Sophie Kaleba

Registered user since Sat 8 Aug 2020

Name:Sophie Kaleba
Country:United Kingdom
Affiliation:University of Kent
Research interests:Managed runtimes, dynamic languages, phase detection

Contributions

DLS 2022 Author of Who You Gonna Call: Analyzing the Run-time Call-Site Behavior of Ruby Applications within the DLS 2022-track
SPLASH 2022 In-person student volunteer in Organizers within the Student Volunteers-track
Truffle 2022 Author of Truffle Interpreter Performance without the Holy Graal within the Truffle 2022-track
‹Programming› 2022 Author of Capturing High-level Nondeterminism in Concurrent Programs for Practical Concurrency Model Agnostic Record & Replay within the Research Papers-track
Author of Less Is More: Merging AST Nodes To Optimize Interpreters (poster) within the Posters and Demonstrations-track
Author of Who You Gonna Call? A study of the call-site behaviour of Ruby-on-Rails applications (poster) within the Posters and Demonstrations-track
MoreVMs 2022 Author of Who You Gonna Call? A Case Study about the Call-Site Behaviour in Ruby-on-Rails Applications within the MoreVMs'22-track
Author of Less Is More: Merging AST Nodes To Optimize Interpreters within the MoreVMs'22-track
SPLASH 2021 Author of Avoiding Monomorphization Bottlenecks with Phase-Based Splitting within the Student Research Competition-track
Author of Avoiding Monomorphization Bottlenecks with Phase-based Splitting within the Doctoral Symposium-track
ICOOOLPS 2021 Presenter of Avoiding Monomorphisation Bottlenecks with Phase-based Splitting within the ICOOOLPS-track
MoreVMs 2021 Session Chair of Performance and Benchmarking (part of MoreVMs’21)
Committee Member in Program Committee within the MoreVMs’21-track
‹Programming› 2021 Author of Capturing High-level Nondeterminism in Concurrent Programs for Practical Concurrency Model Agnostic Record & Replay within the Research Papers-track
SPLASH 2020 Committee Member in Artifact Evaluation Committee within the OOPSLA Artifacts-track
ICOOOLPS 2018 Author of Assessing primitives performance on multi-stage execution within the ICOOOLPS-track