Towards Validating Prediction Systems for Process Understandability: Measuring Process Understandability

Motivated by software metrics, several process metrics for measuring internal (structural) process attributes have been proposed. Integrated in validated prediction systems, these metrics can be used to predict values of external process attributes like, for example, process understandability. There...

Full description

Saved in:
Bibliographic Details
Published in:Symbolic and Numeric Algorithms for Scientific Computing, Proceedings pp. 564 - 571
Main Authors: Melcher, J., Seese, D.
Format: Conference Proceeding
Language:English
Published: IEEE 01.09.2008
Subjects:
Concrete
Costs
Design for experiments
Humans
measurement approach
metric
Process design
process understandability
Scientific computing
Software algorithms
Software measurement
Software metrics
Time measurement
ISBN:0769535232, 9780769535234
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Motivated by software metrics, several process metrics for measuring internal (structural) process attributes have been proposed. Integrated in validated prediction systems, these metrics can be used to predict values of external process attributes like, for example, process understandability. There are only a few papers dealing with finding a process understandability metric and validating prediction systems for process understandability. Looking at these publications, we identified possible problems with metric reliability and validity. In this paper, we define new metrics for process understandability inspired by existing work. Furthermore, we present some hypotheses about effects of measuring process understandability. Conducting an experiment, we got some encouraging findings supporting these hypotheses: different aspects of process understandability can be complicated in varying degrees for a process and asking only some few questions about a process can cause values for process understandability differing very much from the real value. These findings should be considered in future work about measuring process understandability.
ISBN:0769535232
9780769535234
DOI:10.1109/SYNASC.2008.24