English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Tools annual

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Presents the access of premium content as premium feature

Premium Content

Global: Zendy Plus annual

Global: Zendy Free Plan

The customer oriented individualization of products is getting more and more important for the production industry. Especially in car manufacturing industry we can observe a dramatically increasing number of product variants not only related to different car concepts but also concerning different functionality as for example in car entertainment. In order to cope with this increasing complexity in terms of product features and their interrelationships, manufacturers more and more build on a formal approach called feature modeling that allows for a formal analysis of the specified variability artifacts with the help of specialized proving engines as for example SAT-solvers. The development of such proving engines and their test is quite complicated also due to the fact that manufacturers do not disclose the real development data for understandable reasons. Thus, a framework is needed that enables the proving engine developers to test their engines on nearly real data and to show the potential and possibilities of their engines without having the real development data at hand. This paper presents a framework for generating especially large parameterized feature models used for load testing and benchmarking feature model analysis tools, as well as two usage scenarios: the first one runs a typical benchmark with large feature models on two versions of the theorem prover SPASS, the second shows the integration of the generator in a client-server environment where its functionality is hosted on a website, i.e. using the browser as a frontend working on tablets and modern smartphones.

A Framework and Generator for Large Parameterized Feature Models