session, participants will discover how this synergy empowers testers to automate repetitive tasks, enhance testing accuracy, and expedite the software testing life cycle. Topics covered include the seamless integration process, practical use cases, and the benefits of harnessing AI-driven automation for UiPath testing initiatives. By attending this webinar, testers, and automation professionals can gain valuable insights into harnessing the power of AI to optimize their test automation workflows within the UiPath ecosystem, ultimately driving efficiency and quality in software development processes.
What will you get from this session?
1. Insights into integrating generative AI.
2. Understanding how this integration enhances test automation within the UiPath platform
3. Practical demonstrations
4. Exploration of real-world use cases illustrating the benefits of AI-driven test automation for UiPath
Topics covered:
What is generative AI
Test Automation with generative AI and Open AI.
UiPath integration with generative AI
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
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Perfect for developers, AI enthusiasts, and tech leaders. Learn how to leverage MongoDB Atlas to deliver highly relevant, context-aware search results, transforming your data retrieval process. Stay ahead in tech innovation and maximize the potential of your applications.
#MongoDB #VectorSearch #AI #SemanticSearch #TechInnovation #DataScience #LLM #MachineLearning #SearchTechnology
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Wir erklären Ihnen, wie Sie häufige Konfigurationsprobleme lösen können, die dazu führen können, dass mehr Benutzer gezählt werden als nötig, und wie Sie überflüssige oder ungenutzte Konten identifizieren und entfernen können, um Geld zu sparen. Es gibt auch einige Ansätze, die zu unnötigen Ausgaben führen können, z. B. wenn ein Personendokument anstelle eines Mail-Ins für geteilte Mailboxen verwendet wird. Wir zeigen Ihnen solche Fälle und deren Lösungen. Und natürlich erklären wir Ihnen das neue Lizenzmodell.
Nehmen Sie an diesem Webinar teil, bei dem HCL-Ambassador Marc Thomas und Gastredner Franz Walder Ihnen diese neue Welt näherbringen. Es vermittelt Ihnen die Tools und das Know-how, um den Überblick zu bewahren. Sie werden in der Lage sein, Ihre Kosten durch eine optimierte Domino-Konfiguration zu reduzieren und auch in Zukunft gering zu halten.
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- Wie funktionieren CCB- und CCX-Lizenzen wirklich?
- Verstehen des DLAU-Tools und wie man es am besten nutzt
- Tipps für häufige Problembereiche, wie z. B. Team-Postfächer, Funktions-/Testbenutzer usw.
- Praxisbeispiele und Best Practices zum sofortigen Umsetzen
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Cas2010 to-track-defects-or-not-to-track-defects-that-is-the-question
- 1. Haciendo realidad la agilidad To Track Defects or Not to Track Defects. That is the Question © flioukas Marta Gonzalez Ferrero SQS Group Limited
- 2. What's a defect? • “In an Agile context, I define a bug as behavior in a 'Done' story that violates valid expectations of the Product Owner.” - Elisabeth Hendrikson • “A bug is anything that could bug a stakeholder.” - James Bach • “Counting defects is like a body count in battle. It may be an objective measure, but it's a poor indicator of progress in a battle to win hearts and minds.” - Paul Gerard.
- 3. Traditional defect tracking • Separate tool for defects • Out of sight, out of mind • Separate time bucket for fixes • Two different backlogs, one for features and one for defects • Lots of defect based metrics Lots of defect based metrics • Encourages CYA attitude
- 4. But if we don't track defects, what do we do when we find things that don't work?
- 5. If it looks like a duck... A bug: • Has a priority. • Has an estimate. • Has one or more tests. • Is a token for something the customer wants to change in the software
- 6. If it looks like a duck... A bug: • Has a priority. • Has an estimate. • Has one or more tests. • Is a token for something the customer wants to change in the software Just like a story!
- 7. What about in-sprint bugs? • “A defect is evidence of a missing test” • The test will fail until the defect is fixed. Visible progress! • If the test is automated, you'll check that the bug hasn't been reintroduced every time you run your automated suite. • Track the test, not the bug!
- 8. The key: visibility and automation • Backlog housekeeping is essential. • Within an iteration, work added to the board needs to be very visible, and estimates updated. • If you can't automate your tests, your manual time will increase too fast.
- 9. Case study: my last project Proposed workflow:
- 10. The success • It was easier to prioritize with one backlog. • The estimates for in-sprint stories quickly told when a story had many issues and the sprint was at risk. • Whole team approach when dealing with defects, not only testers problem.
- 11. The challenges • Visibility of issues found during the sprint was difficult for the remote side of the team. • Lack of experience/domain knowledge in the BA team: • Required heavy triage, and it made hard to get defects into future stories. Ended up with too many small low priority items in the backlog. • Duplication: defects in excel, emails, and story tracking tool. • Low automation made the manual cases increase very fast
- 12. Lessons learned • Invest in automation. • Invest in training, and agree on how are you going to make things visible for all members of the team. • Track the tests, not the bugs!
- 13. Any questions? Thank you!