COST-EFFECTIVE ANALYSIS OF IN-PLACE SOFTWARE PROCESSES

Process studies and improvement efforts typically call for new instrum entation on the process in order to collect the data they have deemed necessary. This can be intrusive and expensive, and resistance to the extra workload often foils the study before it begins. The result is n either interesting new knowledge nor an improved process. In many orga nizations, however, extensive historical process and product data alre ady exist. Can these existing data be used to empirically explore what process factors might be affecting the outcome of the process? If the y can, organizations would have a cost-effective method for quantitati vely, if not causally, understanding their process and its relationshi p to the product. We present a case study that analyzes an in-place in dustrial process and takes advantage of existing data sources. In doin g this, we also illustrate and propose a methodology for such explorat ory empirical studies. The case study makes use of several readily ava ilable repositories of process data in the industrial organization. Ou r results show that readily available data can be used to correlate bo th simple aggregate metrics and complex process metrics with defects i n the product. Through the case study, we give evidence supporting the claim that exploratory empirical studies can provide significant resu lts and benefits while being cost effective in their demands on the or ganization.