arXiv subjects

Costain Nachuma

Publications and source records attributed to Costain Nachuma.

3 recordsLinked to original sources

arXiv2026

Comprendia: AI-Augmented Code Comprehension

Comprendia is an Eclipse plugin that integrates structural dependency visualization with LLM-powered code explanation on a shared interactive graph for Java program comprehension. The tool rests on four pillars: (1) a multi-edge-type dependency graph with live search and multiple layouts; (2) LLM explanations grounded in Graph-Aware Callee Pruning (GACP), an auditable strategy that selects relevant callees using the same graph the developer navigates; (3) a clone-detection overlay that highlights duplication and suggests extract-to-parent refactoring opportunities; and (4) a CVE risk overlay powered by OSV.dev. GACP uses graph distance, inheritance collapse, and edge-type weighting to produce prompts that are reproducible across LLM families and traceable to visible graph nodes. We demonstrate Comprendia on a Java project containing known clones and vulnerabilities, showing how the unified graph substrate supports comprehension while keeping the developer in control. Screencast: https://youtu.be/1wlh_RYehzA

cs.SE↗

arXiv2026

When AI Teammates Meet Code Review: Collaboration Signals Shaping the Integration of Agent-Authored Pull Requests

Autonomous coding agents increasingly contribute to software development by submitting pull requests on GitHub; yet, little is known about how these contributions integrate into human-driven review workflows. We present a large empirical study of agent-authored pull requests using the public AIDev dataset, examining integration outcomes, resolution speed, and review-time collaboration signals. Using logistic regression with repository-clustered standard errors, we find that reviewer engagement has the strongest correlation with successful integration, whereas larger change sizes and coordination-disrupting actions, such as force pushes, are associated with a lower likelihood of merging. In contrast, iteration intensity alone provides limited explanatory power once collaboration signals are considered. A qualitative analysis further shows that successful integration occurs when agents engage in actionable review loops that converge toward reviewer expectations. Overall, our results highlight that the effective integration of agent-authored pull requests depends not only on code quality but also on alignment with established review and coordination practices.

cs.SE↗

arXiv2025

Decoding Dependency Risks: A Quantitative Study of Vulnerabilities in the Maven Ecosystem

This study investigates vulnerabilities within the Maven ecosystem by analyzing a comprehensive dataset of 14,459,139 releases. Our analysis reveals the most critical weaknesses that pose significant threats to developers and their projects as they look to streamline their development tasks through code reuse. We show risky weaknesses, those unique to Maven, and emphasize those becoming increasingly dangerous over time. Furthermore, we reveal how vulnerabilities subtly propagate, impacting 31.39% of the 635,003 latest releases through direct dependencies and 62.89% through transitive dependencies. Our findings suggest that improper handling of input and mismanagement of resources pose the most risk. Additionally, Insufficient session-ID length in J2EE configuration and no throttling while allocating resources uniquely threaten the Maven ecosystem. We also find that weaknesses related to improper authentication and managing sensitive data without encryption have quickly gained prominence in recent years. These findings emphasize the need for proactive strategies to mitigate security risks in the Maven ecosystem.

cs.SE↗