A model of noisy software engineering data (status report)
Roseanne Tesoriero, Marvin V. Zelkowitz · 1998
ABSTRACT other projects in the database. Software development data is highly variable, which of-ten result,s in underlying trends being hidden. In or-der to address this problem, a method of data analy-sis, adapted from the financial community, is presented that permits the shape of the curve of some activity to be reduced to a few line segments, called the character-istic curve. This process is used on sample data from the NASA/GSFC Software Engineering Laboratory and has shown to be a reasonable method to understand ttie underlying process being plotted.