Investigation of erosive wear of constructional materials

Ryzhenkov, V. A.; Seleznev, L. I.; Ryzhenkov, A. V.

doi:10.1134/s0040601514100103

Cited by 3 publications

(3 citation statements)

References 2 publications

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“…The question also discussed how the lack of a zip operation in Java Stream was significant. Our benchmark leveraged some ideas from kotlin-benchmarks (Ryzhenkov, 2014), such as testing with three different data types: Integer, String and a Value class holding an int and a String field that are combined to implement equals and hashCode.…”

Section: Custom Operation Every the Custom Operationmentioning

confidence: 99%

“…Many use-cases evaluated sequence traversal performance through the use of benchmarks, namely kotlin-benchmarks (Ryzhenkov, 2014), which provides benchmarks over Kotlins features such as the use of Sequence. Another example are the benchmarks devised by Angelika Langer and Klaus Kreft (Langer and Kreft, 2015) with the aim of better understanding how Java Streams perform and when parallel() outperforms sequential processing of the same Stream.…”

Section: Related Workmentioning

confidence: 99%

“…• A novel benchmark that merges state-of-the-art toolkits such as kotlin-benchmarks (Ryzhenkov, 2014) and JMH (Shipilev, 2013), with the idea of processing streams from realistic data sources, interleaved with user-defined operations.…”

Section: Introductionmentioning

confidence: 99%

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Deconstructing yield Operator to Enhance Streams Processing

Poeira

Carvalho

2021

Proceedings of the 16th International Conference on Software Technologies

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Customizing streams pipelines with new user-defined operations is a well-known pattern regarding streams processing. However, programming languages face two challenges when considering streams extensibility: 1) provide a compact and readable way to express new operations, and 2) keep streams' laziness behavior. From here, we may find a consensus around the adoption of the generator operator, i.e. yield, as a means to fulfil both requirements, since most state-of-the-art programming languages provide this feature. Yet, what is the performance overhead of interleaving a yield-based operation in streams processing? In this work we present a benchmark based on realistic use cases of two different web APIs, namely: Last.fm and world weather online, where custom yield-based operations may degrade the streams performance in twofold. We also propose a purely functional and minimalistic design, named tinyield, that can be easily adopted in any programming language and provides a concise way of chaining extension operations fluently, with low overhead in the evaluated benchmarks. The tinyield proposal was deployed in three different libraries, namely for Java (jayield), JavaScript (tinyield4ts) and .Net (tinyield4net).

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Section: Custom Operation Every the Custom Operationmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%