scholarly journals Type Safe Metadata Combining

2017 ◽  
Vol 10 (2) ◽  
pp. 97
Author(s):  
Mikus Vanags ◽  
Rudite Cevere
Keyword(s):  
Programming Languages ◽  
Programming Language ◽  
Type System ◽  
Data Abstraction ◽  
Class Member ◽  
Database Querying ◽  
Type Safety ◽  
Abstraction Layer ◽  
Information Type ◽  
Type Information

Type safety is an important property of any type system. Modern programming languages support different mechanisms to work in type safe manner, e.g., properties, methods, events, attributes (annotations) and other structures. Some programming languages allow access to metadata: type information, type member information and information about applied attributes. But none of the existing mainstream programming languages which support reflection provides fully type safe metadata combining mechanism built in the programming language. Combining of metadata means a class member metadata combining with data, type metadata and constraints. Existing solutions provide no or limited type safe metadata combining mechanism; they are complex and processed at runtime, which by definition is not built-in type-safe metadata combining. Problem can be solved by introducing syntax and methods for type safe metadata combining so that, metadata could be processed at compile time in a fully type safe way. Common metadata combining use cases are data abstraction layer creation and database querying.

scholarly journals Localized Lama Gradual Typing

2021 ◽  
Vol 33 (3) ◽  
pp. 61-76
Author(s):  
Viktor Sergeevich Kryshtapovich
Keyword(s):  
Programming Language ◽  
Type System ◽  
Scientific Research ◽  
Type Systems ◽  
Modern Approach ◽  
Type Safety ◽  
Current Implementation ◽  
Gradual Typing ◽  
Dynamic Typing ◽  
Static Typing

Gradual typing is a modern approach for combining benefits of static typing and dynamic typing. Although scientific research aim for soundness of type systems, many of languages intentionally make their type system unsound for speeding up performance. This paper describes an implementation of a dialect for Lama programming language that supports gradual typing with explicit annotation of dangerous parts of code. The target of current implementation is to grant type safety to programs while keeping their power of untyped expressiveness. This paper covers implementation issues and properties of created type system. Finally, some perspectives on improving precision and soundness of type system are discussed.

scholarly journals Implementing type theory in higher order constraint logic programming

2019 ◽  
Vol 29 (8) ◽  
pp. 1125-1150
Author(s):  
FERRUCCIO GUIDI ◽  
CLAUDIO SACERDOTI COEN ◽  
ENRICO TASSI
Keyword(s):  
Programming Languages ◽  
Programming Language ◽  
Type System ◽  
Theorem Prover ◽  
Type Checking ◽  
Language Extension ◽  
Order Constraint ◽  
Simple Implementation ◽  
Calculus Of Inductive Constructions ◽  
High Level

In this paper, we are interested in high-level programming languages to implement the core components of an interactive theorem prover for a dependently typed language: the kernel – responsible for type-checking closed terms – and the elaborator – that manipulates open terms, that is terms containing unresolved unification variables.In this paper, we confirm that λProlog, the language developed by Miller and Nadathur since the 80s, is extremely suitable for implementing the kernel. Indeed, we easily obtain a type checker for the Calculus of Inductive Constructions (CIC). Even more, we do so in an incremental way by escalating a checker for a pure type system to the full CIC.We then turn our attention to the elaborator with the objective to obtain a simple implementation thanks to the features of the programming language. In particular, we want to use λProlog’s unification variables to model the object language ones. In this way, scope checking, carrying of assignments and occur checking are handled by the programming language.We observe that the eager generative semantics inherited from Prolog clashes with this plan. We propose an extension to λProlog that allows to control the generative semantics, suspend goals over flexible terms turning them into constraints, and finally manipulate these constraints at the meta-meta level via constraint handling rules.We implement the proposed language extension in the Embedded Lambda Prolog Interpreter system and we discuss how it can be used to extend the kernel into an elaborator for CIC.

A paradigmatic object-oriented programming language: Design, static typing and semantics

1994 ◽  
Vol 4 (2) ◽  
pp. 127-206 ◽  
Author(s):  
Kim B. Bruce
Keyword(s):  
Fixed Points ◽  
Programming Languages ◽  
Programming Language ◽  
Type System ◽  
Object Oriented ◽  
Object Oriented Programming ◽  
Language Design ◽  
Type Checking ◽  
Basic Features ◽  
Oriented Programming Language

AbstractTo illuminate the fundamental concepts involved in object-oriented programming languages, we describe the design of TOOPL, a paradigmatic, statically-typed, functional, object-oriented programming language which supports classes, objects, methods, hidden instance variables, subtypes and inheritance.It has proven to be quite difficult to design such a language which has a secure type system. A particular problem with statically type checking object-oriented languages is designing typechecking rules which ensure that methods provided in a superclass will continue to be type correct when inherited in a subclass. The type-checking rules for TOOPL have this feature, enabling library suppliers to provide only the interfaces of classes with actual executable code, while still allowing users to safely create subclasses. To achieve greater expressibility while retaining type-safety, we choose to separate the inheritance and subtyping hierarchy in the language.The design of TOOPL has been guided by an analysis of the semantics of the language, which is given in terms of a model of the F-bounded second-order lambda calculus with fixed points at both the element and type level. This semantics supports the language design by providing a means to prove that the type-checking rules are sound, thus guaranteeing that the language is type-safe.While the semantics of our language is rather complex, involving fixed points at both the element and type level, we believe that this reflects the inherent complexity of the basic features of object-oriented programming languages. Particularly complex features include the implicit recursion inherent in the use of the keyword, self, to refer to the current object, and its corresponding type, MyType. The notions of subclass and inheritance introduce the greatest semantic complexities, whereas the notion of subtype is more straightforward to deal with. Our semantic investigations lead us to recommend caution in the use of inheritance, since small changes to method definitions in subclasses can result in major changes to the meanings of the other methods of the class.

scholarly journals Lolisa: Formal Syntax and Semantics for a Subset of the Solidity Programming Language in Mathematical Tool Coq

2020 ◽  
Vol 2020 ◽  
pp. 1-15
Author(s):  
Zheng Yang ◽  
Hang Lei
Keyword(s):  
Programming Languages ◽  
Programming Language ◽  
Type System ◽  
General Purpose ◽  
Mathematical Tool ◽  
Smart Contracts ◽  
Large Subset ◽  
Formal Syntax ◽  
Emerging Issues ◽  
Line Correspondence

The security of blockchain smart contracts is one of the most emerging issues of the greatest interest for researchers. This article presents an intermediate specification language for the formal verification of Ethereum-based smart contract in Coq, denoted as Lolisa. The formal syntax and semantics of Lolisa contain a large subset of the Solidity programming language developed for the Ethereum blockchain platform. To enhance type safety, the formal syntax of Lolisa adopts a stronger static type system than Solidity. In addition, Lolisa includes a large subset of Solidity syntax components as well as general-purpose programming language features. Therefore, Solidity programs can be directly translated into Lolisa with line-by-line correspondence. Lolisa is inherently generalizable and can be extended to express other programming languages. Finally, the syntax and semantics of Lolisa have been encapsulated as an interpreter in mathematical tool Coq. Hence, smart contracts written in Lolisa can be symbolically executed and verified in Coq.

scholarly journals Low-Cost Dynamic Constraint Checking for the JVM

2016 ◽  
Vol 8 (2) ◽  
pp. 115-136 ◽  
Author(s):  
Konrad Grzanek
Keyword(s):  
Programming Languages ◽  
Programming Language ◽  
Category Theory ◽  
Functional Programming ◽  
Software Verification ◽  
Low Cost ◽  
Type System ◽  
Constraint Checking ◽  
Dynamic Constraint ◽  
Time Overhead

Abstract Using formal methods for software verification slowly becomes a standard in the industry. Overall it is a good idea to integrate as many checks as possible with the programming language. This is a major cause of the apparent success of strong typing in software, either performed on the compile time or dynamically, on runtime. Unfortunately, only some of the properties of software may be expressed in the type system of event the most sophisticated programming languages. Many of them must be performed dynamically. This paper presents a flexible library for the dynamically typed, functional programming language running in the JVM environment. This library offers its users a close to zero run-time overhead and strong mathematical background in category theory.

scholarly journals V: a language with extensible record accessors and a trait-based type system

2018 ◽  
Vol 25 (3) ◽  
pp. 89
Author(s):  
Arthur Giesel Vedana ◽  
Rodrigo Machado ◽  
Álvaro Freitas Moreira
Keyword(s):  
Programming Languages ◽  
Programming Language ◽  
Functional Programming ◽  
Type System ◽  
Functional Programming Languages ◽  
Functional Programming Language ◽  
Novel Approach ◽  
Type Traits

This article introduces the V language, a purely functional programming language with a novel approach to records.Based on a system of type traits, V attempts to solve issues commonly found when manipulating records in purely functional programming languages.

scholarly journals Mechanizing the metatheory of rewire

2019 ◽  
Author(s):  
◽  
Thomas N. Reynolds
Keyword(s):  
Programming Languages ◽  
Type System ◽  
Lambda Calculus ◽  
Equational Theory ◽  
Functional Languages ◽  
Functional Programming Languages ◽  
Type Safety ◽  
High Assurance ◽  
Hardware Description ◽  
Description Languages

The [lambda]-calculus provides a simple, well-established framework for research in functional programming languages that readily lends itself to the use offormal methods--that is, the use of mathematically sound techniques and supporting tools--to describe and verify properties of programming languages, as well. This is no coincidence. After all, the [lambda]-calculus formalizes the concept of effective computability, for all computable functions are definable in the untyped [lambda]-calculus, making it expressively equivalent torecursive functions. In software, the expressiveness of functional languages is considereda strength. Functional approaches to language design, however, needn't be limited to soft-ware. In hardware, the expressiveness of functional languages becomes a major obstacle to successful hardware synthesis, for the reason that such languages are usually capable of expressing general recursion. The presence of general recursion makes it possible to generate expressions that run forever, never producing a well-defined value. In this dissertation, we study two novel variants of the simply typed [lambda]-calculus, representing fragments of functional hardware description languages. The first variant extends the type system, using natural numbers representing time. This addition, though simple, is non-trivial. We prove that this calculus possesses bounded variants of type-safety and strong normalization. That is to say, we show that all well-typed expressions evaluate to values within a bound determined by the natural number index of their corresponding types. The second variant is a computational [lambda]-calculus that formalizes the core fragment of the hardware description language known as ReWire. We prove that the language has type-safety and is strongly normalizing -- the proof of strong normalizationis the first mechanized proof of its kind. We define an equational theory with respect to this language. This allows us to prove that the language has desirable security properties by construction. This work supports a full-edged, formal methodology for producing high assurance hardware.

scholarly journals Description of the Imperative Programming Language in Haskell

2021 ◽  
Vol 4 ◽  
pp. 72-77
Author(s):  
Volodymyr Protsenko
Keyword(s):  
Programming Languages ◽  
Programming Language ◽  
Formal Specification ◽  
Type System ◽  
Main Task ◽  
Abstract Syntax ◽  
Data Types ◽  
Good Tool ◽  
Semantic Function ◽  
Finite Set

When creating a programming language, it is necessary to determine its syntax and semantics. The main task of syntax is to describe all constructions that are elements of the language. For this purpose, a specific syntax highlights syntactically correct sequences of characters of the language alphabet. Most often it is a finite set of rules that generate an infinite set of all construction languages, such as the extended Backus-Naur (BNF) form.To describe the semantics of the language, the preference is given to the abstract syntax, which in real programming languages is shorter and more obvious than specific. The relationship between abstract syntax objects and the syntax of the program in compilers solves the parsing phase.Denotational semantics is used to describe semantics. Initially, it records the denotations of the simplest syntactic objects. Then, with each compound syntactic construction, a semantic function is associated, which by denotations of components of a design calculates its value – denotation. Since the program is a specific syntactic construction, its denotation is possible to determine using the appropriate semantic function. Note that the program itself is not executed when calculating its denotation.The denotative description of a programming language includes the abstract syntax of its constructions, denotations – the meanings of constructions and semantic functions that reflect elements of abstract syntax (language constructions) in their denotations (meanings).The use of the functional programming language Haskell as a metalanguage is considered. The Haskell type system is a good tool for constructing abstract syntax. The various possibilities for describing pure functions, which are often the denotations of programming language constructs, are the basis for the effective use of Haskell to describe denotational semantics.The paper provides a formal specification of a simple imperative programming language with integer data, block structure, and the traditional set of operators: assignment, input, output, loop and conditional. The ability of Haskell to effectively implement parsing, which solves the problem of linking a particular syntax with the abstract, allows to expand the formal specification of the language to its implementation: a pure function — the interpreter.The work contains all the functions and data types that make up the interpreter of a simple imperative programming language.

PERANGKAT LUNAK KOMPUTER

2020 ◽  
Author(s):  
Cut Nabilah Damni
Keyword(s):  
Programming Languages ◽  
Programming Language ◽  
Operating Systems ◽  
Source Code ◽  
Computer Software ◽  
Computer Programs ◽  
Application Systems ◽  
Executable Programs

AbstrakSoftware komputer atau perangkat lunak komputer merupakan kumpulan instruksi (program atau prosedur) untuk dapat melaksanakan pekerjaan secara otomatis dengan cara mengolah atau memproses kumpulan intruksi (data) yang diberikan. (Yahfizham, 2019 : 19) Sebagian besar dari software komputer dibuat oleh (programmer) dengan menggunakan bahasa pemprograman. Orang yang membuat bahasa pemprograman menuliskan perintah dalam bahasa pemprograman seperti layaknya bahasa yang digunakan oleh orang pada umumnya dalam melakukan perbincangan. Perintah-perintah tersebut dinamakan (source code). Program komputer lainnya dinamakan (compiler) yang digunakan pada (source code) dan kemudian mengubah perintah tersebut kedalam bahasa yang dimengerti oleh komputer lalu hasilnya dinamakan program executable (EXE). Pada dasarnya, komputer selalu memiliki perangkat lunak komputer atau software yang terdiri dari sistem operasi, sistem aplikasi dan bahasa pemograman.AbstractComputer software or computer software is a collection of instructions (programs or procedures) to be able to carry out work automatically by processing or processing the collection of instructions (data) provided. (Yahfizham, 2019: 19) Most of the computer software is made by (programmers) using the programming language. People who make programming languages write commands in the programming language like the language used by people in general in conducting conversation. The commands are called (source code). Other computer programs called (compilers) are used in (source code) and then change the command into a language understood by the computer and the results are called executable programs (EXE). Basically, computers always have computer software or software consisting of operating systems, application systems and programming languages.

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