Refactoring pattern matching

Wang, Meng; Gibbons, Jeremy; Matsuda, Kazutaka; Hu, Zhenjiang

doi:10.1016/j.scico.2012.07.014

Cited by 16 publications

(16 citation statements)

References 48 publications

(71 reference statements)

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“…However, datatype inference has been addressed in other contexts, such as (theoretical approaches): XML Schema Definition (XSD) [6,7,14], programming languages [4,5,11,16,31], and OWL [13,19,26,28]. Moreover, we have revised some tools available on the Web for XSD inference 2.…”

Section: Related Workmentioning

confidence: 99%

“…Other works [16,31] also use axioms and pattern matching over the constructors of the datatype during the inference process. In [4,5], operations and a syntax associated with datatypes are analyzed to infer complex datatypes.…”

Section: Function-based Approachesmentioning

confidence: 99%

“…Hierarchy-based methods [6,7,14] cannot infer all simple datatypes, since they consider a reduced set of datatypes and there are intersections between datatype lexical spaces (e.g., 1999 can be an integer or a gYear according to the lexical space of both W3C datatypes); 2. Complex datatype inference methods [4,5,11,16,31] cannot be applied to simple datatypes, since in RDF, a simple datatype is an atomic value associated with a predicate; and 3. Tools available on the Web [12,21,32] have unknown criteria of inference, providing different datatypes for the same data.…”

Section: Introductionmentioning

confidence: 99%

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RDF-F: RDF Datatype inFerring Framework

2018

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In the context of RDF document matching/integration, the datatype information, which is related to literal objects, is an important aspect to be analyzed in order to better determine similar RDF documents. In this paper, we present an RDF Datatype in Ferring Framework, called RDF-F, which provides two independent datatype inference processes: 1) a fourstep process consisting of (i) a predicate information analysis (i.e., deduce the datatype from existing range property), (ii) an analysis of the object value itself by a pattern-matching process (i.e., recognize the object lexical space), (iii) a semantic analysis of the predicate name and its context, and (iv) generalization of Numeric and Binary datatypes to ensure the integration; and 2) a non-ambiguous lexical-space-matching process, where literal values are inferred by the modification of their representation, following new lexical spaces. We evaluated the performance and the accuracy of both processes with datasets from DBpedia. Results show that the execution time of both indicators is linear and their accuracy can increase up to 97.10 and 99.30%, respectively.

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Section: Related Workmentioning

confidence: 99%

Section: Function-based Approachesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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RDF-F: RDF Datatype inFerring Framework

2018

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“…The definition of the composition combinator • is standard [6,7,9,11,13,14,17,21]. It is known that the combinator • preserves the acceptability and consistency laws.…”

Section: Appendix a Proofsmentioning

confidence: 99%

“…Very often, such languages are defined as a collection of combinators which can be read in two ways [6,7,9,11,13,14,17,21]: forward and backward. A disadvantage of the combinator-based approach is that transformations have to be encoded in a somewhat inconvenient programming style.…”

Section: Introductionmentioning

confidence: 99%

“Bidirectionalization for free” for monomorphic transformations

Matsuda

Wang

2015

Science of Computer Programming

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A bidirectional transformation is a pair of mappings between source and view data objects, one in each direction. When the view is modified, the source is updated accordingly with respect to some laws. Over the years, a lot of effort has been made to offer better language support for programming such transformations. In particular, a technique known as bidirectionalization is able to analyze and transform unidirectional programs written in general purpose languages, and "bidirectionalize" them.Among others, an approach termed semantic bidirectionalization proposed by Voigtländer stands out in terms of user-friendliness. A unidirectional program can be written using arbitrary language constructs, as long as the function it represents is polymorphic and the language constructs respect parametricity. The free theorems that follow from the polymorphic type of the program allow a kind of forensic examination of the transformation, determining its effect without examining its implementation. This is convenient, as the programmer is not restricted to using a particular syntax; but it does require the transformation to be polymorphic.In this paper, we lift this polymorphism requirement to improve the applicability of semantic bidirectionalization. Concretely, we provide a type class PackM γ α µ, which intuitively reads "a concrete datatype γ is abstracted to a type α, and the 'observations' made by a transformation on values of type γ are recorded by a monad µ". With PackM , we turn monomorphic transformations into polymorphic ones that are ready to be bidirectionalized. We demonstrate our technique with case studies of typical applications of bidirectional transformation, namely text processing, XML query and graph transformation, which were commonly considered beyond semantic bidirectionalization because of their monomorphic nature.

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ReInstancer: An automatic refactoring approach for Instanceof pattern matching

Zhang,

Hong

2024

J Software Evolu Process

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The instanceof pattern matching can improve the code quality and readability by removing the redundant typecasting and simplifying the design in different scenarios. However, existing works do not provide sufficient support for refactoring instanceof pattern matching. This paper first identifies several cases that cannot be well handled by existing IDEs. Based on these observations, we propose a novel approach called ReInstancer to refactor instanceof pattern matching automatically. ReInstancer conducts program analysis for multi‐branch statements to obtain pattern variables. After analyzing these patterns, the multi‐branch statements are optimized and finally refactored into switch statements or expressions. ReInstancer is evaluated by 20 real‐world projects with more than 7,700 instanceof pattern matching. The experimental results demonstrate that a total of 3,558 instanceof expressions and 228 multi‐branch statements are refactored within 10.8 s on average for each project. ReInstancer improves the code quality by reducing redundant typecasting, demonstrating its effectiveness.

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Refactoring pattern matching

Cited by 16 publications

References 48 publications

RDF-F: RDF Datatype inFerring Framework

RDF-F: RDF Datatype inFerring Framework

“Bidirectionalization for free” for monomorphic transformations

ReInstancer: An automatic refactoring approach for Instanceof pattern matching

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