Recommendation Heuristics for Improving Product Line Configuration Processes

Raúl Mazo (1) , Cosmin Dumitrescu (1) , Camille Salinesi (1) , Daniel Diaz (1)

1 CRI - Centre de Recherche en Informatique de Paris 1

In mass customization industries, such as car manufacturing, configurators play an important role both to interact with customers and in engineering processes. This is particularly true when engineers rely on reuse of assets and product line engineering techniques. Theoretically, product line configuration should be guided by the product line model. However, in the industrial context, the configuration of products from product line models is complex and error prone due to the large number of variables in the models. The configuration activity quickly becomes cumbersome due to the number of decisions needed to get a proper configuration, to the fact that they should be taken in pre-defined order, or the poor response time of configurators when decisions are not appropriate. This chapter presents a collection of recommendation heuristics to improve the interactivity of product line configuration so as to make it scalable to common engineering situations.We describe the principles, benefits and the implementation of each heuristic using constraint programming. The application and usability of the heuristics is demonstrated using a case study from the car industry.

Domains: Logic in Computer Science [cs.LO]; Software Engineering [cs.SE]

Raúl Mazo, Cosmin Dumitrescu, Camille Salinesi, Daniel Diaz. Recommendation Heuristics for Improving Product Line Configuration Processes. Robillard M, Maalej W., Walker R. and Zimmermann T. Recommendation Systems in Software Engineering, Springer, pp.100, 2014, 978-3-642-45135-5. ⟨hal-00914021⟩