Performance models are well-known instruments to understand the scaling behavior of
parallel applications. They express how performance changes as key execution parameters …

Traditional means of gathering performance data are tracing, which is limited by the
available storage, and profiling, which has limited accuracy. Performance modeling is often …

Measurement-based profiling introduces intrusion in program execution. Intrusion effects
can be mitigated by compensating for measurement overhead. Techniques for …

We present Mantis, a new framework that automatically predicts program performance with
high accuracy. Mantis integrates techniques from programming language and machine …

Many parallel applications suffer from latent performance limitations that may prevent them
from scaling to larger machine sizes or solving larger problems. Often, such performance …

Static analysis is a powerful tool for detecting security vulnerabilities and other programming
problems. Global taint tracking, in particular, can spot vulnerabilities arising from …

There is a constant need throughout the life cycle of a parallel program for analyzing, tuning,
and predicting its performance. These tasks all require that the programmer understand the …

Despite the amount of proposed works for the verification of embedded systems,
understanding the root cause of violations of requirements in simulation or execution traces …

Understanding the performance of large, complex enterprise-class applications is an
important, yet nontrivial task. Methods using hardware performance counters, such as …

Taint analysis has a wide variety of compelling applications in security tasks, from software
attack detection to data lifetime analysis. Static taint analysis propagates taint values …