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Found 7 papers, 2 papers with code
Towards Automatic Support of Software Model Evolution with Large Language~Models
We have found that large language models are indeed a promising technology for supporting software model evolution, and that it is worth investigating further in the area of software model evolution.
Feature Interactions on Steroids: On the Composition of ML Models
The lack of specifications is a key difference between traditional software engineering and machine learning.
A Decision Tree Lifted Domain for Analyzing Program Families with Numerical Features (Extended Version)
Lifted (family-based) static analysis by abstract interpretation is capable of analyzing all variants of a program family simultaneously, in a single run without generating any of the variants explicitly.
Programming Languages Logic in Computer Science Software Engineering
Predicting Performance of Software Configurations: There is no Silver Bullet
We have conducted a comparative study regarding the mean prediction accuracy when predicting the performance of all configurations considering 6 machine-learning techniques, 18 sampling strategies, and 6 subject software systems.
Finding Faster Configurations using FLASH
FLASH scales up to software systems that defeat the prior state of the art model-based methods in this area.
Software Engineering
Effectiveness of Anonymization in Double-Blind Review
Double-blind review relies on the authors' ability and willingness to effectively anonymize their submissions.
Digital Libraries General Literature Software Engineering
Faster Discovery of Faster System Configurations with Spectral Learning
Despite the huge spread and economical importance of configurable software systems, there is unsatisfactory support in utilizing the full potential of these systems with respect to finding performance-optimal configurations.
