It is well known that measurement impacts on developer performances. Furthermore, in order to be effective, it must conform to the context characteristics. Both these aspects are critical for globally distributed software processes due to distance and heterogeneity between monitored sites. Here measurement must be non invasive and interpretation of results flexible with respect to each site context. Our conjecture is that quality of primary processes, can be measured, non intrusively, through supporting ones and that interpretation must be based on experience collected during process execution. This work faces these critical issues focusing on maintenance processes. The paper presents a non invasive Statistical Process Control (SPC) based approach, for measuring a primary process (maintenance) through a supporting one (Problem Resolution Process). The approach's efficacy shall be investigated through a simulation carried out on legacy data collected in an industrial environment.
Non Invasive Monitoring of a Distributed Maintenance Process
BALDASSARRE, MARIA TERESA;CAIVANO, DANILO;VISAGGIO, Giuseppe
2006-01-01
Abstract
It is well known that measurement impacts on developer performances. Furthermore, in order to be effective, it must conform to the context characteristics. Both these aspects are critical for globally distributed software processes due to distance and heterogeneity between monitored sites. Here measurement must be non invasive and interpretation of results flexible with respect to each site context. Our conjecture is that quality of primary processes, can be measured, non intrusively, through supporting ones and that interpretation must be based on experience collected during process execution. This work faces these critical issues focusing on maintenance processes. The paper presents a non invasive Statistical Process Control (SPC) based approach, for measuring a primary process (maintenance) through a supporting one (Problem Resolution Process). The approach's efficacy shall be investigated through a simulation carried out on legacy data collected in an industrial environment.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.