Unicorn: Reasoning about configurable system performance through the lens of causality
Modern computer systems are highly configurable, with the total variability space sometimes
larger than the number of atoms in the universe. Understanding and reasoning about the …
larger than the number of atoms in the universe. Understanding and reasoning about the …
Diagconfig: Configuration diagnosis of performance violations in configurable software systems
Performance degradation due to misconfiguration in software systems that violates SLOs
(service-level objectives) is commonplace. Diagnosing and explaining the root causes of …
(service-level objectives) is commonplace. Diagnosing and explaining the root causes of …
Effective performance issue diagnosis with value-assisted cost profiling
Diagnosing performance issues is often difficult, especially when they occur only during
some program executions. Profilers can help with performance debugging, but are …
some program executions. Profilers can help with performance debugging, but are …
ROCAS: Root Cause Analysis of Autonomous Driving Accidents via Cyber-Physical Co-mutation
As Autonomous driving systems (ADS) have transformed our daily life, safety of ADS is of
growing significance. While various testing approaches have emerged to enhance the ADS …
growing significance. While various testing approaches have emerged to enhance the ADS …
CAMEO: A Causal Transfer Learning Approach for Performance Optimization of Configurable Computer Systems
Modern computer systems are highly configurable, with hundreds of configuration options
that interact, resulting in an enormous configuration space. As a result, optimizing …
that interact, resulting in an enormous configuration space. As a result, optimizing …
Visualizing memory consumption with vismep
Detecting and repairing memory issues is still a challenging task. One reason is that
understanding a program's memory usage involves a diverse and related set of dynamic …
understanding a program's memory usage involves a diverse and related set of dynamic …
Towards Understanding the Challenges of Bug Localization in Deep Learning Systems
Software bugs cost the global economy billions of dollars annually and claim~ 50\% of the
programming time from software developers. Locating these bugs is crucial for their …
programming time from software developers. Locating these bugs is crucial for their …
Characterizing the Complexity and Its Impact on Testing in ML-Enabled Systems: A Case Sutdy on Rasa
Machine learning (ML) enabled systems are emerging with recent breakthroughs in ML. A
model-centric view is widely taken by the literature to focus only on the analysis of ML …
model-centric view is widely taken by the literature to focus only on the analysis of ML …
Identifying Performance-Sensitive Configurations in Software Systems through Code Analysis with LLM Agents
Configuration settings are essential for tailoring software behavior to meet specific
performance requirements. However, incorrect configurations are widespread, and …
performance requirements. However, incorrect configurations are widespread, and …
Understanding the Complexity and Its Impact on Testing in ML-Enabled Systems
Machine learning (ML) enabled systems are emerging with recent breakthroughs in ML. A
model-centric view is widely taken by the literature to focus only on the analysis of ML …
model-centric view is widely taken by the literature to focus only on the analysis of ML …