This repository contains the source code implementation of Memorec and the datasets used to replicate the experimental results of our paper submitted to the MDE Intelligence 2020:
A Recommender System based on Collaborative-filtering Techniques to Support the Specification of Metamodels
Authors: Juri Di Rocco, Davide Di Ruscio, Claudio Di Sipio, Phuong T. Nguyen, Alfonso Pierantonio
MMRec is a novel approach that makes use of a collaborative filtering strategy to recommend valuable entities related to the model under construction. Our approach can provide suggestions related to both meta-classes and structured features.
This repository is organized as follows:
- The tools directory contains the implementation of the different tools we developed:
- memorec: The Java implementation of memorec
- dataextractor: A set of tools that are used to transform metamodels into memorec-processable
- demo metamodel: the modeling project of the motivation example Web metamodel.
- The dataset directory contains the datasets described in the paper that we use to evaluate memorec:
- METAMODELS_CURATED: 555 metamodels extracted from the curated dataset
- METAMODELS_RAW: 2151 metamodels mined from GitHub
- CLS ATTR RAW RQ1
- CLS ATTR RAW RQ2
- CLS ATTR CURATED RQ1
- CLS ATTR RAW RQ2
- PKG CLS RAW RQ1
- PKG CLS RAW RQ2
- PKG CLS CURATED RQ1
- PKG CLS RAW RQ2