[HTML][HTML] AI-powered model repair: an experience report—lessons learned, challenges, and opportunities
Artificial intelligence has already proven to be a powerful tool to automate and improve how
we deal with software development processes. The application of artificial intelligence to …
we deal with software development processes. The application of artificial intelligence to …
Synthetic data generation for statistical testing
G Soltana, M Sabetzadeh… - 2017 32nd IEEE/ACM …, 2017 - ieeexplore.ieee.org
Usage-based statistical testing employs knowledge about the actual or anticipated usage
profile of the system under test for estimating system reliability. For many systems, usage …
profile of the system under test for estimating system reliability. For many systems, usage …
Hawk: Towards a scalable model indexing architecture
Version control of large-scale models is still an open problem in Model Driven Engineering
settings. In this paper we review a number of existing approaches for model version control …
settings. In this paper we review a number of existing approaches for model version control …
Resolving model inconsistencies using automated regression planning
J Pinna Puissant, R Van Der Straeten… - Software & Systems …, 2015 - Springer
One of the main challenges in model-driven software engineering is to automate the
resolution of design model inconsistencies. We propose to use the artificial intelligence …
resolution of design model inconsistencies. We propose to use the artificial intelligence …
Towards automated inconsistency handling in design models
MA Almeida da Silva, A Mougenot, X Blanc… - … , Tunisia, June 7-9, 2010 …, 2010 - Springer
The increasing adoption of MDE (Model Driven Engineering) favored the use of large
models of different types. It turns out that when the modeled system gets larger, simply …
models of different types. It turns out that when the modeled system gets larger, simply …
Graph2seq: Fusion embedding learning for knowledge graph completion
W Li, X Zhang, Y Wang, Z Yan, R Peng - IEEE Access, 2019 - ieeexplore.ieee.org
Knowledge Graph (KG) usually contains billions of facts about the real world, where a fact is
represented as a triplet in the form of (head entity, relation, tail entity). KG is a complex …
represented as a triplet in the form of (head entity, relation, tail entity). KG is a complex …
Towards the automated generation of consistent, diverse, scalable and realistic graph models
Automated model generation can be highly beneficial for various application scenarios
including software tool certification, validation of cyber-physical systems or benchmarking …
including software tool certification, validation of cyber-physical systems or benchmarking …
Mofuzz: A fuzzer suite for testing model-driven software engineering tools
Fuzzing or fuzz testing is an established technique that aims to discover unexpected
program behavior (eg, bugs, security vulnerabilities, or crashes) by feeding automatically …
program behavior (eg, bugs, security vulnerabilities, or crashes) by feeding automatically …
Automated reasoning for attributed graph properties
Graphs are ubiquitous in computer science. Moreover, in various application fields, graphs
are equipped with attributes to express additional information such as names of entities or …
are equipped with attributes to express additional information such as names of entities or …
[PDF][PDF] Evaluation of contemporary graph databases for efficient persistence of large-scale models.
K Barmpis, DS Kolovos - J. Object Technol., 2014 - jot.fm
Abstract Scalability in Model-Driven Engineering (MDE) is often a bottleneck for industrial
applications. Industrial scale models need to be persisted in a way that allows for their …
applications. Industrial scale models need to be persisted in a way that allows for their …