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A really interesting paper about comparison between AST based tree walking interpreters and byte code interpreters: Larose, Kaleba, Burchell and Marr AST vs. Bytecode: Interpreters in the Age of Meta-Compilation at OOPSLA'23. They compared Python and Smalltalk interpreters with tree walking and bytecode based implementation. Their finding is that AST interpreters using meta compilation (RPython and Truffle+Graal) were faster than byte code counterparts even after applying all relevant optimizations possible for bytecodes.
This is a very interesting result because AST tree walkers are much more easier to construct and to teach (personal experience). #SE @seresearchers
An interesting paper on using #LLM for automated code repair from Wei et al. https://arxiv.org/abs/2309.00608 #SE
Here (https://arxiv.org/pdf/2308.15276.pdf) is an excellent paper by Wu et al. about using LLMs for fault localization. It seems that LLMs are better at fault localization than SBFL techniques Jaccard, Tarantula, Ochiai, OP2, Dstar, MBFL and SmartFL by about 50%. #LLM #SE
An interesting paper on the usage of #LLM in #SE by Hou et al. -- "Large Language Models for Software Engineering: A Systematic Literature Review" https://arxiv.org/abs/2308.10620
LLMs can be transformative in software engineering, and this paper does a good job in reviewing the state-of-the-art.