📝 New article: "Assisting early-stage software startups with LLMs: Effective prompt engineering and system instruction design" by Thea Lovise Ahlgren, Helene Fønstelien Sunde, Kai-Kristian Kemell, Anh Nguyen-Duc. 👉 Get your copy at

📝 New article: "Practitioners’ perceptions on requirements smells" by Emanuele Gentili, Davide Falessi. 👉 Get your copy at

Join millions who have switched to Grok.

💡 Findings: We proposed CtrlFuzz, a manifold coverage-guided controllable diffusion-based CGF tool to test deep neural networks. Experiments demonstrate that CtrlFuzz outperforms existing approaches in defect exposure with up to 91.5% of fault detection rate.

🤔 Motivation: Mutation-based CGF ensures test oracle through deliberately limited perturbations, but it struggles to obtain sparse and diverse test cases, while generation-based CGF lacks precise controllability in generating high-quality tests.

📜 Context: Deep neural networks have been extensively deployed in safety-critical applications. Nevertheless, the inherent vulnerability to subtle perturbations constitutes serious risks to DNN-based systems.

📝 New article: "CtrlFuzz: A Controllable Diffusion-based Fuzz Testing for Deep Neural Networks via Coverage-aware Manifold Guidance" by Aoshuang Ye, Shilin Zhang, Runze Yan, Jianpeng Ke, Fei Zhu, Benxiao Tang. 👉 Get your copy at

📝 New article: "Beyond Hard vs. Soft: A Mixed-Methods Approach to Developing a Competency Model for E-commerce Software Engineers" by Shuai Chen, Yang Zhao. 👉 Get your copy at

📝 New article: "DiffBCE: Difference Contrastive Learning for Binary Code Embeddings" by Yun Zhang, Ge Cheng. 👉 Get your copy at

@BifolcoDaniele @sabato_nocera @g_scanniello @mdipenta #softwareengineering #opensource #dependencygraph #github #sbom #empiricalstudy #java #python #miningsoftwarerepositories.

@BifolcoDaniele @sabato_nocera @g_scanniello @mdipenta 💡 Findings: We found that GitHub’s dependency graph contains a non-negligible percentage of incorrect dependencies and dependents. The study outlines root causes and provides actionable insights for researchers and practitioners.

@BifolcoDaniele @sabato_nocera @g_scanniello @mdipenta 🤔 Motivation: Despite being widely trusted, GitHub’s dependency graph may contain inaccuracies. This paper addresses a critical gap by assessing the reliability of this feature, which many tools and studies implicitly depend upon.

@BifolcoDaniele @sabato_nocera @g_scanniello @mdipenta 📜 Context: GitHub’s dependency graph is widely used in software engineering by tools like Dependabot and SBOM generator. However, its actual accuracy has not been systematically evaluated—until now.

📝 New article: "An Empirical Study on the Accuracy of GitHub's Dependency Graph and the Nature of Its Inaccuracy" by @BifolcoDaniele, Simone Romano, @sabato_nocera, Rita Francese, @g_scanniello, and @mdipenta . 👉 Get your copy at

📝 New article: "Gamification applied to Knowledge Sharing in Software Development: a Rapid Review" by Rodrigo Feitosa Gonçalves, Carlos Eduardo Barbosa, Matheus Argôlo, and Jano Moreira de Souza. 👉 Get your copy at

📝 New article: "Integrating energy consumption in the development of serverless applications" by Pablo Serrano-Gutierrez, Inmaculada Ayala, Lidia Fuentes. 👉 Get your copy at

📝 New article: "Heuristic-Based Incremental Local Domain Model Generation" by Manuel Quintela-Pumares, Daniel Fernández-Lanvin, Alberto-Manuel Fernandez-Alvarez. 👉 Get your copy at

📝 New article: "An Adaptive Model for Cross-domain Code Search" by Mengge Fang, Lie Wang, Haize Hu. 👉 Get your copy at

📝 New article: "Vulnerability Detection With Graph Attention Network And Metric Learning" by Chunyong Zhang, Liangwei Yao, Yang Xin. 👉 Get your copy at

📝 New article: "Neural-Guided Superoptimization in Ethereum" by Matheus Araújo Aguiar, Elvira Albert, Samir Genaim, Pablo Gordillo, Alejandro Hernández-Cerezo, Daniel Kirchner, Albert Rubio. 👉 Get your copy at

@merealone2516 #SoftwareEngineering #CommitMessageGeneration #CodeDiffAnalysis #MultiLevelCommitMessages.