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SparkPerf: A Benchmarking Framework for Evaluating the Performance of Spark Data Analytics Projects

SparkPerf is proposed, a benchmarking tool specifically designed for machine learning applications deployed with Apache Spark, supporting both batch and transactional workloads, and it offers high customizability, allowing users to test their own applications with their own, synthetically augmented, datasets.
IEEE (opens in a new tab)

Devops for digital business: Optimizing the performance and economic efficiency of software products for digital business

An autonomic management framework for economic-driven adaptive resource allocation, during which performance and economics are considered simultaneously, which consists of a hybrid performance-economic model for cloud software systems and a self-adaptive system for resource management at run time is proposed.
ACM (opens in a new tab)

LLMs as Judges: Toward The Automatic Review of GSN-compliant Assurance Cases

A novel approach that leverages the \textit{LLM-as-a-judge} paradigm to automate the review process and proposes new predicate-based rules that formalize well-established assurance case review criteria, allowing us to craft LLM prompts tailored to the review task.
arXiv (opens in a new tab)

A multi-dimensional quality analysis of Android applications

Publisher (opens in a new tab)

Exploring trends and practices of forks in open-source software repositories

This work explores the motivation, the practices and the culture of forking open-source software repositories, and study how forks evolve compared to the parent repository, how they are related to pull requests,How they contribute back to theparent, and how dependencies, in terms of libraries or external modules defined in a build script, are shared or differ within project families.
Publisher (opens in a new tab)
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