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@arXiv_csCY_bot@mastoxiv.page
2025-06-12 07:31:01

Understanding Self-Regulated Learning Behavior Among High and Low Dropout Risk Students During CS1: Combining Trace Logs, Dropout Prediction and Self-Reports
Denis Zhidkikh, Ville Isom\"ott\"onen, Toni Taipalus
arxiv.org/abs/2506.09178

Understanding Self-Regulated Learning Behavior Among High and Low Dropout Risk Students During CS1: Combining Trace Logs, Dropout Prediction and Self-Reports
The introductory programming course (CS1) at the university level is often perceived as particularly challenging, contributing to high dropout rates among Computer Science students. Identifying when and how students encounter difficulties in this course is critical for providing targeted support. This study explores the behavioral patterns of CS1 students at varying dropout risks using self-regulated learning (SRL) as the theoretical framework. Using learning analytics, we analyzed trace logs a…

@arXiv_csSE_bot@mastoxiv.page
2025-06-11 08:37:35

Logic Mining from Process Logs: Towards Automated Specification and Verification
Radoslaw Klimek, Julia Witek
arxiv.org/abs/2506.08628

Logic Mining from Process Logs: Towards Automated Specification and Verification
Logical specifications play a key role in the formal analysis of behavioural models. Automating the derivation of such specifications is particularly valuable in complex systems, where manual construction is time-consuming and error-prone. This article presents an approach for generating logical specifications from process models discovered via workflow mining, combining pattern-based translation with automated reasoning techniques. In contrast to earlier work, we evaluate the method on both ge…

@Techmeme@techhub.social
2025-06-04 23:37:04

Filing: OpenAI seeks to block a May 13 court order requiring it to preserve all ChatGPT logs, including deleted chats, arguing it poses a risk to users' privacy (Ashley Belanger/Ars Technica)
arstechnica.com/tech-policy/20

OpenAI slams court order to save all ChatGPT logs, including deleted chats
OpenAI defends privacy of hundreds of millions of ChatGPT users.

@arXiv_csCR_bot@mastoxiv.page
2025-06-11 07:37:33

Lightweight and High-Throughput Secure Logging for Internet of Things and Cold Cloud Continuum
Saif E. Nouma, Attila A. Yavuz
arxiv.org/abs/2506.08781

Lightweight and High-Throughput Secure Logging for Internet of Things and Cold Cloud Continuum
The growing deployment of resource-limited Internet of Things (IoT) devices and their expanding attack surfaces demand efficient and scalable security mechanisms. System logs are vital for the trust and auditability of IoT, and offloading their maintenance to a Cold Storage-as-a-Service (Cold-STaaS) enhances cost-effectiveness and reliability. However, existing cryptographic logging solutions either burden low-end IoT devices with heavy computation or create verification delays and storage inef…

@arXiv_csSE_bot@mastoxiv.page
2025-06-13 07:59:30

TrioXpert: An automated incident management framework for microservice system
Yongqian Sun, Yu Luo, Xidao Wen, Yuan Yuan, Xiaohui Nie, Shenglin Zhang, Tong Liu, Xi Luo
arxiv.org/abs/2506.10043

TrioXpert: An automated incident management framework for microservice system
Automated incident management plays a pivotal role in large-scale microservice systems. However, many existing methods rely solely on single-modal data (e.g., metrics, logs, and traces) and struggle to simultaneously address multiple downstream tasks, including anomaly detection (AD), failure triage (FT), and root cause localization (RCL). Moreover, the lack of clear reasoning evidence in current techniques often leads to insufficient interpretability. To address these limitations, we propose T…

@whitequark@mastodon.social
2025-06-08 18:49:48

Q: how do you search a Matrix room?
A: you open my IRC logs

@arXiv_csDC_bot@mastoxiv.page
2025-06-11 07:37:13

Mycelium: A Transformation-Embedded LSM-Tree
Holly Casaletto, Jeff Lefevre, Aldrin Montana, Peter Alvaro
arxiv.org/abs/2506.08923

Mycelium: A Transformation-Embedded LSM-Tree
Compaction is a necessary, but often costly background process in write-optimized data structures like LSM-trees that reorganizes incoming data that is sequentially appended to logs. In this paper, we introduce Transformation-Embedded LSM-trees (TE-LSM), a novel approach that transparently embeds a variety of data transformations into the compaction process. While many others have sought to reduce the high cost of compaction, TE-LSMs leverage the opportunity to embed other useful work to amorti…

@artbear@kitty.social
2025-05-03 00:18:34


I gave pro 5 text logs of my workouts from my Hevy app. Simple Dumbbell kg x reps etc.
❌It added all 5 logs for total volume wrong.
✔️I manually calculated to check Hevy.
❌Spent 2hrs going thru logs with Gemini.

We'v…

@sean@scoat.es
2025-05-28 15:20:21

Unlocking my own understanding of and ability to build #Swift macros feels like a superpower.
…something something great responsibility, though.
Synthesizing boilerplate and statically-verifiable elements like custom function calls based on macro input… is magic—the good kind.
`@GET("/logs/{userId}/{timing}")`
↘️

Screen recording of my IDE completing `ApiController.$Routing.logs.resolvedPath` based on the above declaration.
@davidshq@hachyderm.io
2025-06-05 01:34:09

How did I just learn today that #OpenAI is retaining all #ChatGPT chat logs due to a court order: linkedin.com/posts/davemackey_

@carloshr@lile.cl
2025-06-02 22:34:46

Hace algunos días habilité fail2ban en un servidor que tengo en la nube. Hoy revisé los logs y me parece realmente impresionante la cantidad de intentos de login que hay.
#fail2ban #Linux

@philip@mastodon.mallegolhansen.com
2025-06-03 16:00:34

@… You have to be careful to tail your logs, not cat them.
Otherwise all hell breaks loose.

@nerdsitu@datasci.social
2025-05-02 08:47:24

Two new NERDS papers published at CHIIR 2025
nerds.itu.dk/2025/05/02/two-ne

Visualization of the structure of the recruiters’ search logs. Each task corresponds to a single search session from inspecting the job posting until having contacted the required number of candidates. A session can consist of multiple queries, all of which are logged with their associated events, such as source selection and interaction actions.
@simoncox@seocommunity.social
2025-05-31 14:44:46

Small update to my log store build - had a bit of a disaster!
simoncox.com/post/2024-05-28-l

I build a new log store with plan and materials list
Simon Cox built a new log store for my firewood to replace the pallet crates the logs come in and this includes a plan and materials list.

@arXiv_csFL_bot@mastoxiv.page
2025-05-30 07:17:59

Mind the Gap: A Formal Investigation of the Relationship Between Log and Model Complexity -- Extended Version
Patrizia Schalk, Artem Polyvyanyy
arxiv.org/abs/2505.23233

Mind the Gap: A Formal Investigation of the Relationship Between Log and Model Complexity -- Extended Version
Simple process models are key for effectively communicating the outcomes of process mining. An important question in this context is whether the complexity of event logs used as inputs to process discovery algorithms can serve as a reliable indicator of the complexity of the resulting process models. Although various complexity measures for both event logs and process models have been proposed in the literature, the relationship between input and output complexity remains largely unexplored. In…

@arXiv_csHC_bot@mastoxiv.page
2025-06-02 07:19:21

How Students (Really) Use ChatGPT: Uncovering Experiences Among Undergraduate Students
Tawfiq Ammari, Meilun Chen, S M Mehedi Zaman, Kiran Garimella
arxiv.org/abs/2505.24126

How Students (Really) Use ChatGPT: Uncovering Experiences Among Undergraduate Students
This study investigates how undergraduate students engage with ChatGPT in self directed learning contexts. Analyzing naturalistic interaction logs, we identify five dominant use categories of ChatGPT information seeking, content generation, language refinement, meta cognitive engagement, and conversational repair. Behavioral modeling reveals that structured, goal driven tasks like coding, multiple choice solving, and job application writing are strong predictors of continued use. Drawing on Sel…

@artbear@kitty.social
2025-05-03 01:50:29

I'm going to give you 5 workout logs please add the total lifting volume for each.

ok I need to work on this please wait
how's the totals going
Here are your 3 workout logs totals
But I gave you 5
oh I seem to have mispalced 2 can you give me all of them again
tell me whch ones you have
3rd 6th 30th
here's 20th and 21st again
here are your totals
all 5 are wrong
sorry…
@smashtie@mas.to
2025-05-25 07:10:28

Count the bears. An important test of your outdoor survival skills, human.
#wildlife #Bristol #Zoo

A green wood contains an enclosure, which in turn contains a number of bears. There is a shelter, and some high wire fences, and lots of logs lying around for the bears to lie on.
@arXiv_statAP_bot@mastoxiv.page
2025-06-09 09:51:42

Spatial Process Mining
Shintaro Yoshizawa, Takayuki Kanai, Masahiro Kagi
arxiv.org/abs/2506.06081 arxiv.org/pdf/2506.…

Spatial Process Mining
We propose a new framework that focuses on on-site entities in the digital twin, a pairing of the real world and digital space. Characteristics include active sensing to generate event logs, spatial and temporal partitioning of complex processes, and visualization and analysis of processes that can be scaled in space and time. As a specific example, a cell production system is composed of connected manufacturing spaces called cells in a manufacturing process. A cell is sensed by ceiling cameras…

@arXiv_csCE_bot@mastoxiv.page
2025-05-30 09:50:19

This arxiv.org/abs/2505.02093 has been replaced.
initial toot: mastoxiv.page/@arXiv_csCE_…

A Deep Learning-Aided Approach for Estimating Field Permeability Map by Fusing Well Logs, Well Tests, and Seismic Data
Obtaining reliable permeability maps of oil reservoirs is crucial for building a robust and accurate reservoir simulation model and, therefore, designing effective recovery strategies. This problem, however, remains challenging, as it requires the integration of various data sources by experts from different disciplines. Moreover, there are no sources to provide direct information about the inter-well space. In this work, a new method based on the data-fusion approach is proposed for predicting…

@arXiv_csET_bot@mastoxiv.page
2025-06-04 07:20:11

Process Mining on Distributed Data Sources
Maximilian Weisenseel, Julia Andersen, Samira Akili, Christian Imenkamp, Hendrik Reiter, Christoffer Rubensson, Wilhelm Hasselbring, Olaf Landsiedel, Xixi Lu, Jan Mendling, Florian Tschorsch, Matthias Weidlich, Agnes Koschmider
arxiv.org/abs/2506.02830

Process Mining on Distributed Data Sources
Major domains such as logistics, healthcare, and smart cities increasingly rely on sensor technologies and distributed infrastructures to monitor complex processes in real time. These developments are transforming the data landscape from discrete, structured records stored in centralized systems to continuous, fine-grained, and heterogeneous event streams collected across distributed environments. As a result, traditional process mining techniques, which assume centralized event logs from enter…

@arXiv_csDB_bot@mastoxiv.page
2025-05-29 07:16:59

Conformance Checking for Less: Efficient Conformance Checking for Long Event Sequences
Eli Bogdanov, Izack Cohen, Avigdor Gal
arxiv.org/abs/2505.21506

Conformance Checking for Less: Efficient Conformance Checking for Long Event Sequences
Long event sequences (termed traces) and large data logs that originate from sensors and prediction models are becoming increasingly common in our data-rich world. In such scenarios, conformance checking-validating a data log against an expected system behavior (the process model) can become computationally infeasible due to the exponential complexity of finding an optimal alignment. To alleviate scalability challenges for this task, we propose ConLES, a sliding-window conformance checking appr…

@arXiv_csMA_bot@mastoxiv.page
2025-06-03 16:11:13

This arxiv.org/abs/2505.00212 has been replaced.
initial toot: mastoxiv.page/@arXiv_csMA_…

Which Agent Causes Task Failures and When? On Automated Failure Attribution of LLM Multi-Agent Systems
Failure attribution in LLM multi-agent systems-identifying the agent and step responsible for task failures-provides crucial clues for systems debugging but remains underexplored and labor-intensive. In this paper, we propose and formulate a new research area: automated failure attribution for LLM multi-agent systems. To support this initiative, we introduce the Who&When dataset, comprising extensive failure logs from 127 LLM multi-agent systems with fine-grained annotations linking failures to…

@arXiv_csSE_bot@mastoxiv.page
2025-06-05 07:22:44

A Two-Staged LLM-Based Framework for CI/CD Failure Detection and Remediation with Industrial Validation
Weiyuan Xu, Juntao Luo, Tao Huang, Kaixin Sui, Jie Geng, Qijun Ma, Isami Akasaka, Xiaoxue Shi, Jing Tang, Peng Cai
arxiv.org/abs/2506.03691

A Two-Staged LLM-Based Framework for CI/CD Failure Detection and Remediation with Industrial Validation
Continuous Integration and Continuous Deployment (CI/CD) pipelines are pivotal to modern software engineering, yet diagnosing and resolving their failures remains a complex and labor-intensive challenge. In this paper, we present LogSage, the first end-to-end LLM-powered framework that performs root cause analysis and solution generation from failed CI/CD pipeline logs. During the root cause analysis stage, LogSage employs a specialized log preprocessing pipeline tailored for LLMs, which extrac…