Available a New Edition of MetricViews “Your Views on Metrics”
The world is living, sadly and globally, something new for us: the COVID-19 (Coronavirus) pandemic has changed the world and life in a few weeks. Now everything takes another perspective; now we appreciate with more intensity the essential of the life.
In spite of this worldwide situation, IFPUG announces that the March edition of MetricViews is now available. In this edition you can read what worldwide metric professionals have to say as they share with us their views on metrics. In the article “20/20 Hindsight: Tips for Software Measurement Success” Carol Dekkers compiles a list of tips that will help to increase success for software measurement programs, Thomas Cagley introduces the emergent technique “Test Case Points” and shares with us several other size techniques, and Carlos Eduardo Vazquez focus the article “Non-functional Complexity Threshold in Function Point Delivery Rates” in improving productivity risk distribution.
Antonio Ferre Albero recalls in the article “The Excellence Determining ILF and EIFs” that to measure with a high level of accuracy is a “must”, and Joe Schofield in the article “Measurement Origins, When and Then, Provoking Us to Think Again” includes, amongst others, a review of some of the origins of measures. A special feature in this edition of MetricViews includes an interview with Talmon Ben-Cnaan, the chairperson of the Non-Functional Sizing Standards IFPUG Committee and part of the team that created the IFPUG SNAP method. In addition, you will find a Message from the President, Christine Green, and news from the different IFPUG committees.
You can read or download this MetricViews edition from here, or the previous editions from the IFPUG MetricViews section.
As always, we welcome your comments and feedback. And an important message that we hope is soon outdated: #Andratuttobene, #QuedateEnCasa, #StayAtHome, …
Take care of yourself and your families, and enjoy of this new edition of MetricViews, the window to the world of metrics.