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20202026
most citedData Mesh: a Systematic Gray Literature Review

57 citations · 107 across the 12 of their papers we have counts for

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11 papers · 1 filter

cs.SE2026

Sustainability of Open-Source Machine Learning Robustness Assessment Tools: A Repository Mining Study

Joshua Owotogbe, Indika Kumara, Willem-Jan van den Heuvel +1

Robustness evaluation is essential for deploying machine-learning (ML) systems in real-world settings, where models may face adversarial perturbations, distribution shifts, and oth…

cs.SE2026

A Taxonomy of Runtime Faults in Model Context Protocol Servers

Joshua Owotogbe, Indika Kumara, Willem-Jan van den Heuvel +3

MCP (Model Context Protocol) enables LLMs (Large Language Models) to interact with external tools and data sources via a standardized protocol. Its rapid adoption in tool-augmented…

cs.SE2025★ 1 cited

Chaos Engineering in the Wild: Findings from GitHub

Joshua Owotogbe, Indika Kumara, Dario Di Nucci +2

Chaos Engineering (CE) enhances system resilience by deliberately injecting faults to uncover weaknesses before they cause outages. Despite the availability of many CE tools, littl…

cs.SE2024★ 1 cited

Chaos Engineering: A Multi-Vocal Literature Review

Joshua Owotogbe, Indika Kumara, Willem-Jan Van Den Heuvel +1

Organizations, particularly medium and large enterprises, typically rely heavily on complex, distributed systems to deliver critical services and products. However, the growing com…

cs.SE2024★ 1 cited

Architectural Design Decisions for Self-Serve Data Platforms in Data Meshes

Tom van Eijk, Indika Kumara, Dario Di Nucci +2

Data mesh is an emerging decentralized approach to managing and generating value from analytical enterprise data at scale. It shifts the ownership of the data to the business domai…

cs.SE2023★ 57 cited

Data Mesh: a Systematic Gray Literature Review

Abel Goedegebuure, Indika Kumara, Stefan Driessen +4

Data mesh is an emerging domain-driven decentralized data architecture that aims to minimize or avoid operational bottlenecks associated with centralized, monolithic data architect…

cs.SE2021

QSOC: Quantum Service-Oriented Computing

Indika Kumara, Willem-Jan Van Den Heuvel, Damian A. Tamburri

Quantum computing is quickly turning from a promise to a reality, witnessing the launch of several cloud-based, general-purpose offerings, and IDEs. Unfortunately, however, existin…

cs.SE2020

DeepIaC: Deep Learning-Based Linguistic Anti-pattern Detection in IaC

Nemania Borovits, Indika Kumara, Parvathy Krishnan +5

Linguistic anti-patterns are recurring poor practices concerning inconsistencies among the naming, documentation, and implementation of an entity. They impede readability, understa…

cs.SE2020★ 29 cited

Towards Semantic Detection of Smells in Cloud Infrastructure Code

Indika Kumara, Zoe Vasileiou, Georgios Meditskos +5

Automated deployment and management of Cloud applications relies on descriptions of their deployment topologies, often referred to as Infrastructure Code. As the complexity of appl…

cs.SE2020

Quality Assurance of Heterogeneous Applications: The SODALITE Approach

Indika Kumara, Giovanni Quattrocchi, Damian Tamburri +1

A key focus of the SODALITE project is to assure the quality and performance of the deployments of applications over heterogeneous Cloud and HPC environments. It offers a set of to…

cs.SE2020★ 5 cited

FM4SN: A Feature-Oriented Approach to Tenant-Driven Customization of Multi-Tenant Service Networks

Indika Kumara, Jun Han, Alan Colman +2

In a multi-tenant service network, multiple virtual service networks (VSNs), one for each tenant, coexist on the same service network. The tenants themselves need to be able to dyn…