Fully-Homomorphic Encryption (FHE) offers powerful capabilities by enabling secure offloading of both storage and computation, and recent innovations in schemes and implementation have made it all the more attractive. At the same time, FHE is notoriously hard to use with a very constrained programming model, a very unusual performance profile, and many cryptographic constraints. Existing compilers for FHE either target simpler but less efficient FHE schemes or only support specific domains where they can rely on expert provided high-level runtimes to hide complications.This paper presents a new FHE language called Encrypted Vector Arithmetic (EVA), which includes an optimizing compiler that generates correct and secure FHE programs, while hiding all the complexities of the target FHE scheme. Bolstered by our optimizing compiler, programmers can develop efficient general purpose FHE applications directly in EVA. For example, we have developed image processing applications using EVA, with very few lines of code.EVA is designed to also work as an intermediate representation that can be a target for compiling higher-level domainspecific languages. To demonstrate this we have re-targeted CHET, an existing domain-specific compiler for neural network inference, onto EVA. Due to the novel optimizations in EVA, its programs are on average 5.3× faster than those generated by CHET. We believe EVA would enable a wider adoption of FHE by making it easier to develop FHE applications and domain-specific FHE compilers.

In the last few decades, several value-modeling methods have emerged in requirements engineering for IS research. We compare two value-modeling methods, e 3 value and SEAM. We illustrate their use with an example of the exchange of the Intellectual Property Rights (IPR) on music. In the process, we propose a comparison framework. The results of our study show that e 3 value and SEAM are similar valuemodeling techniques: both model services in networked systems and focus on value exchanges. They differ, however, in the way value is conceptualized: the market viability of the service system in e 3 value versus the subjective value and lack of market profitability analysis in SEAM. e 3 value shows how value flows from one actor to another, whereas SEAM shows the relative importance of different value propositions and how they are constructed by the service network. These results can be used by modelers to select a value-modeling method for their purposes by proposing explicit selection criteria. The comparison framework, which is in its early stages of development, can be used to compare other modeling methods.

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