Design Computation is the use of programming in the design of physical systems such as buildings and infrastructure. This involves embedding both general-purpose textual languages and domain-specific visual languages ...
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ISBN:
(纸本)9798400712159
Design Computation is the use of programming in the design of physical systems such as buildings and infrastructure. This involves embedding both general-purpose textual languages and domain-specific visual languages within geometry modelling and engineering applications in the construction industry. A unique form of entry-level end-user programming has emerged in Design Computation. However, there are significant usability and representational issues;general-purpose languages present barriers to adoption, whilst visual languages do not scale to complex design problems. In this essay, we explore how advances in programming language research could be harnessed in future Design Computation languages to address these pedagogic, representational and scaling issues so as to improve human-readable program structure and semantics and to enable machine-readable program verification.
作者：
Turner, RaymondCSEE
University of Essex Wivenhoe Park Colchester CO43SQ United Kingdom
Taken at face value, a programming language is defined by a formal grammar. But, clearly, there is more to it. By themselves, the naked strings of the language do not determine when a program is correct relative to so...
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Wireless Sensor Networks (WSNs) are highly coexisting, dynamic and application specific, as well as having resource constrained in nature, thus programming the sensor nodes is difficult when compared to traditional co...
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ISBN:
(纸本)9789380544168
Wireless Sensor Networks (WSNs) are highly coexisting, dynamic and application specific, as well as having resource constrained in nature, thus programming the sensor nodes is difficult when compared to traditional computer systems. It is most difficult task to build reliable and practical programming solutions or systems for distributed and resource-constrained wireless sensor devices. The objective of this research contribution is to present a comparative study in terms of programming approaches, its potentials and pitfalls.
Background: The current primary focus of programming language benchmarking studies in the literature is performance with less attention on safety. However, this context has a research gap because the software industry...
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Background: The current primary focus of programming language benchmarking studies in the literature is performance with less attention on safety. However, this context has a research gap because the software industry has focused more on software safety than performance to safeguard clients. This paper attempts to address this research gap by benchmarking languages in both safety and performance. Furthermore, this study includes Rust, a relatively new language with promising safety and performance features. Methods: This paper compares six prominent programming languages (in alphabetical order: C, C++, Go, Java, Python and Rust) to determine which is the best in terms of safety and performance using quantitative and qualitative methods through actual testing of code and analysis of existing information. Results: The comparisons show that Rust was the safest language, outperforming all the other languages. Regarding performance, Rust, C and C++ performed comparably to each other and generally outperformed Go, Java and Python. Conclusion: It is possible to achieve a superior balance of software safety and performance with, at worst, a minimal performance drop;as Rust clearly demonstrates.
programming language documentation refers to the set of technical documents that provide application developers with a description of the high-level concepts of a language (e.g., manuals, tutorials, and API references...
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programming language documentation refers to the set of technical documents that provide application developers with a description of the high-level concepts of a language (e.g., manuals, tutorials, and API references). Such documentation is essential to support application developers in effectively using a programming language. One of the challenges faced by documenters (i.e., personnel that design and produce documentation for a programming language) is to ensure that documentation has relevant information that aligns with the concrete needs of developers, defined as the missing knowledge that developers acquire via voluntary search. In this article, we present an automated approach to support documenters in evaluating the differences and similarities between the concrete information need of developers and the current state of documentation (a problem that we refer to as the topical alignment of a programming language documentation). Our approach leverages semi-supervised topic modelling that uses domain knowledge to guide the derivation of topics. We initially train a baseline topic model from a set of Rust-related Q&A posts. We then use this baseline model to determine the distribution of topic probabilities of each document of the official Rust documentation. Afterwards, we assess the similarities and differences between the topics of the Q&A posts and the official documentation. Our results show a relatively high level of topical alignment in Rust documentation. Still, information about specific topics is scarce in both the Q&A websites and the documentation, particularly related topics with programming niches such as network, game, and database development. For other topics (e.g., related topics with language features such as structs, patterns and matchings, and foreign function interface), information is only available on Q&A websites while lacking in the official documentation. Finally, we discuss implications for programming language documenters, particula
In this paper a new fuzzy programming language XL is defined. XL is obtained from the elementary fuzzy programming language L by broadening its syntax and semantics with an indefinite loop statement (while loop). Depe...
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In this paper a new fuzzy programming language XL is defined. XL is obtained from the elementary fuzzy programming language L by broadening its syntax and semantics with an indefinite loop statement (while loop). Depending on the choice of W-functions used in the fuzzy assignment, a family of related languages can be defined. These languages are proposed for both studying and refining some ideas about fuzzy computability and specifying real fuzzy algorithms. (C) 1997 Elsevier Science B.V.
Regression Testing (RT) is a quality-assurance practice commonly adopted in the software industry to check if functionality remains intact after code changes. Test flakiness is a serious problem for RT. A test is said...
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Regression Testing (RT) is a quality-assurance practice commonly adopted in the software industry to check if functionality remains intact after code changes. Test flakiness is a serious problem for RT. A test is said to be flaky when it non-deterministically passes or fails on a fixed environment. Prior work studied test flakiness primarily on Java programs. It is unclear, however, how problematic is test flakiness for software written in other programming languages. This paper reports on a study focusing on three central aspects of test flakiness: concentration, similarity, and cost. Considering concentration, our results show that, for any given programming language that we studied (C, Go, Java, JS, and Python), most issues could be explained by a small fraction of root causes (5/13 root causes cover 78.07% of the issues) and could be fixed by a relatively small fraction of fix strategies (10/23 fix strategies cover 85.20% of the issues). Considering similarity, although there were commonalities in root causes and fixes across languages (e.g., concurrency and async wait are common causes of flakiness in most languages), we also found important differences (e.g., flakiness due to improper release of resources are more common in C), suggesting that there is opportunity to fine tuning analysis tools. Considering cost, we found that issues related to flaky tests are resolved either very early once they are posted (<10 days), suggesting relevance, or very late (>100 days), suggesting irrelevance.
This paper presents a large-scale study that investigates the bug resolution characteristics among popular Github projects written in different programming languages. We explore correlations but, of course, we cannot ...
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This paper presents a large-scale study that investigates the bug resolution characteristics among popular Github projects written in different programming languages. We explore correlations but, of course, we cannot infer causation. Specifically, we analyse bug resolution data from approximately 70 million Source Line of Code, drawn from 3 million commits to 600 GitHub projects, primarily written in 10 programming languages. We find notable variations in apparent bug resolution time and patch (fix) size. While interpretation of results from such large-scale empirical studies is inherently difficult, we believe that the differences in medians are sufficiently large to warrant further investigation, replication, re-analysis and follow up research. For example, in our corpus, the median apparent bug resolution time (elapsed time from raise to resolve) for Ruby was 4X that for Go and 2.5X for Java. We also found that patches tend to touch more files for the corpus of strongly typed and for statically typed programs. However, we also found evidence for a lower elapsed resolution time for bug resolution committed to projects constructed from statically typed languages. These findings, if replicated in subsequent follow on studies, may shed further empirical light on the debate about the importance of static typing.
The development of robot languages has followed a pattern similar to that of conventional programming languages, where robot languages have been based on an existing programming language. This paper first identifies t...
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The development of robot languages has followed a pattern similar to that of conventional programming languages, where robot languages have been based on an existing programming language. This paper first identifies the use of an existing base as one way of developing robot programming languages, and discusses the areas of difficulty in this approach. Then, on-line and off-line programming of robots is discussed and the requirements of robot programming languages that are different to those of non-specialised programming languages are presented. A discussion and evaluation of some programming languages in terms of their appropriateness for use as the base for an intelligent robot programming language is presented. This leads to the conclusion that no current language forms an adequate base for intelligent robot programming languages. What is needed as a base is a language for use in the artificial intelligence domain, that incorporates real-time facilities.
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