Conjunctive Query Based Constraint Solving For Feature Model Configuration
This work addresses feature model configuration for software engineers by providing a more accessible method, though it is incremental as it adapts existing database technology to a known problem.
The paper tackled the problem of feature model configuration by applying conjunctive queries from relational databases to solve constraint satisfaction problems, enabling the use of widespread database technology and new algorithmic approaches for inconsistency resolution.
Feature model configuration can be supported on the basis of various types of reasoning approaches. Examples thereof are SAT solving, constraint solving, and answer set programming (ASP). Using these approaches requires technical expertise of how to define and solve the underlying configuration problem. In this paper, we show how to apply conjunctive queries typically supported by today's relational database systems to solve constraint satisfaction problems (CSP) and -- more specifically -- feature model configuration tasks. This approach allows the application of a wide-spread database technology to solve configuration tasks and also allows for new algorithmic approaches when it comes to the identification and resolution of inconsistencies.