Pattern Language as Support to Software Measurement Planning for Statistical Process Control

Abstract

The growing interest of organizations in improving their software processes has led them to aim at achieving high maturity, where statistical process control (SPC) is required. One of the challenges involved in performing SPC is selecting measures suitable for it. Measures used in SPC can be found in the literature and can be reused by organizations, but the information is dispersed, not favoring reuse. From measures suggested in the literature or used in practical experiences, it is possible to identify patterns that can be used to support organizations in measurement planning. Patterns can be organized as pattern languages, which favor reuse and contribute towards increasing productivity. In this work, from the results of a systematic mapping and a survey, we identified measurement planning patterns in the Goal-Question-Metric format and organized them in a Measurement Planning Pattern Language (MePPLa). MePPLa was created by following a Systematic Approach for creating Measurement Planning Pattern Languages (SAMPPLa), also defined in this work. This paper presents SAMPPLa, MePPLa and the main results of a study carried out to evaluate MePPLa. The results showed that using MePPLa is viable and useful to aid in software measurement planning. Mainly, MePPLa contributes to increasing productivity when creating a measurement plan and the quality of the resulting measurement plan.

Keywords

• Software Measurement
• Statistical Process Control