Software metrics to predict the health of a project ?

Vincent Blondeau (1, 2) , Nicolas Anquetil (1) , Stéphane Ducasse (1) , Sylvain Cresson (2) , Pascal Croisy (2)

1 RMOD - Analyses and Languages Constructs for Object-Oriented Application Evolution
2 Atos Worldline

More and more companies would like to mine software data with the goal of assessing the health of their software projects. The hope is that some software metrics could be tracked to predict failure risks or confirm good health. If a factor of success was found, projects failures could be anticipated and early actions could be taken by the organisation to help or to monitor closely the project, allowing one to act in a preventive mode rather than a curative one. We were called by a major IT company to fulfil this goal. We conducted a study to check whether software metrics can be related to project failure. The study was both theoretic with a review of literature on the subject, and practical with mining past projects data and interviews with project managers. We found that metrics used in practice are not reliable to assess project outcome.

Mots clés: Project health; Closed-source; Data-mining; Interviews

Domaines: Langage de programmation [cs.PL]

Vincent Blondeau, Nicolas Anquetil, Stéphane Ducasse, Sylvain Cresson, Pascal Croisy. Software metrics to predict the health of a project ?: An assessment in a major IT company. IWST '15 International Workshop On Smalltalk Technologies, Jul 2015, Brescia, Italy. pp.8, ⟨10.1145/2811237.2811294⟩. ⟨hal-01185079⟩