Tootfinder

Soft vs. Hard Dependency. A Better Way to Think About Dependencies for More Reliable Systems
https://www.thecoder.cafe/p/soft-hard-dependency

jung: JUNG and javax class dependencies (2012)
A network of software class dependency within the JUNG 2.0.1 and javax 1.6.0.7 library namespaces edu.uci.ics.jung and java/javax. Nodes represent classes and a directed edge indicates a dependency of one class on another.
This network has 6120 nodes and 138706 edges.
Tags: Technological, Software, Unweighted

PyPitfall: Dependency Chaos and Software Supply Chain Vulnerabilities in Python
Jacob Mahon, Chenxi Hou, Zhihao Yao
https://arxiv.org/abs/2507.18075 https://

PyPitfall: Dependency Chaos and Software Supply Chain Vulnerabilities in Python
Python software development heavily relies on third-party packages. Direct and transitive dependencies create a labyrinth of software supply chains. While it is convenient to reuse code, vulnerabilities within these dependency chains can propagate through dependencies, potentially affecting down-stream packages and applications. PyPI, the official Python package repository, hosts many packages and lacks a comprehensive analysis of the prevalence of vulnerable dependencies. This paper introduces…

Not All Features Deserve Attention: Graph-Guided Dependency Learning for Tabular Data Generation with Language Models
Zheyu Zhang, Shuo Yang, Bardh Prenkaj, Gjergji Kasneci
https://arxiv.org/abs/2507.18504

Not All Features Deserve Attention: Graph-Guided Dependency Learning for Tabular Data Generation with Language Models
Large Language Models (LLMs) have shown strong potential for tabular data generation by modeling textualized feature-value pairs. However, tabular data inherently exhibits sparse feature-level dependencies, where many feature interactions are structurally insignificant. This creates a fundamental mismatch as LLMs' self-attention mechanism inevitably distributes focus across all pairs, diluting attention on critical relationships, particularly in datasets with complex dependencies or semanticall…

from my link log —
Basic dependency injection with objects in OCaml.
https://gr-im.github.io/a/dependency-injection.html
saved 2025-08-18

I just released nugraph, a #dotnet tool for creating visual dependency graph of NuGet packages.
Installation:
dotnet tool install --global nugraph
Usage for a NuGet package:
nugraph Azure.Core
or for a .NET project:
nugraph ~/Projects/Kerberos.NET/Bruce/Bruce.csproj
Many options are available, everything is documented on https://github.com/0xced/nugraph
Enjoy!
Here's the kind of graph it generates (Azure.Core example).

https://mermaid.live/view#pako:eNqcVU2P2jAQ_StWViu1EjgBVqjNjS6raqXl0t6qXIwzSVwSO3UmAor4780HKF4wWdJcYux5z2_ezISDw1UIju-Mx-NAosAUfLKEHGQIku9JrFmeEBWRxd9SA31WGsiEPs3plHySgF-o9zmQDTaQj4_kO0jQDCEk6z1JEPPCd91YYFKuKVeZ6-04hK4sG9oa0_K__ajXPGVFsYSIaKWQFKjVBsZbEWLiP-U74zyEiJUpkkikqc_-lCxjWkgYtRD_wfO-evPJiKtUaf9h1jz1BV0Oh0O3Ph5Jpb_0vNkLWQmuVaEipN94ShfFXvJXiaAjxqEwCTrIz32BkNHnVIDEVWVm2hu3gkzpPV0yZIHsrnvZIchCKFnQNxXHQsZ0sa7yYRzrTZtCA9IV7FX-hgbyDh7Ia5UfUNpU9NPYEjwVzeyeuriW7VNN6xPBN-ZJTT-dnptpu93Sqn8AqdKxmzO-YTEUbhfvtu3Zok7gq-Ztt88yeqt-qaw_-C6xvRRuNVPUeye__0oj_jqhAU1yO9EhJAMNGEDdGDO9YcwQiQZPr2HWQbzHJCvw_42x0TVmzD42wyrFwJ4NsAz2RaaWiLtSusbVE3pRSAu5EXQh0vjC3BBpRgwRaeDceWXSxCbSJDeCAumMnAx0xkRY_Z8e2l1MIIN26bevs-Lmx7HC5Ez-UipzfNQlHP8BAAD__wMAEYyvHw

#Python world be like:
"Oh, hi, we wrote a new library implementing this spec."
"Hey, it looks like it doesn't conform to the spec, it doesn't pass the examples from it."
"Oh, you're right, we'll fix it ASAP."
…and that was over 3 years ago.
And yet projects keep adding a dependency on this library which has a single "pre-alpha" release 3.5 years ago and whose very first bug report points out it's incorrect.

Urban observations about #Winnipeg
-Why are the downtown streets so large? For a city built before car dependency, I find everything very large
-So many one-ways
-While it looks quite car centric, I see many people at bus stop. (I hope it means transit is decent and not that there’s isn’t enough bus)
-Sadly downtown has seen better days. Beautiful buildings but ma…

LLM-Driven Collaborative Model for Untangling Commits via Explicit and Implicit Dependency Reasoning
Bo Hou, Xin Tan, Kai Zheng, Fang Liu, Yinghao Zhu, Li Zhang
https://arxiv.org/abs/2507.16395

LLM-Driven Collaborative Model for Untangling Commits via Explicit and Implicit Dependency Reasoning
Atomic commits, each of which addresses a single development concern, are a best practice in software development. However, developers frequently produce tangled commits that mix unrelated changes due to practical constraints or unclear boundaries, negatively impacting code review and maintenance. Although prior commit untangling approaches: rule-based, feature-based, or graph-based, have made progress, they often rely on shallow signals and fail to distinguish between explicit dependencies (e.…

Met$^2$Net: A Decoupled Two-Stage Spatio-Temporal Forecasting Model for Complex Meteorological Systems
Shaohan Li, Hao Yang, Min Chen, Xiaolin Qin
https://arxiv.org/abs/2507.17189

Met$^2$Net: A Decoupled Two-Stage Spatio-Temporal Forecasting Model for Complex Meteorological Systems
The increasing frequency of extreme weather events due to global climate change urges accurate weather prediction. Recently, great advances have been made by the \textbf{end-to-end methods}, thanks to deep learning techniques, but they face limitations of \textit{representation inconsistency} in multivariable integration and struggle to effectively capture the dependency between variables, which is required in complex weather systems. Treating different variables as distinct modalities and appl…

software_dependencies: Software dependencies (2010)
Several networks of software dependencies. Nodes represent libraries and a directed edge denotes a library dependency on another.
This network has 1040 nodes and 5363 edges.
Tags: Technological, Software, Unweighted
https://networks.skewed.d…

The dependency digraph for irreducible finite-range random walk in free groups
Chevalier Guillaume (IMB)
https://arxiv.org/abs/2507.15902 https://

The dependency digraph for irreducible finite-range random walk in free groups
This article is one of a triptych composed with [Che25a] and [Che25b], that aims at proving an asymptotic expansion to any order of the passage probability of an irreducible equivariant finite range random walk on a tree. In this text we study the analytic and geometric properties of the objects introduced in [Che25b]. To do so we introduce the definition of a ''flooded cavern tree'' enabling a precise study of some dependency digraph associated with a given irreducible finite-range random walk…

Deep Intrinsic Coregionalization Multi-Output Gaussian Process Surrogate with Active Learning
Chun-Yi Chang, Chih-Li Sung
https://arxiv.org/abs/2508.16434 https://

Deep Intrinsic Coregionalization Multi-Output Gaussian Process Surrogate with Active Learning
Deep Gaussian Processes (DGPs) are powerful surrogate models known for their flexibility and ability to capture complex functions. However, extending them to multi-output settings remains challenging due to the need for efficient dependency modeling. We propose the Deep Intrinsic Coregionalization Multi-Output Gaussian Process (deepICMGP) surrogate for computer simulation experiments involving multiple outputs, which extends the Intrinsic Coregionalization Model (ICM) by introducing hierarchica…

Auto-scaling Approaches for Cloud-native Applications: A Survey and Taxonomy
Minxian Xu, Linfeng Wen, Junhan Liao, Huaming Wu, Kejiang Ye, Chengzhong Xu
https://arxiv.org/abs/2507.17128

Auto-scaling Approaches for Cloud-native Applications: A Survey and Taxonomy
The interactions within cloud-native applications are complex, with a constantly changing number of services and loads, posing higher demands on auto-scaling approach. This mainly involves several challenges such as microservices dependency analysis, performance profiling, anomaly detection, workload characterization and task co-location. Therefore, some advanced algorithms have been investigated into auto-scaling cloud-native applications to optimize system and application performance. These a…

Direct Dual-Energy CT Material Decomposition using Model-based Denoising Diffusion Model
Hang Xu, Alexandre Bousse, Alessandro Perelli
https://arxiv.org/abs/2507.18012 https://

Direct Dual-Energy CT Material Decomposition using Model-based Denoising Diffusion Model
Dual-energy X-ray Computed Tomography (DECT) constitutes an advanced technology which enables automatic decomposition of materials in clinical images without manual segmentation using the dependency of the X-ray linear attenuation with energy. However, most methods perform material decomposition in the image domain as a post-processing step after reconstruction but this procedure does not account for the beam-hardening effect and it results in sub-optimal results. In this work, we propose a dee…

is it too much to ask that a software dependency be:
1. fast
2. permissive open-source licensed
3. lightweight in bundle cost
4. lightweight in installation size
5. well-maintained
6. accurate
7. able to run in all of the marginally different JavaScript runtimes
8. human sourced to avoid ethical and future copyright issues with AI
9. use modern APIs and without vestigial polyfill bloat
10. use best progressive enhancement and accessibility p…

Bayesian Variable Selection in Multivariate Regression Under Collinearity in the Design Matrix
Joyee Ghosh, Xun Li
https://arxiv.org/abs/2507.17975 https://

Bayesian Variable Selection in Multivariate Regression Under Collinearity in the Design Matrix
We consider the problem of variable selection in Bayesian multivariate linear regression models, involving multiple response and predictor variables, under multivariate normal errors. In the absence of a known covariance structure, specifying a model with a non-diagonal covariance matrix is appealing. Modeling dependency in the random errors through a non-diagonal covariance matrix is generally expected to lead to improved estimation of the regression coefficients. In this article, we highlight…

Low-Complexity Semantic Packet Aggregation for Token Communication via Lookahead Search
Seunghun Lee, Jihong Park, Jinho Choi, Hyuncheol Park
https://arxiv.org/abs/2506.19451

Low-Complexity Semantic Packet Aggregation for Token Communication via Lookahead Search
Tokens are fundamental processing units of generative AI (GenAI) and large language models (LLMs), and token communication (TC) is essential for enabling remote AI-generate content (AIGC) and wireless LLM applications. Unlike traditional bits, each of which is independently treated, the semantics of each token depends on its surrounding context tokens. This inter-token dependency makes TC vulnerable to outage channels, where the loss of a single token can significantly distort the original mess…

Ah, I figured it out. Classic.
Somewhere else in the project someone is mocking one of my dependencies and overwriting the singleton instance.
So it’s wholly non deterministic whether I get a working or broken dependency at runtime.
The debugger being attached slowed execution of my particular test, making it more likely the offending one had run in parallel before I finished stepping through the code.

Are you interested in how dependency-heavy your (or another) package is and why? #rstats

GitHub - jokergoo/pkgndep: Analyzing Dependency Heaviness of R Packages
Analyzing Dependency Heaviness of R Packages. Contribute to jokergoo/pkgndep development by creating an account on GitHub.

Ties, Tails and Spectra: On Rank-Based Dependency Measures in High Dimensions
Nina D\"ornemann, Michael Fleermann, Johannes Heiny
https://arxiv.org/abs/2508.14992 https://

Ties, Tails and Spectra: On Rank-Based Dependency Measures in High Dimensions
This work is concerned with the limiting spectral distribution of rank-based dependency measures in high dimensions. We provide distribution-free results for multivariate empirical versions of Kendall's $τ$ and Spearman's $ρ$ in a setting where the dimension $p$ grows at most proportionally to the sample size $n$. Although rank-based measures are known to be well suited for discrete and heavy-tailed data, previous works in the field focused mostly on the continuous and light-tailed case. We c…

🔄 Key features include automatic garbage collection, extendable frontend formats & concurrent dependency resolution
⚡ Efficient instruction caching with build cache import/export capabilities & nested build job invocations

The $\overline\partial$-Robin Laplacian
Joaquim Duran
https://arxiv.org/abs/2507.16895 https://arxiv.org/pdf/2507.16895

The $\overline\partial$-Robin Laplacian
We study the family of operators $\{\mathcal{R}_a\}_{a\in [0,+\infty)}$ associated to the Robin-type problems in a bounded domain $Ω\subset\mathbb{R}^2$ $$ \begin{cases} -Δu = f & \text{in } Ω, \\ 2 \bar ν\partial_{\bar z} u + au = 0 & \text{on } \partialΩ, \end{cases} $$ and their dependency on the boundary parameter $a$ as it moves along $[0,+\infty)$. In this regard, we study the convergence of such operators in a resolvent sense. We also describe the eigenvalues of such operato…

Structural and Connectivity Patterns in the Maven Central Software Dependency Network
Daniel Ogenrwot, John Businge, Shaikh Arifuzzaman
https://arxiv.org/abs/2508.13819 https://…

Structural and Connectivity Patterns in the Maven Central Software Dependency Network
Understanding the structural characteristics and connectivity patterns of large-scale software ecosystems is critical for enhancing software reuse, improving ecosystem resilience, and mitigating security risks. In this paper, we investigate the Maven Central ecosystem, one of the largest repositories of Java libraries, by applying network science techniques to its dependency graph. Leveraging the Goblin framework, we extracted a sample consisting of the top 5,000 highly connected artifacts base…

#Figma's $300,000 Daily #AWS Bill Highlights Cloud Dependency Risks
https://www.infoq.com/news/2025/07/figma-a…

A B-Spline Finite Element Method for Cloth Simulation
Yuqi Meng, Yihao Shi, Kemeng Huang, Ning Guo, Taku Komura, Yin Yang, Minchen Li
https://arxiv.org/abs/2506.18867

A B-Spline Finite Element Method for Cloth Simulation
We present a B-spline finite element method (FEM) for cloth simulation. Building on quadratic B-spline basis functions, our method provides a globally $C^1$-continuous displacement field, enabling consistent and accurate discretization of both membrane and bending energies. This smooth representation effectively mitigates locking artifacts and mesh dependency issues commonly observed with linear FEM. To further improve efficiency, we develop a reduced integration scheme that separately optimize…

Beyond Syntax: Action Semantics Learning for App Agents
Bohan Tang, Dezhao Luo, Jingxuan Chen, Shaogang Gong, Jianye Hao, Jun Wang, Kun Shao
https://arxiv.org/abs/2506.17697

Beyond Syntax: Action Semantics Learning for App Agents
The advent of Large Language Models (LLMs) enables the rise of App agents that interpret user intent and operate smartphone Apps through actions such as clicking and scrolling. While prompt-based solutions with closed LLM APIs show promising ability, they incur heavy compute costs and external API dependency. Fine-tuning smaller open-source LLMs solves these limitations. However, current fine-tuning methods use a syntax learning paradigm that forces agents to reproduce exactly the ground truth …

Dependency Pairs for Expected Innermost Runtime Complexity and Strong Almost-Sure Termination of Probabilistic Term Rewriting
Jan-Christoph Kassing, Leon Spitzer, J\"urgen Giesl
https://arxiv.org/abs/2507.12918

Dependency Pairs for Expected Innermost Runtime Complexity and Strong Almost-Sure Termination of Probabilistic Term Rewriting
The dependency pair (DP) framework is one of the most powerful techniques for automatic termination and complexity analysis of term rewrite systems. While DPs were extended to prove almost-sure termination of probabilistic term rewrite systems (PTRSs), automatic complexity analysis for PTRSs is largely unexplored. We introduce the first DP framework for analyzing expected complexity and for proving positive or strong almost-sure termination (SAST) of innermost rewriting with PTRSs, i.e., finite…

CYCLE-INSTRUCT: Fully Seed-Free Instruction Tuning via Dual Self-Training and Cycle Consistency
Zhanming Shen, Hao Chen, Yulei Tang, Shaolin Zhu, Wentao Ye, Xiaomeng Hu, Haobo Wang, Gang Chen, Junbo Zhao
https://arxiv.org/abs/2508.16100

CYCLE-INSTRUCT: Fully Seed-Free Instruction Tuning via Dual Self-Training and Cycle Consistency
Instruction tuning is vital for aligning large language models (LLMs) with human intent, but current methods typically rely on costly human-annotated seed data or powerful external teacher models. While instruction back-translation techniques reduce this dependency, they remain fundamentally tethered to an initial seed set, which limits full automation, introduces biases, and can lead to inefficient use of unlabeled corpora. In this paper, we propose Cycle-Instruct, a novel framework that achie…

python_dependency: Python Dependency Network
Python's package dependency networks. Nodes in the network are Python's packages registered to PyPI and edges are dependencies among packages.
This network has 58743 nodes and 108399 edges.
Tags: Technological, Software, Unweighted
https://networks.sk…

The GameTheory package for Macaulay2
Erin Connelly, Vincenzo Galgano, Zhuang He, Giacomo Maletto, Elke Neuhaus, Irem Portakal, Hannah Tillmann-Morris, Chenyang Zhao
https://arxiv.org/abs/2507.16755

The GameTheory package for Macaulay2
We describe the GameTheory package version 1.0 for computing equilibria in game theory available since version 1.25.05 of Macaulay2. We briefly explain the four equilibrium notions, Nash, correlated, dependency, and conditional independence, and demonstrate their implementation in the package with examples.

Efficient and Scalable Self-Healing Databases Using Meta-Learning and Dependency-Driven Recovery
Joydeep Chandra, Prabal Manhas
https://arxiv.org/abs/2507.13757

Efficient and Scalable Self-Healing Databases Using Meta-Learning and Dependency-Driven Recovery
This study explored the development of a novel self-healing framework for databases using meta-learning and reinforcement learning techniques. The primary objective was to address the challenges of real-time adaptability and minimal retraining in dynamic workload environments. The proposed approach integrated Model-Agnostic Meta-Learning (MAML) with reinforcement learning to enable anomaly detection and corrective actions that adapted swiftly to evolving database conditions. Multi-objective opt…

IPIGuard: A Novel Tool Dependency Graph-Based Defense Against Indirect Prompt Injection in LLM Agents
Hengyu An, Jinghuai Zhang, Tianyu Du, Chunyi Zhou, Qingming Li, Tao Lin, Shouling Ji
https://arxiv.org/abs/2508.15310

IPIGuard: A Novel Tool Dependency Graph-Based Defense Against Indirect Prompt Injection in LLM Agents
Large language model (LLM) agents are widely deployed in real-world applications, where they leverage tools to retrieve and manipulate external data for complex tasks. However, when interacting with untrusted data sources (e.g., fetching information from public websites), tool responses may contain injected instructions that covertly influence agent behaviors and lead to malicious outcomes, a threat referred to as Indirect Prompt Injection (IPI). Existing defenses typically rely on advanced pro…

Musing again about some kind of lightweight vector graphics format as an intermediate between (a subset of) SVG and ImDrawList. Probably YAML based since we already have yaml-cpp as a dependency.

python_dependency: Python Dependency Network
Python's package dependency networks. Nodes in the network are Python's packages registered to PyPI and edges are dependencies among packages.
This network has 58743 nodes and 108399 edges.
Tags: Technological, Software, Unweighted
https://networks.sk…

Okay, time to continue bashing. Perhaps this one project is just that bad, but Conan sounds like a complete antithesis of what a package manager is all about.
Well, this package insists to build its dependencies via Conan. Except it insists on really old versions that don't work with my glibc. So I need to start swapping dependencies.
Except it turns out Conan doesn't care much about resolving dependencies. So I actually need to start adjust versions of the dependencies of packages that it wants to build. And then it starts rebuilding other stuff and again everything fails because of incompatible versions.
And when I finally manage to find a working set, the actual project fails over protobuf version. After a long WTF-ing, I finally realize that it's complaining, because it somehow managed to mix the version of protobuf built by Conan and the external protobuf installed by Conda.
So yeah, great job. A package manager that doesn't really resolve dependencies but instead forces a dependency hell on you, and on top of that ends up mixing system packages with its own packages.

This is a really cool insight about talking to people who like to use Midjourney/ChatGPT. The comparison with plastic use (and also car dependency) is great. For both of these things we know that they waste precious resources, pollute the environment and are health hazards. But even people who know this will still not let go because it's too much work. AI is not yet at this point but may soon be...

Reviewing some #aspnetcore Minimal API endpoint code today, and the need to inject every dependency, even a “RedirectManager”, feels like a code smell.
There is an elegance to an MVC endpoint or Razor Page that exists in a self-aware context.

The Custom #Tenant Code Nightmare (And How to Wake Up) 🏗️
🔥 Managing dozens of customer branches wastes 40% of development time on merges instead of features
🎨 Custom Views: Use fallback patterns
or customer-specific directories for branding without logic changes
⚙️ Custom Services: Swap implementations via dependency injection - same interface, different providers
…

@… I really appreciated how Java would make me jump through a few hoops to set a private variable in an object controlled by a dependency, but it would absolutely do it. It’s something I definitely miss when writing Rust.
In JavaScript, you can make objects via classes/prototypes, or by closing over local variables. The latter hides them because there’s no way to re…

Every company or government should think about this, prepare exit and contingency plans. Also for other dependencies.
https://www.theregister.com/2025/06/26/cost_of_microsoft_dependency/

What if Microsoft just turned you off? Security pro counts the cost of dependency
Comment: Czech researcher lays out a business case for reducing reliance on Redmond

Toda lattice formed in nonequilibrium steady states of SWCNT
Heeyuen Koh, Shigeo Maruyama
https://arxiv.org/abs/2507.18412 https://arxiv.org/pdf/2507.18412…

Toda lattice formed in nonequilibrium steady states of SWCNT
Toda lattice or FPUT chain-like dynamics have been regarded as the prerequisite condition to explain the length dependency of high thermal conductivity of low-dimensional systems at the nanoscale. In this paper, a hypothetical condition is introduced that establishes a theoretical connection between the thermal conductivity of a nanoscale low-dimensional system in nonequilibrium steady states(NESS) and the canonical motion of the equation in the Toda lattice in equilibrium. The hypothesis relie…

Thanks to the Dependency Track daily scan, vulnerabilities like this now get flagged pretty quickly so we can do an out-of-schedule dependency bump.
One less thing to worry about :)
#DevOps
https://

EUVD
European Vulnerability Database

ok but are you absolutely sure, libcxx?

jdk: Java SE Dev Kit dependencies (1.6.0.7)
A network of class dependencies within the JDK (Java SE Development Kit) 1.6.0.7 framework. Nodes represent classes and a directed edge indicates a dependency of one class on another.
This network has 6434 nodes and 150985 edges.
Tags: Technological, Software, Unweighted, Multigraph
https://

DEPTH: Hallucination-Free Relation Extraction via Dependency-Aware Sentence Simplification and Two-tiered Hierarchical Refinement
Yupei Yang, Fan Feng, Lin Yang, Wanxi Deng, Lin Qu, Biwei Huang, Shikui Tu, Lei Xu
https://arxiv.org/abs/2508.14391

DEPTH: Hallucination-Free Relation Extraction via Dependency-Aware Sentence Simplification and Two-tiered Hierarchical Refinement
Relation extraction enables the construction of structured knowledge for many downstream applications. While large language models (LLMs) have shown great promise in this domain, most existing methods concentrate on relation classification, which predicts the semantic relation type between a related entity pair. However, we observe that LLMs often struggle to reliably determine whether a relation exists, especially in cases involving complex sentence structures or intricate semantics, which lea…

Parallel repetition of expanded, and multiplayer, Quantum games: anchoring, optimal values, generalized error bounds, dependency-breaking as symmetry-breaking
Pete Rigas
https://arxiv.org/abs/2508.09380

Parallel repetition of expanded, and multiplayer, Quantum games: anchoring, optimal values, generalized error bounds, dependency-breaking as symmetry-breaking
We demonstrate that parallel repetition of the multiplayer anchored optimal value, $ω\big( G_{\bot} \big)^{\otimes n}$, decays exponentially. Central to our approach are several probabilistic computations, pertaining to: (1) the computation of expected values for quantifying how the winning probability of the game is likely to change under the anchoring transformation; (2) the computation of positive operator valued measurements, which can be placed into direct correspondence with several prob…

Design of an Edge-based Portable EHR System for Anemia Screening in Remote Health Applications
Sebastian A. Cruz Romero, Misael J. Mercado Hernandez, Samir Y. Ali Rivera, Jorge A. Santiago Fernandez, Wilfredo E. Lugo Beauchamp
https://arxiv.org/abs/2507.15146

Design of an Edge-based Portable EHR System for Anemia Screening in Remote Health Applications
The design of medical systems for remote, resource-limited environments faces persistent challenges due to poor interoperability, lack of offline support, and dependency on costly infrastructure. Many existing digital health solutions neglect these constraints, limiting their effectiveness for frontline health workers in underserved regions. This paper presents a portable, edge-enabled Electronic Health Record platform optimized for offline-first operation, secure patient data management, and m…

So what I learned from the recent Google outage, is how much of a cirklejerk "big tech" actually is.
Google did a fucky wucky... Which caused Cloudflare to go belly up, Shopify to go belly up, Spotify to go belly up...
Imagine having given *one* company having so much power that, if they make a mistake somewhere, half the internet is gone.
So if you self-host, make sure to see how your dependency chain is.
How much places can make a mistake that can knock you …

Toward an African Agenda for AI Safety
Samuel T. Segun, Rachel Adams, Ana Florido, Scott Timcke, Jonathan Shock, Leah Junck, Fola Adeleke, Nicolas Grossman, Ayantola Alayande, Jerry John Kponyo, Matthew Smith, Dickson Marfo Fosu, Prince Dawson Tetteh, Juliet Arthur, Stephanie Kasaon, Odilile Ayodele, Laetitia Badolo, Paul Plantinga, Michael Gastrow, Sumaya Nur Adan, Joanna Wiaterek, Cecil Abungu, Kojo Apeagyei, Luise Eder, Tegawende Bissyande

Toward an African Agenda for AI Safety
This paper maps Africa's distinctive AI risk profile, from deepfake fuelled electoral interference and data colonial dependency to compute scarcity, labour disruption and disproportionate exposure to climate driven environmental costs. While major benefits are promised to accrue, the availability, development and adoption of AI also mean that African people and countries face particular AI safety risks, from large scale labour market disruptions to the nefarious use of AI to manipulate public o…

🎨 Droip: The Modern Website Builder WordPress Needed
#web

Droip: The Modern Website Builder WordPress Needed — Smashing Magazine
Traditional page builders have shaped how we build WordPress sites for years. Let’s take a closer look at [Droip](https://droip.com/), a modern, no-code visual builder, and explore how it redefines the experience with cleaner performance, full design freedom, and zero plugin dependency.

Arintra, whose AI medical coding system translates clinical documentation into insurance codes for healthcare providers, raised a $21M Series A led by Peak XV (Erin Brodwin/Axios)
https://www.axios.com/pro/health-tech-deals/2025/08/12/arintra-21m…

Exclusive: Arintra raises $21M to expand into denials prevention
As financial pressure mounts on U.S. health systems, Arintra aims to leverage gen-AI to secure reimbursement while reducing dependency on human coders.

Evaluating virtual-control-augmented trials for reproducing treatment effect from original RCTs
Alex Fernandes, Rapha\"el Porcher, Viet-Thi Tran, Fran\c{c}ois Petit
https://arxiv.org/abs/2507.16048

Evaluating virtual-control-augmented trials for reproducing treatment effect from original RCTs
This study investigates the use of virtual patient data to augment control arms in randomised controlled trials (RCTs). Using data from the IST and IST3 trials, we simulated RCTs in which the recruitment in the control arms would stop after a fraction of the initially planned sample size, and would be completed by virtual patients generated by CTGAN and TVAE, two AI algorithms trained on the recruited control patients. In IST, the absolute risk difference(ARD) on death or dependency at 14 days …

It's a Complete Haystack: Understanding Dependency Management Needs in Computer-Aided Design
Kathy Cheng, Alison Olechowski, Shurui Zhou
https://arxiv.org/abs/2508.05940 htt…

It's a Complete Haystack: Understanding Dependency Management Needs in Computer-Aided Design
In today's landscape, hardware development teams face increasing demands for better quality products, greater innovation, and shorter manufacturing lead times. Despite the need for more efficient and effective processes, hardware designers continue to struggle with a lack of awareness of design changes and other collaborators' actions, a persistent issue in decades of CSCW research. One significant and unaddressed challenge is understanding and managing dependencies between 3D CAD (computer-aid…

ROSE: Transformer-Based Refactoring Recommendation for Architectural Smells
Samal Nursapa, Anastassiya Samuilova, Alessio Bucaioni. Phuong T. Nguyen
https://arxiv.org/abs/2507.12561

ROSE: Transformer-Based Refactoring Recommendation for Architectural Smells
Architectural smells such as God Class, Cyclic Dependency, and Hub-like Dependency degrade software quality and maintainability. Existing tools detect such smells but rarely suggest how to fix them. This paper explores the use of pre-trained transformer models--CodeBERT and CodeT5--for recommending suitable refactorings based on detected smells. We frame the task as a three-class classification problem and fine-tune both models on over 2 million refactoring instances mined from 11,149 open-sour…

GratNet: A Photorealistic Neural Shader for Diffractive Surfaces
Narayan Kandel, Daljit Singh J. S. Dhillon
https://arxiv.org/abs/2506.15815 https://

GratNet: A Photorealistic Neural Shader for Diffractive Surfaces
Structural coloration is commonly modeled using wave optics for reliable and photorealistic rendering of natural, quasi-periodic and complex nanostructures. Such models often rely on dense, preliminary or preprocessed data to accurately capture the nuanced variations in diffractive surface reflectances. This heavy data dependency warrants implicit neural representation which has not been addressed comprehensively in the current literature. In this paper, we present a multi-layer perceptron (MLP…

MS-UMamba: An Improved Vision Mamba Unet for Fetal Abdominal Medical Image Segmentation
Caixu Xu, Junming Wei, Huizhen Chen, Pengchen Liang, Bocheng Liang, Ying Tan, Xintong Wei
https://arxiv.org/abs/2506.12441

MS-UMamba: An Improved Vision Mamba Unet for Fetal Abdominal Medical Image Segmentation
Recently, Mamba-based methods have become popular in medical image segmentation due to their lightweight design and long-range dependency modeling capabilities. However, current segmentation methods frequently encounter challenges in fetal ultrasound images, such as enclosed anatomical structures, blurred boundaries, and small anatomical structures. To address the need for balancing local feature extraction and global context modeling, we propose MS-UMamba, a novel hybrid convolutional-mamba mo…

Finite-Time Ruin for the Compound Markov Binomial Risk Model
Zbigniew Palmowski, Lewis Ramsden, Apostolos D. Papaioannou
https://arxiv.org/abs/2507.16448 h…

Finite-Time Ruin for the Compound Markov Binomial Risk Model
In this paper, we study finite-time ruin probabilities for the compound Markov binomial risk model - a discrete-time model where claim sizes are modulated by a finite-state ergodic Markov chain. In the classic (non-modulated) case, the risk process has interchangeable increments and consequently, its finite-time ruin probability can be obtained in terms of Takács' famous Ballot Theorem results. Unfortunately, due to the dependency of our process on the state(s) of the modulating chain these do…

python_dependency: Python Dependency Network
Python's package dependency networks. Nodes in the network are Python's packages registered to PyPI and edges are dependencies among packages.
This network has 58743 nodes and 108399 edges.
Tags: Technological, Software, Unweighted
https://networks.sk…

Replaced article(s) found for cs.DB. https://arxiv.org/list/cs.DB/new
[1/1]:
- Enabling Data Dependency-based Query Optimization
Daniel Lindner, Daniel Ritter, Felix Naumann

Analysis of Anonymous User Interaction Relationships and Prediction of Advertising Feedback Based on Graph Neural Network
Yanjun Dai, Haoyang Feng, Yuan Gao
https://arxiv.org/abs/2506.13787

Analysis of Anonymous User Interaction Relationships and Prediction of Advertising Feedback Based on Graph Neural Network
While online advertising is highly dependent on implicit interaction networks of anonymous users for engagement inference, and for the selection and optimization of delivery strategies, existing graph models seldom can capture the multi-scale temporal, semantic and higher-order dependency features of these interaction networks, thus it's hard to describe the complicated patterns of the anonymous behavior. In this paper, we propose Decoupled Temporal-Hierarchical Graph Neural Network (DTH-GNN), …

🚨🚨🚨 uv has fixed my pet issue https://github.com/astral-sh/uv/issues/6314 and `uv tool install ansible --with-executables-from ansible-core` works now! 🚨🚨🚨
for us, that was the last blocker before going all-in on uv.

Support including dependency executables (e.g., `--include-deps`) in `uv tool install` · Issue #6314 · astral-sh/uv
hi, congrats on 0.3.0! I've noticed one very useful pipx option that uv tool is currently missing: --install-deps. It means that it also adds the CLIs of packages it depends on. This is crucial for...

Improving Neural Diarization through Speaker Attribute Attractors and Local Dependency Modeling
David Palzer, Matthew Maciejewski, Eric Fosler-Lussier
https://arxiv.org/abs/2506.05593

Improving Neural Diarization through Speaker Attribute Attractors and Local Dependency Modeling
In recent years, end-to-end approaches have made notable progress in addressing the challenge of speaker diarization, which involves segmenting and identifying speakers in multi-talker recordings. One such approach, Encoder-Decoder Attractors (EDA), has been proposed to handle variable speaker counts as well as better guide the network during training. In this study, we extend the attractor paradigm by moving beyond direct speaker modeling and instead focus on representing more detailed `speake…

rt-RISeg: Real-Time Model-Free Robot Interactive Segmentation for Active Instance-Level Object Understanding
Howard H. Qian, Yiting Chen, Gaotian Wang, Podshara Chanrungmaneekul, Kaiyu Hang
https://arxiv.org/abs/2507.10776

rt-RISeg: Real-Time Model-Free Robot Interactive Segmentation for Active Instance-Level Object Understanding
Successful execution of dexterous robotic manipulation tasks in new environments, such as grasping, depends on the ability to proficiently segment unseen objects from the background and other objects. Previous works in unseen object instance segmentation (UOIS) train models on large-scale datasets, which often leads to overfitting on static visual features. This dependency results in poor generalization performance when confronted with out-of-distribution scenarios. To address this limitation, …

TraGe: A Generic Packet Representation for Traffic Classification Based on Header-Payload Differences
Chungang Lin, Yilong Jiang, Weiyao Zhang, Xuying Meng, Tianyu Zuo, Yujun Zhang
https://arxiv.org/abs/2506.14151

TraGe: A Generic Packet Representation for Traffic Classification Based on Header-Payload Differences
Traffic classification has a significant impact on maintaining the Quality of Service (QoS) of the network. Since traditional methods heavily rely on feature extraction and large scale labeled data, some recent pre-trained models manage to reduce the dependency by utilizing different pre-training tasks to train generic representations for network packets. However, existing pre-trained models typically adopt pre-training tasks developed for image or text data, which are not tailored to traffic d…

Having to add an explicit dependency declaration to a #gradle build file, to ensure that an app isn't built with a GSON version that has vulnerabilities dating back to 2022, feels sooo wrong..... but hey, that's #AndroidDev!
(if you're wondering, a dependency of the project has a deep …

python_dependency: Python Dependency Network
Python's package dependency networks. Nodes in the network are Python's packages registered to PyPI and edges are dependencies among packages.
This network has 58743 nodes and 108399 edges.
Tags: Technological, Software, Unweighted
https://networks.sk…

Step-by-step Instructions and a Simple Tabular Output Format Improve the Dependency Parsing Accuracy of LLMs
Hiroshi Matsuda, Chunpeng Ma, Masayuki Asahara
https://arxiv.org/abs/2506.09983

Step-by-step Instructions and a Simple Tabular Output Format Improve the Dependency Parsing Accuracy of LLMs
Recent advances in large language models (LLMs) have enabled impressive performance in various tasks. However, standard prompting often struggles to produce structurally valid and accurate outputs, especially in dependency parsing. We propose a novel step-by-step instruction strategy, where universal part-of-speech tagging precedes the prediction of syntactic heads and dependency labels, and a simplified CoNLL-U like output format, our method achieves state-of-the-art accuracy on Universal Depe…

Solving Package Management via Hypergraph Dependency Resolution
Ryan Gibb, Patrick Ferris, David Allsopp, Michael Winston Dales, Mark Elvers, Thomas Gazagnaire, Sadiq Jaffer, Thomas Leonard, Jon Ludlam, Anil Madhavapeddy
https://arxiv.org/abs/2506.10803

Solving Package Management via Hypergraph Dependency Resolution
Package managers are everywhere, with seemingly every language and operating system implementing their own solution. The lack of interoperability between these systems means that multi-lingual projects are unable to express precise dependencies across language ecosystems, and external system and hardware dependencies are typically implicit and unversioned. We define HyperRes, a formal system for describing versioned dependency resolution using a hypergraph that is expressive enough to model man…

The CSA releases Matter 1.4.2 to improve reliability, stability, and cross-platform coordination, like Wi-Fi-only commissioning to cut its Bluetooth dependency (Jennifer Pattison Tuohy/The Verge)
https://www.theverge.com/matter/757179/matter-1…

Matter’s latest update doubles down on stability and pushes the platforms to play better together
Updates to how Wi-Fi routers work in Matter, how devices connect to the network, and the addition of Wi-Fi commissioning arrive with the latest Matter spec.

Critical trajectories in kinetic geometry
Helge Dietert, Cl\'ement Mouhot, Lukas Niebel, Rico Zacher
https://arxiv.org/abs/2508.14868 https://arxiv.org…

Critical trajectories in kinetic geometry
We construct critical trajectories in kinetic geometry, i.e. curves in $\mathbb{R}^{1+2n}$ that are: tangential to the vector fields $\partial_t+v\cdot \nabla_x$ and $\nabla_v$, connecting any two given points, respecting the underlying kinetic scaling, and with the property, that the singularity of the $v$-tangent vector near the starting point equates the degeneracy of the dependency of the curve velocity in terms of the endpoint velocity. The construction is based on Newton's laws of motio…

Dependency on Meta AI Chatbot in Messenger Among STEM and Non-STEM Students in Higher Education
Hilene E. Hernandez, Rhiziel P. Manalese, Roque Francis B. Dianelo, Jaymark A. Yambao, Almer B. Gamboa, Lloyd D. Feliciano, Mike Haizon M. David, Freneil R. Pampo, John Paul P. Miranda
https://arxiv.org/abs/2507.21059

Dependency on Meta AI Chatbot in Messenger Among STEM and Non-STEM Students in Higher Education
To understand the potential dependency of tertiary students regarding Meta AI in the academic context. This descriptive cross-sectional study surveyed 872 tertiary students from public and private institutions in Luzon, Philippines. Demographic information and perceptions on Meta AI dependency based on existing literature were collected. Descriptive statistics were used to summarize the data and differences between STEM and non-STEM students were analyzed using the Mann-Whitney U test. The resu…

jung: JUNG and javax class dependencies (2012)
A network of software class dependency within the JUNG 2.0.1 and javax 1.6.0.7 library namespaces edu.uci.ics.jung and java/javax. Nodes represent classes and a directed edge indicates a dependency of one class on another.
This network has 6120 nodes and 138706 edges.
Tags: Technological, Software, Unweighted

python_dependency: Python Dependency Network
Python's package dependency networks. Nodes in the network are Python's packages registered to PyPI and edges are dependencies among packages.
This network has 58743 nodes and 108399 edges.
Tags: Technological, Software, Unweighted
https://networks.sk…

Tool Graph Retriever: Exploring Dependency Graph-based Tool Retrieval for Large Language Models
Linfeng Gao, Yaoxiang Wang, Minlong Peng, Jialong Tang, Yuzhe Shang, Mingming Sun, Jinsong Su
https://arxiv.org/abs/2508.05152

Tool Graph Retriever: Exploring Dependency Graph-based Tool Retrieval for Large Language Models
With the remarkable advancement of AI agents, the number of their equipped tools is increasing rapidly. However, integrating all tool information into the limited model context becomes impractical, highlighting the need for efficient tool retrieval methods. In this regard, dominant methods primarily rely on semantic similarities between tool descriptions and user queries to retrieve relevant tools. However, they often consider each tool independently, overlooking dependencies between tools, whi…

A Joint Multitask Model for Morpho-Syntactic Parsing
Demian Inostroza, Mel Mistica, Ekaterina Vylomova, Chris Guest, Kemal Kurniawan
https://arxiv.org/abs/2508.14307 https://

A Joint Multitask Model for Morpho-Syntactic Parsing
We present a joint multitask model for the UniDive 2025 Morpho-Syntactic Parsing shared task, where systems predict both morphological and syntactic analyses following novel UD annotation scheme. Our system uses a shared XLM-RoBERTa encoder with three specialized decoders for content word identification, dependency parsing, and morphosyntactic feature prediction. Our model achieves the best overall performance on the shared task's leaderboard covering nine typologically diverse languages, with …

dependency groups 🥰

New in #Python world: #setuptools now vendors deep dependencies with LGPL license. Not that I do mind (but some people and companies do!) — but these dependencies aren't even used! I mean, `autocommand` is just a dependency of some scripts in `jaraco.text` that aren't used by setuptools.
Oh, wait, I actually do care, because I need to fix LICENSE in dev-python/ensurepip-setuptools.
https://github.com/pypa/setuptools/issues/5045
https://github.com/pypa/setuptools/issues/5049

Data Dependency Inference for Industrial Code Generation Based on UML Sequence Diagrams
Wenxin Mao, Zhitao Wang Long Wang, Sirong Chen, Cuiyun Gao, Luyang Cao, Ziming Liu, Qiming Zhang, Jun Zhou, Zhi Jin
https://arxiv.org/abs/2508.03379

Data Dependency Inference for Industrial Code Generation Based on UML Sequence Diagrams
Large language models (LLMs) excel at generating code from natural language (NL) descriptions. However, the plain textual descriptions are inherently ambiguous and often fail to capture complex requirements like intricate system behaviors, conditional logic, and architectural constraints; implicit data dependencies in service-oriented architectures are difficult to infer and handle correctly. To bridge this gap, we propose a novel step-by-step code generation framework named UML2Dep by leveragi…

jung: JUNG and javax class dependencies (2012)
A network of software class dependency within the JUNG 2.0.1 and javax 1.6.0.7 library namespaces edu.uci.ics.jung and java/javax. Nodes represent classes and a directed edge indicates a dependency of one class on another.
This network has 6120 nodes and 138706 edges.
Tags: Technological, Software, Unweighted

jung: JUNG and javax class dependencies (2012)
A network of software class dependency within the JUNG 2.0.1 and javax 1.6.0.7 library namespaces edu.uci.ics.jung and java/javax. Nodes represent classes and a directed edge indicates a dependency of one class on another.
This network has 6120 nodes and 138706 edges.
Tags: Technological, Software, Unweighted

Temporal Network Analysis of Microservice Architectural Degradation
Alexander Bakhtin
https://arxiv.org/abs/2508.11571 https://arxiv.org/pdf/2508.11571

Temporal Network Analysis of Microservice Architectural Degradation
Microservice architecture can be modeled as a network of microservices making calls to each other, commonly known as the service dependency graph. Network Science can provide methods to study such networks. In particular, temporal network analysis is a branch of Network Science that analyzes networks evolving with time. In microservice systems, temporal networks can arise if we examine the architecture of the system across releases or monitor a deployed system using tracing. In this research …

It's time to shame #PDM, the "#Python package and dependency manager", for embracing unethical coding. Also, clearly wasting large amounts energy to make a 4-line change, and get it wrong twice while at it.
(Yes, the "no significant changes" is another fix to the same #LLM coding mistake.)
#AI

Signal-First Architectures: Rethinking Front-End Reactivity
Shrinivass Arunachalam Balasubramanian
https://arxiv.org/abs/2506.13815 https://

Signal-First Architectures: Rethinking Front-End Reactivity
Modern front-end frameworks face escalating reactivity management challenges, including performance degradation from complex observable chains and unpredictable re-renders. This paper introduces Signal-First Architecture--a novel paradigm where granular, dependency-tracked signals are the atomic unit of reactivity. Unlike traditional RxJS or NgRx patterns, Signal-First enforces reactive flows from explicit signal declarations, with derived values via computed() and side effects scoped to effect…

jdk: Java SE Dev Kit dependencies (1.6.0.7)
A network of class dependencies within the JDK (Java SE Development Kit) 1.6.0.7 framework. Nodes represent classes and a directed edge indicates a dependency of one class on another.
This network has 6434 nodes and 150985 edges.
Tags: Technological, Software, Unweighted, Multigraph
https://

StylOch at PAN: Gradient-Boosted Trees with Frequency-Based Stylometric Features
Jeremi K. Ochab, Mateusz Matias, Tymoteusz Boba, Tomasz Walkowiak
https://arxiv.org/abs/2507.12064

StylOch at PAN: Gradient-Boosted Trees with Frequency-Based Stylometric Features
This submission to the binary AI detection task is based on a modular stylometric pipeline, where: public spaCy models are used for text preprocessing (including tokenisation, named entity recognition, dependency parsing, part-of-speech tagging, and morphology annotation) and extracting several thousand features (frequencies of n-grams of the above linguistic annotations); light-gradient boosting machines are used as the classifier. We collect a large corpus of more than 500 000 machine-generat…

jung: JUNG and javax class dependencies (2012)
A network of software class dependency within the JUNG 2.0.1 and javax 1.6.0.7 library namespaces edu.uci.ics.jung and java/javax. Nodes represent classes and a directed edge indicates a dependency of one class on another.
This network has 6120 nodes and 138706 edges.
Tags: Technological, Software, Unweighted

Model Discovery and Graph Simulation: A Lightweight Alternative to Chaos Engineering
Anatoly A. Krasnovsky, Alexander Zorkin
https://arxiv.org/abs/2506.11176

Model Discovery and Graph Simulation: A Lightweight Alternative to Chaos Engineering
Microservice applications are prone to cascading failures because of dense inter-service dependencies. Ensuring resilience usually demands fault-injection experiments in production-like setups. We propose \textit{model discovery} -- an automated CI/CD step that extracts a live dependency graph from trace data -- and show that this lightweight representation is sufficient for accurate resilience prediction. Using the DeathStarBench Social Network, we build the graph, simulate failures via Monte-…

jung: JUNG and javax class dependencies (2012)
A network of software class dependency within the JUNG 2.0.1 and javax 1.6.0.7 library namespaces edu.uci.ics.jung and java/javax. Nodes represent classes and a directed edge indicates a dependency of one class on another.
This network has 6120 nodes and 138706 edges.
Tags: Technological, Software, Unweighted

jdk: Java SE Dev Kit dependencies (1.6.0.7)
A network of class dependencies within the JDK (Java SE Development Kit) 1.6.0.7 framework. Nodes represent classes and a directed edge indicates a dependency of one class on another.
This network has 6434 nodes and 150985 edges.
Tags: Technological, Software, Unweighted, Multigraph
https://

jung: JUNG and javax class dependencies (2012)
A network of software class dependency within the JUNG 2.0.1 and javax 1.6.0.7 library namespaces edu.uci.ics.jung and java/javax. Nodes represent classes and a directed edge indicates a dependency of one class on another.
This network has 6120 nodes and 138706 edges.
Tags: Technological, Software, Unweighted

jung: JUNG and javax class dependencies (2012)
A network of software class dependency within the JUNG 2.0.1 and javax 1.6.0.7 library namespaces edu.uci.ics.jung and java/javax. Nodes represent classes and a directed edge indicates a dependency of one class on another.
This network has 6120 nodes and 138706 edges.
Tags: Technological, Software, Unweighted

jung: JUNG and javax class dependencies (2012)
A network of software class dependency within the JUNG 2.0.1 and javax 1.6.0.7 library namespaces edu.uci.ics.jung and java/javax. Nodes represent classes and a directed edge indicates a dependency of one class on another.
This network has 6120 nodes and 138706 edges.
Tags: Technological, Software, Unweighted

jung: JUNG and javax class dependencies (2012)
A network of software class dependency within the JUNG 2.0.1 and javax 1.6.0.7 library namespaces edu.uci.ics.jung and java/javax. Nodes represent classes and a directed edge indicates a dependency of one class on another.
This network has 6120 nodes and 138706 edges.
Tags: Technological, Software, Unweighted

jdk: Java SE Dev Kit dependencies (1.6.0.7)
A network of class dependencies within the JDK (Java SE Development Kit) 1.6.0.7 framework. Nodes represent classes and a directed edge indicates a dependency of one class on another.
This network has 6434 nodes and 150985 edges.
Tags: Technological, Software, Unweighted, Multigraph
https://

jdk: Java SE Dev Kit dependencies (1.6.0.7)
A network of class dependencies within the JDK (Java SE Development Kit) 1.6.0.7 framework. Nodes represent classes and a directed edge indicates a dependency of one class on another.
This network has 6434 nodes and 150985 edges.
Tags: Technological, Software, Unweighted, Multigraph
https://

jdk: Java SE Dev Kit dependencies (1.6.0.7)
A network of class dependencies within the JDK (Java SE Development Kit) 1.6.0.7 framework. Nodes represent classes and a directed edge indicates a dependency of one class on another.
This network has 6434 nodes and 150985 edges.
Tags: Technological, Software, Unweighted, Multigraph
https://

software_dependencies: Software dependencies (2010)
Several networks of software dependencies. Nodes represent libraries and a directed edge denotes a library dependency on another.
This network has 181 nodes and 470 edges.
Tags: Technological, Software, Unweighted
https://networks.skewed.de/n…

jdk: Java SE Dev Kit dependencies (1.6.0.7)
A network of class dependencies within the JDK (Java SE Development Kit) 1.6.0.7 framework. Nodes represent classes and a directed edge indicates a dependency of one class on another.
This network has 6434 nodes and 150985 edges.
Tags: Technological, Software, Unweighted, Multigraph
https://

software_dependencies: Software dependencies (2010)
Several networks of software dependencies. Nodes represent libraries and a directed edge denotes a library dependency on another.
This network has 550 nodes and 3691 edges.
Tags: Technological, Software, Unweighted
https://networks.skewed.de/…