A Model of Noisy Software Engineering Data (Status Report)

other projects in the database. Software development data is highly variable, which often result,s in underlying trends being hidden. In order to address this problem, a method of data analysis, 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 characteristic 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. Lines of code produced, staff hours, error reports filed, change reports filed, modules created, and modules changed are all reported weekly by project personnel or are extracted automatically from the source code libraries. Once in the data base, we can plot these as raw data weekly scatter plots or as various growth functions to show how the collected statistics change over time. KEYWORDS Curve fit,ting, Esponential moving average, Financial da...

• Type: Conference
• Year: 1998
• Where: ICSE
• Authors: Roseanne Tesoriero, Marvin V. Zelkowitz
• Keywords: Data Weekly Scatter, ICSE 1998, Software Development Data, Software Engineering, Ttie Underlying Process