Delta debugging (DD) is an approach to automating the debugging activities based on systematic testing. DD algorithms find the cause of a regression of a program by minimizing the changes applied between a working version and a faulty version of the program. However, it is still an open problem to minimize a huge set of changes while avoiding any invalid subsets that do not result in testable programs, especially in case that no software configuration management system is available. Continue reading →

The process of performance tuning is time consuming and costly even if it is carried out automatically. It is crucial to learn from the experience of experts. Our long-term goal is to construct a database of facts extracted from specific performance tuning histories of computation-intensive applications such that we can search the database for promising optimization patterns that fit a given kernel. Continue reading →

To improve performance of large-scale scientific applications, scientists or tuning experts make various empirical attempts to change compiler options, program parameters or even the syntactic structure of programs. Those attempts followed by performance evaluation are repeated until satisfactory results are obtained. On account of combinatorial explosion of possible attempts, the task of performance tuning requires a great deal of time and effort, and hence scientists/tuning experts have a tendency to make decisions on what to be explored just based on their intuition or good sense of tuning. Continue reading →