A case study in preserving a high energy physics application with Parrot

The reproducibility of scientific results increasingly depends upon the preservation of computational artifacts. Although preserving a computation to be used later sounds easy, it is surprisingly difficult due to the complexity of existing software and systems. Implicit dependencies, networked resources, and shifting compatibility all conspire to break applications that appear to work well. To investigate these issues, we present a case study of a complex high energy physics application. We analyze the application and attempt several methods at extracting its dependencies for the purposes of preservation. We propose one fine-grained dependency management toolkit to preserve the application and demonstrate its correctness in three different environments the original machine, one virtual machine from the Notre Dame Cloud Platform and one virtual machine from the Amazon EC2 Platform. We report on the completeness, performance, and efficiency of each technique, and offer some guidance for future work in application preservation.