Initial thoughts on rapid prototyping techniques

This paper sets some context, raises issues, and provides our initial thinking on the characteristics of effective rapid prototyping techniques.After discussing the role rapid prototyping techniques can play in the software lifecycle, the paper looks at possible technical approaches including: heavily parameterized models, reusable software, rapid prototyping languages, prefabrication techniques for system generation, and reconfigurable test harnesses.The paper concludes that a multi-faceted approach to rapid prototyping techniques is needed if we are to address a broad range of applications successfully -- no single technical approach suffices for all potentially desirable applications

DeepSaucer: Unified Environment for Verifying Deep Neural Networks

In recent years, a number of methods for verifying DNNs have been developed. Because the approaches of the methods differ and have their own limitations, we think that a number of verification methods should be applied to a developed DNN. To apply a number of methods to the DNN, it is necessary to translate either the implementation of the DNN or the verification method so that one runs in the same environment as the other. Since those translations are time-consuming, a utility tool, named DeepSaucer, which helps to retain and reuse implementations of DNNs, verification methods, and their environments, is proposed. In DeepSaucer, code snippets of loading DNNs, running verification methods, and creating their environments are retained and reused as software assets in order to reduce cost of verifying DNNs. The feasibility of DeepSaucer is confirmed by implementing it on the basis of Anaconda, which provides virtual environment for loading a DNN and running a verification method. In addition, the effectiveness of DeepSaucer is demonstrated by usecase examples