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Software Test Estimation
 
  SOFTWARE TEST ESTIMATION
A Practical, Hands-on Course for Managers
 
       
  2-Day Course  
  Contact us at onsitetraining@sqe.com for On-site pricing  
 
 
  This Course is Available for On-site Training  
 

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Based on the books Managing the Testing Process and Critical Testing Processes, as well as two decades of software, hardware, and systems experience, this seminar will guide course attendees through a risk-based approach to creating realistic, actionable estimates of the testing tasks required for a project.

Using techniques and demonstrations ranging from the informal to ISO 9126 to Failure Mode and Effect Analysis, students will learn how to determine what you should test (and how extensively) by developing a prioritized list of risks to system quality. Attendees will then use a hypothetical case study to translate that list of quality risks into an estimated schedule and budget via techniques like the Delphic Oracle, Three-Point, and Wideband team task sizing methods, plus the use of historical data and rules of thumb for additional accuracy.

Finally, attendees will examine options for testers when they're asked to shrink their testing efforts into pre-existing schedule or budget targets, including risk-driven test effort descoping. Throughout, attendees will have a chance to solidify their understanding of the techniques through in-class discussion, Q&A, and three exercises.

Prerequisites
• Be familiar with the general concept of a software development lifecycle (e.g., waterfall, spiral, evolutionary, etc.)
• Have experience with general project management tasks like estimating (work-breakdown-structures, schedules, and budget).

Learning Objectives
• Analyze risks to system quality to determine what should be tested-and to what degree-in a test subproject.
• Create an actionable, realistic estimate of the tasks, dependencies, resources, and time required for the testing subproject.
• Adjust the estimated schedule and budget to fit project constraints without undermining accuracy or unduly increasing risk.

 
 
 
 

 
   

 

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