57 citations · 107 across the 12 of their papers we have counts for
16 papers
Actionable Meta-Requirements for AI Robustness Auditing
Joshua Owotogbe, Roya Nasiri, Indika Kumara +2
AI-enabled systems must remain dependable when the conditions under which they operate change (e.g., due to input perturbations, distribution shifts, or changes in external depende…
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…
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…
IaC Generation with LLMs: An Error Taxonomy and A Study on Configuration Knowledge Injection
Roman Nekrasov, Stefano Fossati, Indika Kumara +2
Large Language Models (LLMs) currently exhibit low success rates in generating correct and intent-aligned Infrastructure as Code (IaC). This research investigated methods to improv…
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…
Recursive Self-Similarity in Deep Weight Spaces of Neural Architectures: A Fractal and Coarse Geometry Perspective
Ambarish Moharil, Indika Kumara, Damian Andrew Tamburri +2
This paper conceptualizes the Deep Weight Spaces (DWS) of neural architectures as hierarchical, fractal-like, coarse geometric structures observable at discrete integer scales thro…
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…
A Scale-Invariant Diagnostic Approach Towards Understanding Dynamics of Deep Neural Networks
Ambarish Moharil, Damian Tamburri, Indika Kumara +2
This paper introduces a scale-invariant methodology employing \textit{Fractal Geometry} to analyze and explain the nonlinear dynamics of complex connectionist systems. By leveragin…
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…
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…
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…
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…
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…
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…
SDSN@RT: a middleware environment for single-instance multi-tenant cloud applications
Indika Kumara, Jun Han, Alan Colman +3
With the Single-Instance Multi-Tenancy (SIMT) model for composite Software-as-a-Service (SaaS) applications, a single composite application instance can host multiple tenants, yiel…
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…