Abstract The rapid progress of quantum technologies, fostered by the efforts of both academia and industry, has stimulated the design of quantum programming languages and the development of methods to support their verification and optimization. As in the classical setting, static analysis plays a fundamental role in such an endeavour. In this paper, we provide a survey on static analysis approaches for quantum programs, which have been proposed in the literature, distinguishing between dataflow-oriented approaches, which are based on a graph representation of the program information flow, and domain-oriented approaches, which essentially consist of the definition of some appropriate abstract domains representing the program property to be analysed. To illustrate these two perspectives concretely, we also present in detail two specific analyses: a dataflow analysis for managing quantum variables and uncomputation, and a static analysis based on abstract interpretation for detecting state entanglement.

There is a growing attention, in the research communities of political economics, onto the potential of text analytics in classifying documents with economic content. This interest extends the data analytics approach that has been the traditional base for economic theory with scientific perspective. To devise a general method for prediction applicability, we identify some phases of a methodology and perform tests on a large well-structured repository of resource contracts containing documents related to resources. The majority of these contracts involve mining resources. In this paper we prove that, by the usage of text analytics measures, we can cluster these documents on three indicators: fairness of the contract content, transparency of the document themselves, and applicability of the clauses of the contract intended to guarantee execution on an international basis. We achieve these results, consistent with a gold-standard test obtained with human experts, using text similarity b (More)