Enhancing Product Comparison through Automated Similarity Matching

Mike Mannon, Hermann Kaindl

Publikation: Wissenschaftliche FachzeitschriftKonferenzartikelBegutachtung

Abstract

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. Reasons for product comparison include (i) to decide whether to build a new product or not (ii) to evaluate how products of the same type differ for strategic positioning or branding reasons (iii) to gauge if a product line needs to be reorganized (iv) to assess if a product falls within the national legislative and regulatory boundaries. We will discuss two different approaches to address this challenge. One is grounded in feature modelling, the other in case-based reasoning. We will also describe a specific product comparison process in which a product configured from a product line feature model is represented as a weighted binary string, the overall similarity between products is compared using a binary string metric, and the significance of individual feature combinations for product similarity can be explored by modifying the weights. We will illustrate our ideas with a mobile phone example, and discuss some of the benefits and limitations of this approach.

OriginalspracheEnglisch
Seiten (von - bis)463-464
Seitenumfang2
FachzeitschriftACM International Conference Proceeding Series
DOIs
PublikationsstatusVeröffentlicht - 13 Juni 2022
Extern publiziertJa
Veranstaltung26th ACM International Conference on Evaluation and Assessment in Software Engineering, EASE 2022 - Gothenburg, Schweden
Dauer: 13 Juni 202215 Juni 2022

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