Generators in Icon

Griswold, Ralph E.; Hanson, David R.; Korb, John T.

doi:10.1145/357133.357136

Cited by 39 publications

(18 citation statements)

References 24 publications

(35 reference statements)

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“…For example, ZNat(0).zero() evaluates to true because its implementation tests the equation val = 0. A named constructor for type T may be invoked without an explicit receiver object when it is used to pattern-match a 1 class ZNat { ... constructor equals(Nat n) 9 ( n.zero() ) 10 } 11 class PSucc { ...…”

Section: Named Constructorsmentioning

confidence: 99%

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Reconciling exhaustive pattern matching with objects

Isradisaikul

Myers

2013

SIGPLAN Not.

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Pattern matching, an important feature of functional languages, is in conflict with data abstraction and extensibility, which are central to object-oriented languages. Modal abstraction offers an integration of deep pattern matching and convenient iteration abstractions into an object-oriented setting; however, because of data abstraction, it is challenging for a compiler to statically verify properties such as exhaustiveness. In this work, we extend modal abstraction in the JMatch language to support static, modular reasoning about exhaustiveness and redundancy. New matching specifications allow these properties to be checked using an SMT solver. We also introduce expressive pattern-matching constructs. Our evaluation shows that these new features enable more concise code and that the performance of checking exhaustiveness and redundancy is acceptable.

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Section: Named Constructorsmentioning

confidence: 99%

“…For example, the formula int x = y-1 # y+1 (which should be read as int x = (y-1 # y+1)) generates the two solutions x = y-1 and x = y+1 when solving for x, and y = x+1 and y = x-1 when solving for y. Unlike Icon's alternation expression [9], a match is attempted against all alternatives even if one of them fails.…”

Section: Other Extensionsmentioning

confidence: 99%

Reconciling exhaustive pattern matching with objects

Isradisaikul

Myers

2013

SIGPLAN Not.

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“…The idea of bringing nondeterminism into programming languages has appeared in works that focus on goal-directed programming [21], functional and logic programming [7,29] and recently, specifically testing [18]. These approaches introduced additional facilities into the existing programming model to allow operations analogous to enumeration in SciFe, such as querying for multiple results [18,21] and fair enumeration of composite results [7,29]. Instead of relying on non-determinism, SciFe lacks the generality of such approaches and offers specialized enumerators for exhaustive fine-grained controlled generation that avoids backtracking, for both simple and complex constraints.…”

Section: Related Workmentioning

confidence: 99%

Programming with enumerable sets of structures

Kuraj

Kunčak

Jackson

2015

Proceedings of the 2015 ACM SIGPLAN International Conference on Object-Oriented Programming, Systems, Languages, and Applicatio

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We present an efficient, modular, and feature-rich framework for automated generation and validation of complex structures, suitable for tasks that explore a large space of structured values. Our framework is capable of exhaustive, incremental, parallel, and memoized enumeration from not only finite but also infinite domains, while providing fine-grained control over the process. Furthermore, the framework efficiently supports the inverse of enumeration (checking whether a structure can be generated and fast-forwarding to this structure to continue the enumeration) and lazy enumeration (achieving exhaustive testing without generating all structures). The foundation of efficient enumeration lies in both direct access to encoded structures, achieved with well-known and new pairing functions, and dependent enumeration, which embeds constraints into the enumeration to avoid backtracking. Our framework defines an algebra of enumerators, with combinators for their composition that preserve exhaustiveness and efficiency. We have implemented our framework as a domain-specific language in Scala. Our experiments demonstrate better performance and shorter specifications by up to a few orders of magnitude compared to existing approaches.

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“…Examples taken from Icon should be clea~ by context, at least in their general aspects, if not in all details. More comprehensive descriptions of Icon are given in [16,18,19,24] and implementation is discussed in [24].…”

Section: A Brief Overviewmentioning

confidence: 99%

An Alternative to the Use of Patterns in String Processing

Griswold

Hanson

1980

ACM Trans. Program. Lang. Syst.

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~v SNOBOL4 is best known for its string processing facilities, which are based on patterns as da~: objects. Despite the demonstrated success of patterns, there are many shortcomings associated with, their use. The concept of patterns in SNOBOL4 is examined and problem areas are discussed. A~. alternative method for high-level string processing is described. This method, implemented in thg programming language Icon, employs generators, which are capable of producing alternative value~ Generators, coupled with a goal-driven method of expression evaluation, provide the string processingfacilities of SNOBOL4 without the disadvantages associated with patterns. Comparisons betwee~ SNOBOL4 and Icon are included and the broader implications of the new approach are discussed. ;~

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Generators in Icon

Cited by 39 publications

References 24 publications

Reconciling exhaustive pattern matching with objects

Reconciling exhaustive pattern matching with objects

Programming with enumerable sets of structures

An Alternative to the Use of Patterns in String Processing

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