61,993 research outputs found
A Quantitative Study of Java Software Buildability
Researchers, students and practitioners often encounter a situation when the
build process of a third-party software system fails. In this paper, we aim to
confirm this observation present mainly as anecdotal evidence so far. Using a
virtual environment simulating a programmer's one, we try to fully
automatically build target archives from the source code of over 7,200 open
source Java projects. We found that more than 38% of builds ended in failure.
Build log analysis reveals the largest portion of errors are
dependency-related. We also conduct an association study of factors affecting
build success
The use of data-mining for the automatic formation of tactics
This paper discusses the usse of data-mining for the automatic formation of tactics. It was presented at the Workshop on Computer-Supported Mathematical Theory Development held at IJCAR in 2004. The aim of this project is to evaluate the applicability of data-mining techniques to the automatic formation of tactics from large corpuses of proofs. We data-mine information from large proof corpuses to find commonly occurring patterns. These patterns are then evolved into tactics using genetic programming techniques
An automated workflow for parallel processing of large multiview SPIM recordings
Multiview light sheet fluorescence microscopy (LSFM) allows to image
developing organisms in 3D at unprecedented temporal resolution over long
periods of time. The resulting massive amounts of raw image data requires
extensive processing interactively via dedicated graphical user interface (GUI)
applications. The consecutive processing steps can be easily automated and the
individual time points can be processed independently, which lends itself to
trivial parallelization on a high performance cluster (HPC). Here we introduce
an automated workflow for processing large multiview, multi-channel,
multi-illumination time-lapse LSFM data on a single workstation or in parallel
on a HPC. The pipeline relies on snakemake to resolve dependencies among
consecutive processing steps and can be easily adapted to any cluster
environment for processing LSFM data in a fraction of the time required to
collect it.Comment: 13 pages with supplement, LATEX; 1 table, 1 figure, 2 supplementary
figures, 2 supplementary lists, 2 supplementary tables; corrected error in
results table, results unchange
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