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 44
Adopting InnerSource in a Public Sector Organization: A Case Study
InnerSource (IS) is increasingly viewed as a way to improve large-scale software development.Technical Report on the Turba Fertilizer Machine Learning Stack in Morocco
Site-specific fertilizer recommendation systems adapt nutrient advice to location, soil properties, crop type, and production targets, but scientific reuse is constrained when recommendation…Mechanizing the User's Eye: Pre-Registered Deployment of a Sabotage-Validated Fail-Plausible Observer in a Production LLM Agent Runtime
A prior longitudinal study of silent failures in a production LLM agent runtime (arXiv:2606.14589) found that about 70% were discovered by a human looking at the product as a user while thousands of…From Trust-by-Design to Continuous Trust in the Era of Artificial Intelligence
Trust is crucial in the digital world, particularly in the age of systems based on artificial intelligence.No More Translation at Runtime: LLM-Empowered Static Binary Translation
While AArch64 CPUs are becoming strong market contenders, their software ecosystem lags behind the mature x86-64 environment, hindering the adoption of the new architectures and impacting user…AgentSpy: Making AI Agent Behavior Observable
AI agents built on large language models (LLMs) run shell commands, read and write files, and reach the network, typically with their user's privileges.Experimentation Practices in Indie Game Startups
Small independent (indie) game startups face fierce competition when developing games with limited time, budget, and resources.Let the Agent Do It? How Software Practitioners Understand and Make Permission Decisions in Agentic AI Assistants
Agentic AI assistants increasingly act on developers' behalf by modifying files, executing commands, and accessing external resources.Backdooring Sparse Autoencoders
Sparse autoencoders (SAEs) are increasingly used not only to interpret language models but also to intervene on their internal representations.Where Does the Budget Go? Structural Concentration in Learning-Based Mutant Selection
Learning-based mutant selection is used to reduce the cost of mutation testing by ranking and selecting the mutants that seem to be the most promising.Security Is More Than a Library Call: How Security Features Live in Code
Implementing security features---functionalities that protect sensitive data or prevent malicious actions by attackers---is important for ensuring the security and integrity of software systems.When Equivalent Quantum Circuits Lose Synthesis Choices
Quantum compilers synthesize high-level operations, such as the quantum Fourier transform and multi-controlled X gates, into gate-level circuits.Where Did the Repair First Go Wrong? Localizing the Origins of Silent Failures in Agentic Vulnerability Repair
Localizing where an LLM-based agent first fails to uphold security during a repair can show which stage of its workflow needs an additional safeguard.Correct Code, Broken Contributions? SWE-CC: Benchmarking Repository Policy Compliance for Coding Agents
Autonomous coding agents now resolve a substantial share of real-world GitHub issues.LLM Non-Determinism in Deterministic Processes: A Controlled Variation Space for Constraining the Propagation of Non-Determinism
Large Language Models are increasingly used in software development processes that rely on defined states, rules, and approvals.Correct Verdicts, Flawed Reasoning: Structured Auditing of LLM-based Vulnerability Reasoning
Large Language Models (LLMs) are increasingly deployed for automated software vulnerability analysis.Choosing an energy-efficient software architecture for building system diagnostic support
Around 30\% of global energy expenditure can be attributed to the building sector, where a large portion of energy-consumption could be avoided by repairing existing faults.Hybrid Classical-Quantum Solutions to Accelerate the Adoption of Quantum Computing
Despite the promise and potential of quantum computing, most of the current day developments of quantum computing have several limitations for relevant practical use.SAFESHIELD: A Decision-Organization Framework for Deployment-Time Safety of Small Language Models
Deployment-time safety of language models is commonly implemented through runtime guardrails such as input moderation, routing, retrieval verification, and output filtering.Catching Developers in the Flow: Low-Latency Agentic Program Repair at Google Scale
Manual repair of program failures is time-consuming and disruptive for software developers, particularly during the pre-submit phase where test failures occur within continuous integration systems.