Detecting Flow of Sensitive Data in Mini-Programs with Static Taint Analysis
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Updated
Mar 19, 2024 - Python
Detecting Flow of Sensitive Data in Mini-Programs with Static Taint Analysis
An Empirical Study of Date and Time Bugs in Open-Source Python Software.
Lecture
Quantifying prompt quality using information theory: entropy and mutual information analysis of 1,800 LLM generations
An analysis framework for characterizing test scope, fixtures, assertions, inputs, and mocking patterns in tests.
Observational dataset of 200 B2B AI deployments in France (2022-2025). Median annual gain of 1.60x investment (159.8%) across 165 deployments in production; 1.27x across the full cohort. Self-published, not peer-reviewed, no independent audit. Reproduction script included. CC BY 4.0.
📡 Visualize and understand amateur radio antenna patterns and physics through an interactive 3D platform designed for Ham Radio enthusiasts.
An empirical study of bug-fixing patterns in open-source Python repositories.
An empirical study evaluating the correctness of LLM-generated Python code for introductory programming tasks.
Machine learning framework for detecting flaky tests and improving CI/CD pipeline reliability.
This repository contains the LaTeX source code and additional resources for a research paper that was accepted for publication at the 2021 Mining Software Repositories Conference.
Empirical study on correlation vs. computational hardness in SAT solving
Replication package for "Do LLMs Generate Adequate REST API Tests?" — ASE 2026 NIER
Replication package for "Who Tests Better When They Built It?" — ICSE 2027 NIER (under review)
Estudo empírico que avalia a assertividade lógica, desempenho (tempo/memória) e qualidade estrutural (Complexidade Ciclomática e Cognitiva) de código PHP gerado via Zero-Shot Prompting por Claude Sonnet 5, Gemini 3.5 Flash e GPT-5.5 Instant, usando 20 problemas do LeetCode.
📊 Explore how Shannon entropy and mutual information can quantify prompt quality in generative AI systems across various temperature settings.
对 Karpathy「不要问 LLM 你怎么想」建议的实证批评。2天单人实验证明:Karpathy 说对了机制原文,但说错了使用建议。附量化测量框架和可复现方法。
Empirical study of linear, exact-kernel, and approximate-kernel classifiers on nonlinear binary classification tasks.
In the volatile telecommunications sector of Pakistan, projects often face extreme pressures. This study explores how Project Internal Social Capital (PISC)—the relational and cognitive bonds within a team—allows individuals to maintain performance. The study demonstrates that this is not a simple direct link, but a complex serial mediation.
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