Logic Programming Applications: What Are the Abstractions and Implementations?

This article presents an overview of applications of logic programming, classifying them based on the abstractions and implementations of logic languages that support the applications. The three key abstractions are join, recursion, and constraint. Their essential implementations are for-loops, fixed points, and backtracking, respectively. The corresponding kinds of applications are database queries, inductive analysis, and combinatorial search, respectively. We also discuss language extensions and programming paradigms, summarize example application problems by application areas, and touch on example systems that support variants of the abstractions with different implementations

Incremental Computation for Transformational Software Development

Given a program f and an input change \Phi, we wish to obtain an incremental program that computes f(x \Phi y) efficiently by making use of the value of f(x), the intermediate results computed in computing f(x), and auxiliary information about x that can be inexpensively maintained. Obtaining such incremental programs is an essential part of the transformational-programming approach to software development and enhancement. This paper presents a systematic approach that discovers a general class of useful auxiliary information, combines it with useful intermediate results, and obtains an efficient incremental program that uses and maintains these intermediate results and auxiliary information. We give a number of examples from list processing, VLSI circuit design, image processing, etc. 1 Introduction Software engineering is the systematic approach to the development, operation, maintenance, and retirement of software [1]. The transformational-programming approach to software engine..

High-level Cryptographic Abstractions

The interfaces exposed by commonly used cryptographic libraries are clumsy, complicated, and assume an understanding of cryptographic algorithms. The challenge is to design high-level abstractions that require minimum knowledge and effort to use while also allowing maximum control when needed. This paper proposes such high-level abstractions consisting of simple cryptographic primitives and full declarative configuration. These abstractions can be implemented on top of any cryptographic library in any language. We have implemented these abstractions in Python, and used them to write a wide variety of well-known security protocols, including Signal, Kerberos, and TLS. We show that programs using our abstractions are much smaller and easier to write than using low-level libraries, where size of security protocols implemented is reduced by about a third on average. We show our implementation incurs a small overhead, less than 5 microseconds for shared key operations and less than 341 microseconds (< 1%) for public key operations. We also show our abstractions are safe against main types of cryptographic misuse reported in the literature