Applied & Human-Centered · Computer Science & AI
Software Engineering
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1,466 papers, from 31 August 2026 to 5 November 2026: 1,451 arXiv preprints and 15 OpenAlex records.
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Newest papers, page 60
Developing a Unified Verification and Validation Activity Standard at JPL
Verification and validation practices (V&V) at NASA's Jet Propulsion Laboratory (JPL) have diverged over the past decade, creating fragmentation that increases overhead, reduces cross-project…CONCURDEP: Event-Guided Analysis of Dependency Invalidation in CPython Concurrency
Removing CPython's Global Interpreter Lock (GIL) exposes native code to concurrency absent from ordinary C types.Towards a Platform for Mastering Personal Sovereignty
The ongoing digital transformation of work, administration, health, mobility, and social interaction is profoundly reshaping everyday life, steadily shifting control from individuals to large…Soundness Checking of Taint Flow Models
Existing state-of-the-art static taint flow analyses for imperative programming languages can scale to large applications by using precise user-provided taint flow models of library methods.Category-Based MLM: Unifying Powertypes with Superclasses
MultiLevel software Modeling (MLM) suggests that conceptual modeling in broad subject domains might require abstraction of multiple classification levels.Pack Iteration in Swift: Ordinary Control Flow for Variadic Generics
Variadic generics are a powerful tool for type-safe meta-programming.RECLAIM: Can Agents Reproduce the Claims of Machine Learning Papers?
Reproducing a machine learning paper involves most research steps, from installing software and debugging to running experiments, work that AI agents increasingly do.Distributed Service Orchestration in Edge-Cloud Continuum for Digital Healthcare
Today's digital healthcare services rely on various applications and functions that must be continuously accessible.Silent Success: A Release Gate That Passed on Checks It Never Ran, and Eight More
A blocking quality gate in a production release pipeline reported PASS on a run in which one subgate had executed neither of its two checks and another had run six of its eight.Empty Intersection: Provenance Coverage Rose to 98% and Neither Verification Decision Moved
Two structural defenses for provenance, a grade on every row, so that a verification routine cannot mistake the system's own output for an observation, and a single write ingress, so that the grade…HyQDB: LLM-Assisted Debugging for Hybrid Quantum Workflows
Hybrid quantum program failures frequently occur silently, yet existing debugging tools provide limited support for detecting and repairing them.Proceedings Tenth Symposium on Working Formal Methods
The 10th Working Formal Methods Symposium (FROM 2026) was held in Timişoara, Romania on September 15-17, 2026.When Is a Multi-Agent Code Judge Actually Grounded? Two Label-Free Measurements, and a Judge That Declines to Guess
When one language model judges whether another's code is correct, it does not report the absence of evidence.The Vocabulary of Flaky Tests in Swift
Flaky tests produce non-deterministic outcomes without code change, eroding CI confidence and delaying deliveries.Dynamic Conformance Testing of WebGPU Through Specification-Driven Mutation
WebGPU is a low-level graphics and compute API that exposes modern GPU functionality to web applications.Evaluating Shaker for Flaky Test Detection in Python Projects
Flaky tests pass or fail non-deterministically on unchanged code, eroding trust in test suites and inflating the cost of every failure.An Empirical Analysis of Cross-OS Portability Issues in Python Projects
While Python is designed as a cross-platform language, real-world applications encounter portability failures when deployed across different operating systems.Understanding Maintenance and Support in a Community-Driven Scientific Workflow Ecosystem: A Cross-Space Study of Galaxy
Galaxy is a widely used, community-driven scientific workflow system whose sustainability depends on continuous maintenance across its software, tools, workflows, infrastructure, documentation, and…Testing and Learning Symbolic Finite State Machines
Symbolic finite state machines (SFSMs) describe input/output behaviour using guards and output assignments with possibly infinite data domains.What Was Once Learned May Need to Be Unlearned: Machine Unlearning for Deprecated API Knowledge in Large Language Models
Large language models (LLMs) for code completion may generate deprecated APIs because their pre-training corpora contain code from historical library versions.