Unifying execution of imperative and declarative code

Milićević, Aleksandar; Rayside, Derek; Yessenov, Kuat; Jackson, Daniel

doi:10.1145/1985793.1985863

Cited by 44 publications

(30 citation statements)

References 18 publications

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“…In comparison, our Python API seems more lightweight, since it does not require an object-oriented approach. When it comes to computational performance, [12] reports good results, which our implementation is not able to match.…”

Section: Related Workmentioning

confidence: 85%

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Lowering the Learning Curve for Declarative Programming: A Python API for the IDP System

Vennekens

2016

Practical Aspects of Declarative Languages

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Abstract. Programmers may be hesitant to use declarative systems, because of the associated learning curve. In this paper, we present an API that integrates the IDP Knowledge Base system into the Python programming language. IDP is a state-of-the-art logical system, which uses SAT, SMT, Logic Programming and Answer Set Programming technology. Python is currently one of the most widely used (teaching) languages for programming. The first goal of our API is to allow a Python programmer to use the declarative power of IDP, without needing to learn any new syntax or semantics. The second goal is allow IDP to be added to/removed from an existing code base with minimal changes.

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Section: Related Workmentioning

confidence: 85%

“…In [12], a reasoner for FO extended with transitive closure is integrated into Java. Their KB language is therefore very similar to (but more restricted than) that of IDP.…”

Section: Related Workmentioning

confidence: 99%

Lowering the Learning Curve for Declarative Programming: A Python API for the IDP System

Vennekens

2016

Practical Aspects of Declarative Languages

View full text Add to dashboard Cite

show abstract

“…In this case, declarative specifications are executed 'by magic', as if, in a conventional setting, the interpreter could execute a program assertion by making it true despite the lack of any explicit code to establish it [10,9]. Alternatively, flipping the precedence of the two paradigms, the interpreter can be viewed as a declarative model finder that uses imperative code to setup a declarative specification to be solved.…”

Section: Motivationsmentioning

confidence: 99%

αRby—An Embedding of Alloy in Ruby

Milićević

Efrati

Jackson

2014

Lecture Notes in Computer Science

Self Cite

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Abstract. We present αRby-an embedding of the Alloy language in Rubyand demonstrate the benefits of having a declarative modeling language (backed by an automated solver) embedded in a traditional object-oriented imperative programming language. This approach aims to bring these two distinct paradigms (imperative and declarative) together in a novel way. We argue that having the other paradigm available within the same language is beneficial to both the modeling community of Alloy users and the object-oriented community of Ruby programmers. In this paper, we primarily focus on the benefits for the Alloy community, namely, how αRby provides elegant solutions to several well-known, outstanding problems: (1) mixed execution, (2) specifying partial instances, (3) staged model finding.

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“…In Jeeves, the logical environment is always consistent and the runtime only performs decidable search routines. Jeeves differs from the Squander system [31] for unified execution of imperative and declarative code in that Jeeves propagates constraints alongside the core program rather than executing isolated constraint-based subprocedures. As with relaxed approximate programs [11], Jeeves nondeterministically provides an acceptable output for a specific class of acceptability properties.…”

Section: Related Workmentioning

confidence: 99%

Faceted execution of policy-agnostic programs

Austin

Yang

Flanagan

et al. 2013

Proceedings of the Eighth ACM SIGPLAN Workshop on Programming Languages and Analysis for Security

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It is important for applications to protect sensitive data. Even for simple confidentiality and integrity policies, it is often difficult for programmers to reason about how the policies should interact and how to enforce policies across the program. A promising approach is policy-agnostic programming, a model that allows the programmer to implement policies separately from core functionality. Yang et al. describe Jeeves [48], a programming language that supports information flow policies describing how to reveal sensitive values in different output channels. Jeeves uses symbolic evaluation and constraint-solving to produce outputs adhering to the policies. This strategy provides strong confidentiality guarantees but limits expressiveness and implementation feasibility.We extend Jeeves with faceted values [6], which exploit the structure of sensitive values to yield both greater expressiveness and to facilitate reasoning about runtime behavior. We present a faceted semantics for Jeeves and describe a model for propagating multiple views of sensitive information through a program. We provide a proof of termination-insensitive non-interference and describe how the semantics facilitate reasoning about program behavior.

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Unifying execution of imperative and declarative code

Cited by 44 publications

References 18 publications

Lowering the Learning Curve for Declarative Programming: A Python API for the IDP System

Lowering the Learning Curve for Declarative Programming: A Python API for the IDP System

αRby—An Embedding of Alloy in Ruby

Faceted execution of policy-agnostic programs

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