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N. Eickelmann and A. Anant, “Statistical process control: What you don’t measure can hurt you!” IEEE Software, Vol. 20, No. 2, pp. 49–51, March/April, 2003.

has been cited by the following article:

• TITLE: What can Software Engineers Learn from Manufacturing to Improve Software Process and Product?

  AUTHORS: Norman SCHNEIDEWIND

  KEYWORDS: manufacturing methods, software process, software product, product and process quality, Taguchi methods

  JOURNAL NAME: Intelligent Information Management, Vol.1 No.2, November 30, 2009

  ABSTRACT: The purpose of this paper is to provide the software engineer with tools from the field of manufacturing as an aid to improving software process and product quality. Process involves classical manufacturing methods, such as statistical quality control applied to product testing, which is designed to monitor and correct the process when the process yields product quality that fails to meet specifications. Product quality is measured by metrics, such as failure count occurring on software during testing. When the process and product quality are out of control, we show what remedial action to take to bring both the process and product under control. NASA Space Shuttle failure data are used to illustrate the process methods.