The use of statistical process control methods can determine the process capability of sustaining stable levels of variability, so that processes will yield predictable results. This enables to prepare achievable plans, meet cost estimates and scheduling commitments, and deliver required product functionality and quality with acceptable and reasonable reliability. We present initial results of applying statistical analysis methods to the maintenance processes of a software organization rated at the CMM level 3 that is currently planning the assessment to move to the CMM level 4. In particular, we present results from an empirical study conducted on the massive adaptive maintenance process of the organization. We analyzed the correlation between the maintenance size and productivity metrics. The resulting models allow to estimate the costs of a project conducted according to the adopted maintenance processes. Model performances on future observations were assessed by means of a cross validation which guarantees a nearly unbiased estimate of the prediction error. Data about the single phases of the process were also available, thus allowing to analyze the distribution of the effort among the phases and the causes of variations.
Assessing the Maintenance Processes of a Software Organization: an Empirical Analysis of a Large Industrial Project
DE LUCIA, Andrea;
2003-01-01
Abstract
The use of statistical process control methods can determine the process capability of sustaining stable levels of variability, so that processes will yield predictable results. This enables to prepare achievable plans, meet cost estimates and scheduling commitments, and deliver required product functionality and quality with acceptable and reasonable reliability. We present initial results of applying statistical analysis methods to the maintenance processes of a software organization rated at the CMM level 3 that is currently planning the assessment to move to the CMM level 4. In particular, we present results from an empirical study conducted on the massive adaptive maintenance process of the organization. We analyzed the correlation between the maintenance size and productivity metrics. The resulting models allow to estimate the costs of a project conducted according to the adopted maintenance processes. Model performances on future observations were assessed by means of a cross validation which guarantees a nearly unbiased estimate of the prediction error. Data about the single phases of the process were also available, thus allowing to analyze the distribution of the effort among the phases and the causes of variations.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
