Mauricio Zambrano (ALMA Observatory), Cristian Recabarren, ALMA Observatory, Victor Gonzalez, ALMA Observatory, Arturo Hoffstadt, ALMA Observatory, Ruben Soto, ALMA Observatory, Tzu-Chiang Shen, ALMA Observatory,
Software quality assurance and planning of an astronomy project is a complex task, specially if it is a globally distributed collaborative project such as ALMA, where the development centers are spread across the globe. When you execute a software project there is much valuable information about this process itself that you might be able to collect. One of the ways you can receive this input is via an issue tracking system that will gather the problem reports relative to software bugs captured during the testing of the software, during the integration of the different components or even worst, problems occurred during production time. Usually, there is little time spent on analyzing them but with some multidimensional processing you can extract valuable information from them and it might help you on the long term planning and resources allocation.
We present a methodology to analyze and get insight from bug reports and a collection of key unbiased indicators. We describe here the extraction, transformation and load process and how the data was processed. We used data warehouse techniques and open source business intelligence tools applied to data gathered throughout the recent years of ALMA software integration process. The main objective is to improve a software process and planning by establishing the basis for a model that predicts the software stabilization and related effort time.
Poster in PDF format
Paper ID: P165