Popular Economics: What the Rolling Stones, Downton Abbey, by John Tamny

By John Tamny

Forbes editor John Tamny makes use of interesting tales from activities, videos, pop culture, and well-known companies to illustrate the fundamental ideas of economics.

The Rolling Stones, the Dallas Cowboys, and Paris Hilton turn into examples of fine and undesirable tax policy.

The Godfather, long gone With the Wind, and The Sopranos exhibit the drawback of antitrust rules, whereas the Michigan Wolverines' 2007 loss to Appalachian country explains why rules frequently fail to accomplish their meant purpose.

NBA megastar LeBron James' exploits at the basketball courtroom illustrate unfastened alternate and comparative virtue, whereas the cooking of poultry wings makes the case for a good dollar.

Popular Economics is an everyman's advisor to how funds fairly works--a lesson politicians attempt (and fail) to understand each day.

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Due to time constraints not all errors will be fixed before release. These errors may lead later to interruptions in production if they are not corrected. Other errors may lead to false results which must be manually corrected. M. Sneed become annoying to the users. The users may accept living with these inconveniences for a while but eventually they will insist that they be fixed. The cost of fixing them is not trivial. Together with the code smells and the missing features this adds up to a significant debt.

Defect Analysis: Basic Techniques for Management and Learning. In: Advances in Computers, ch. 7, vol. 65, pp. 259–295 (2005) 2. : Defect Causal Analysis Drives Down Error Rates. IEEE Software 10(4), 98–99 (1993) 3. : Experiences with Defect Prevention. IBM Systems Journal 29(1), 4–32 (1990) 4. : Defect Causal Analysis: A Report from the Field. In: Proceedings of International Conference of Software Quality, American Society for Quality Control (1992) 5. : Using Defect Analysis Feedback for Improving Quality and Productivity in Iterative Software Development.

Definition, assessment, and prediction of quality attributes should rely on the same model. However, in practice different (often implicit and incomplete) models are used for these tasks. Therefore a common infrastructure that supports definition, assessment and prediction of software quality using a common representation of the underlying quality-relevant data and metrics is highly desireable. As mentioned previously, our dashboard solution focuses on continuous monitoring of the software life cycle particularly addressing the need for a smooth integration of various quality dimensions.

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