The Software Heritage Open Science Ecosystem

Cosmo, Roberto Di; Zacchiroli, Stefano

doi:10.1007/978-3-031-36060-2_2

Cited by 5 publications

(5 citation statements)

References 34 publications

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“…Transitions between HRAs were depicted using the circular layout plugin in Gephi (v. 0.10.1 202301172018). All programs used in this study are available at https://github.com/AntonyJose-Lab/Jose_2023 , copy archived at Jose, 2023 .…”

Section: Methodsmentioning

confidence: 99%

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Heritable epigenetic changes are constrained by the dynamics of regulatory architectures

Jose

2024

eLife

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Interacting molecules create regulatory architectures that can persist despite turnover of molecules. Although epigenetic changes occur within the context of such architectures, there is limited understanding of how they can influence the heritability of changes. Here I develop criteria for the heritability of regulatory architectures and use quantitative simulations of interacting regulators parsed as entities, their sensors and the sensed properties to analyze how architectures influence heritable epigenetic changes. Information contained in regulatory architectures grows rapidly with the number of interacting molecules and its transmission requires positive feedback loops. While these architectures can recover after many epigenetic perturbations, some resulting changes can become permanently heritable. Such stable changes can (1) alter steady-state levels while preserving the architecture, (2) induce different architectures that persist for many generations, or (3) collapse the entire architecture. Architectures that are otherwise unstable can become heritable through periodic interactions with external regulators, which suggests that the evolution of mortal somatic lineages with cells that reproducibly interact with the immortal germ lineage could make a wider variety of regulatory architectures heritable. Differential inhibition of the positive feedback loops that transmit regulatory architectures across generations can explain the gene-specific differences in heritable RNA silencing observed in the nematode C. elegans, which range from permanent silencing, to recovery from silencing within a few generations and subsequent resistance to silencing. More broadly, these results provide a foundation for analyzing the inheritance of epigenetic changes within the context of the regulatory architectures implemented using diverse molecules in different living systems.

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Section: Methodsmentioning

confidence: 99%

“…The current manuscript is a computational study, so no data have been generated for this manuscript. Modeling code is available at https://github.com/AntonyJose-Lab/Jose_2023 , copy archived at Jose, 2023 .…”

Section: Data Availabilitymentioning

confidence: 99%

Heritable epigenetic changes are constrained by the dynamics of regulatory architectures

Jose

2024

eLife

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“…At present, the public benchmark datasets are : SH L , SH S , M V L . The SH L dataset contains 610 Java files, which are randomly selected from 5147 Java projects retrieved from GitHub through software heritage [25]. To speed up the evaluation of the model, SH S extracted smaller 200 Java projects from SH L .…”

Section: Dataset Descriptionmentioning

confidence: 99%

Similarity Pattern Enhancement for API Recommended Methods via Graph Representation Learning

Fang,

Wang,

Gao

et al. 2024

Preprint

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Developers often utilize application programming interfaces (API) to simplify their development tasks. API recommendation methods can automatically recommend the APIs that developers need to improve development quality and efficiency. Recent research combines collaborative filtering with graph neural networks for API recommendation. However, these approaches often face the problem of sub-optimal graph representation due to data sparsity. To address these issues, we propose an API recommendation method that enhances the raw data by fusing usage patterns in similar projects. Typically, similar projects share similar functional and structural features, including code modules with similar usage patterns, which include rich information such as invocation and structural details. Enhancing the raw data with this information can effectively alleviate the sparsity problem of the interaction matrix induced by the construction graph of the raw data. Specifically, our approach consists of matching similar items for each entry in the original dataset to form new classes. These new classes are then merged into code modules with similar usage patterns to augment the original dataset. Subsequently, the graph represents the learning model capturing the higher-order collaborative signals of the API calls in the augmented dataset and integrating the structural information of the items into the graph. To evaluate the effectiveness of our approach, we conducted experiments using data collected from large open source repositories. The experimental results show that the method is effective.

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“…Recent initiatives on reproducible research focus on transparent research artifacts with Guix, a system that enables the building of computation environments (Vallet, Michonneau, and Tournier 2022). Software heritage projects aim at preserving source code and binaries from research software (Cosmo and Zacchiroli 2017;Audemard, Paulevé, and Simon 2020).…”

Section: Introductionmentioning

confidence: 99%

Parallel Empirical Evaluations: Resilience despite Concurrency

Fichte,

Geibinger,

Hecher

et al. 2024

AAAI

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Computational evaluations are crucial in modern problem-solving when we surpass theoretical algorithms or bounds. These experiments frequently take much work, and the sheer amount of needed resources makes it impossible to execute them on a single personal computer or laptop. Cluster schedulers allow for automatizing these tasks and scale to many computers. But, when we evaluate implementations of combinatorial algorithms, we depend on stable runtime results. Common approaches either limit parallelism or suffer from unstable runtime measurements due to interference among jobs on modern hardware. The former is inefficient and not sustainable. The latter results in unreplicable experiments. In this work, we address this issue and offer an acceptable balance between efficiency, software, hardware complexity, reliability, and replicability. We investigate effects towards replicability stability and illustrate how to efficiently use widely employed cluster resources for parallel evaluations. Furthermore, we present solutions which mitigate issues that emerge from the concurrent execution of benchmark jobs. Our experimental evaluation shows that – despite parallel execution – our approach reduces the runtime instability on the majority of instances to one second.

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The Software Heritage Open Science Ecosystem

Cited by 5 publications

References 34 publications

Heritable epigenetic changes are constrained by the dynamics of regulatory architectures

Heritable epigenetic changes are constrained by the dynamics of regulatory architectures

Similarity Pattern Enhancement for API Recommended Methods via Graph Representation Learning

Parallel Empirical Evaluations: Resilience despite Concurrency

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