Description
Date depot: 1 janvier 1900
Titre: Automatic Generation of Recovery Plans during software process deviations
Directrice de thèse:
Marie-Pierre GERVAIS (LIP6)
Domaine scientifique: Sciences et technologies de l'information et de la communication
Thématique CNRS : Non defini
Resumé:
Context: This work will be done in the context of the ITEA MeRGE Project, an industrial research project involving 18 European partners from the industry and from academia.
Introduction: Software companies have been struggling for many years to apply and to adopt process models in their development projects. The difficulty comes mainly from two strong assumptions made during software processes adoption. The first one is that the adopted process model captures the right steps, milestones, artifacts and roles necessary to achieve the company’s objectives. The second one is that the process agents are going to strictly follow the adopted process model, without taking any personal initiative to perform the process differently from the specification.
Trying to understand why these assumptions sometimes fail to hold in the software development domain, companies realized that their processes depend on too many human factors and resources, which makes them highly unpredictable [1]. For example, sometimes, due to unexpected project constraints, they need to adapt the process execution in order to change the order of some process steps or even to remove them. Difficulties also arise with regards to the second assumption. In critical processes, having agents deviating from the process model is unthinkable, however, as Lanubile and Vissagio argue in [2], in software processes, this is much more common, 98% of developers deviate during process execution whatever the process used (i.e., scrum, rup, etc). This comes from the fact that developers may be confronted to unanticipated situations which are not represented in the process model; late and unexpected project constraints or simply their willing to accomplish the activity in a way that is closer to their experience and intuitions but far from the process specification
Doctorant.e: Khelladi Djamel Eddine