Using Binary Strings for Comparing Products from Software-intensive Systems Product Lines
Mike Mannion, Hermann Kaindl · 2021
The volume, variety and velocity of products in software-intensive systems product lines is increasing. One challenge is to understand the range of similarity between products to evaluate its impact on product line management. This paper contributes to product line management by presenting a product similarity evaluation process in which (i) a product configured from a product line feature model is represented as a weighted binary string (ii) the overall similarity between products is compared using the Jaccard Coefficient similarity metric (iii) the significance of individual features and feature combinations to product similarity is explored by modifying the weights. We propose a method for automatically allocating weights to features depending on their position in a product line feature model, although we do not claim that this allocation method nor the use of the Jaccard Coefficient is optimal. We illustrate our ideas with mobile phone worked examples.