collaborators

5 papers

cs.SE2026

Mitigating Errors in LLM-Generated Web API Invocations via Retrieval-Augmented Generation and Constrained Decoding

Daniel Maninger, Leon Chemnitz, Jannis Brugger +3

Integration of web APIs is a cornerstone of modern software systems, yet writing correct web API invocation code remains challenging due to complex and evolving API specifications.…

cs.SE2026

Benchmarking Web API Integration Code Generation

Daniel Maninger, Leon Chemnitz, Amir Molzam Sharifloo +2

API integration is a cornerstone of our digital infrastructure, enabling software systems to connect and interact. However, as shown by many studies, writing or generating correct…

cs.PL2026

Beyond BLEU: A Semantic Evaluation Method for Code Translation

Julius Näumann, Sven Keidel, Amir Molzam Sharifloo +1

Code translation is one of the core capabilities of LLMs. However, evaluating the correctness of translations remains difficult, as commonly used metrics such as BLEU measure only…

cs.SE2026

Deep Graph-Language Fusion for Structure-Aware Code Generation

Mert Tiftikci, Amir Molzam Sharifloo, Mira Mezini

Pre-trained Language Models (PLMs) have the potential to transform software development tasks. However, despite significant advances, current PLMs struggle to capture the structure…

cs.SE2025

Where Do LLMs Still Struggle? An In-Depth Analysis of Code Generation Benchmarks

Amir Molzam Sharifloo, Maedeh Heydari, Parsa Kazerooni +2

Large Language Models (LLMs) have achieved remarkable success in code generation, and the race to improve their performance has become a central focus of AI research. Benchmarks an…