A software product line is an engineering approach to efficient development of software product portfolios. Key to the success of the approach is to identify the common and variable features of the products and the interdependencies between them, which are usually modeled using feature models. Implicitly, such models also include valuable information that can be used by economic models to estimate the payoffs of a product line. Unfortunately, as product lines grow, analyzing large feature models manually becomes impracticable. This paper proposes an algorithm to compute the total number of products that a feature model represents and, for each feature, the number of products that implement it. The inference of both parameters is helpful to describe the standardization/parameterization balance of a product line, detect scope flaws, assess the product line incremental development, and improve the accuracy of economic models. The paper reports experimental evidence that our algorithm has better runtime performance than existing alternative approaches.

In software product line engineering, feature diagrams are a popular means to represent the similarities and differences within a family of related systems. In addition, feature diagrams implicitly model valuable information that can be used in economic models to estimate the cost savings of a product line. In particular, this paper reviews existing proposals on computing the total number of products modeled with a feature diagram and, given a feature, the number of products that implement it. This paper also reviews the economic information that can be estimated when such numbers are known. Thus, this paper contributes by bringing together previously-disparate streams of work: the automated analysis of feature diagrams and economic models for product lines.

This article describes the modeling, control scheme and experimental validation of a new three-degree-of-freedom flexible arm. This arm was built with light links, has most of its mass concentrated at the tip, and uses a special mechanical configuration to approximately decouple radial tip motion from angular tip motions. This special configuration facilitates the dynamic modeling and control of the arm. The compliance matrix can be used to model the oscillations of the structure. Due to this simple dynamics, minimum sensing effort is required (only motor and tip measurements) and the use of complex observers is avoided because the state of the system is obtained directly. A two-nested loop controls the tip position. Experimental results are presented.