Articles

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.

Don Porter
Product Risk Analysis Clarifies Requirements

This presentation re-emphasizes that requirements are important. The difference between functional and nonfunctional requirements will be covered. Then, Product Risk Analysis will be described, along with the elements of the analysis and steps toward performing the analysis.

Jim Kandler
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.

Ross Collard's picture Ross Collard
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.

Johanna Rothman's picture Johanna Rothman

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