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Problem Resolution Optimization No matter how well we plan and execute software development, defects are generated and can escape to the customers. Failure to quickly resolve software problems leads to negative consequences for our customers and increases internal business costs. A quick deterministic
method to prioritize problems and implement their solution helps to reduce cycle time and costs. Achieving this goal requires several steps. The first is to determine a model that links problem resolution performance to institutional variables and problem characteristics. Statistical Design of
Experiments (DOE) is a tool that provides data requirements for estimating the impacts of these variables on problem resolution. Once data has been gathered, the results of statistical analysis can be input into a mathematical optimization model to guide the organization.
This paper describes such an analysis.
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Manage the Risks and the Process Including a testing/QA component early in a software project necessarily prolongs the schedule, right? Not so, according to Ross Collard. In this, the third of a three-part series, Collard explains how to anticipate risks and to aggressively manage the process to prevent disaster.
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What Does Success Look Like? How do you know when software is ready to release? This article discusses one piece of knowing when the software is ready to release—knowing what a successful release would look like.
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A Tester’s Tips for Dealing with Developers Is the tester doing a good job or a bad job when she proves that the program is full of bugs? It’s a bad job from some developers’ points of view. Ridiculous as it seems, there are project managers blaming testers for the late shipment of a product and developers complaining (often jokingly) that “the testers are too tough on the program.” Obviously, there is more to successful testing than bug counts. Here are some tips about how testers can build successful relationships with developers.
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