22 citations · 94 across the 19 of their papers we have counts for
22 papers
Observability and Fault Injection for LLM-Based Multi-Agent Systems in Software Engineering
Zahra Seyedghorban, Egor Klimov, Arie van Deursen +2
Large Language Model-based multi-agent systems are increasingly explored for software engineering tasks, but they remain difficult to inspect, debug, and evaluate under controlled…
Model See, Model Do? Exposure-Aware Evaluation of Bug-vs-Fix Preference in Code LLMs
Ali Al-Kaswan, Claudio Spiess, Prem Devanbu +2
Large language models are increasingly used for code generation and debugging, but their outputs can still contain bugs, that originate from training data. Distinguishing whether a…
Long Code Arena: a Set of Benchmarks for Long-Context Code Models
Egor Bogomolov, Aleksandra Eliseeva, Timur Galimzyanov +8
Nowadays, the fields of code and natural language processing are evolving rapidly. In particular, models become better at processing long context windows - supported context sizes…
CheckMate: Evaluating Checkpointing Protocols for Streaming Dataflows
George Siachamis, Kyriakos Psarakis, Marios Fragkoulis +3
Stream processing in the last decade has seen broad adoption in both commercial and research settings. One key element for this success is the ability of modern stream processors t…
Are Concept Drift Detectors Reliable Alarming Systems? -- A Comparative Study
Lorena Poenaru-Olaru, Luis Cruz, Arie van Deursen +1
As machine learning models increasingly replace traditional business logic in the production system, their lifecycle management is becoming a significant concern. Once deployed int…
Code Smells for Machine Learning Applications
Haiyin Zhang, Luís Cruz, Arie van Deursen
The popularity of machine learning has wildly expanded in recent years. Machine learning techniques have been heatedly studied in academia and applied in the industry to create bus…