Context: Several code guidelines aim at providing a common perspective on the readability and comprehensibility of source code. However, in many cases, they are contradictory on how to improve these quality characteri...
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ISBN:
(纸本)9789873806988
Context: Several code guidelines aim at providing a common perspective on the readability and comprehensibility of source code. However, in many cases, they are contradictory on how to improve these quality characteristics. Objective: To analyze the influence of three contradictory source code attributes - indentation spacing, identifier length and code size - on the source code reada-bility and comprehensibility, interpreting whether programming experience and domain knowledge can support explaining these contradictions. Method: To per-form an empirical study with software developers collecting quantitative (Likert scale) and qualitative data to assess the readability and comprehensibility of de-velopers regarding Python snippets. To observe eventual perceptions contradic-tions and whether their levels of experience and knowledge have something to do with such contrary results. Results: Regardless their programming experience, 4-spaces indentation dominated the readability preference of participants. While the readability and comprehensibility preferences towards long and complete-word identifiers were mostly true for both novice/experts, developers with more experience and low domain knowledge level seemed to be more affected by the length of identifiers. Furthermore, while all participants showed more positive comprehensibility perceptions for Pythin snippets with more lines of code, their readability perceptions regardnig code size were contradictory since the less experienced participants preferred more lines of code and the more experienced ones prefer fewer lines. Conclusion: The results presented in the technical literature seemed to be caused by the interchangeable use of the readability and comprehensibility concepts. Further investigation is still needed to observe whether other confounding factors might support the explanation of such contrary results.
The breakage-fusion-bridge (BFB) mechanism was proposed over seven decades ago and is a source of genomic variability and gene amplification in cancer. Here we formally model and analyze the BFB mechanism, to our know...
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Large-scale scientific computations are often organized as a composition of many computational tasks linked through data flow. After the completion of a computational scientific experiment, a scientist has to analyze ...
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In this abstract, we describe provenance traces generated from executions of scientific workflows managed by the Swift parallel scripting system. They follow a provenance data model, used by MTCProv, the provenance ma...
The firefly algorithm (FA) is a new population-based metaheuristic bioinspired on the behavior of the flashing characteristics of fireflies. As a population-based algorithm, the FA suffers from large execution times s...
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Maintaining railway tracks in healthy conditions is critical to ensuring the safe operation of railroad transportation. According to the Federal Railroad Administration (FRA), nearly 23% of train accidents that occurr...
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This paper presents the implementation of ARQ-PROP II, a limited-depth propositional reasoner, via the compilation of its specification into an exact formulation using the satyrus platform. satyrus' compiler takes...
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This paper focuses on a performance enhancement of communication performance by compressing data stream. ASE coding is an effective lossless data compression method for data stream. The software implementation of the ...
This paper focuses on a performance enhancement of communication performance by compressing data stream. ASE coding is an effective lossless data compression method for data stream. The software implementation of the coding/decoding method inevitably meets a performance mismatch in memory and storage devices. In the compressor side, it is predictable to decide the size of an original data block and is available to process a flexible buffer memory. However, the decompressor is not able to predict the buffer size because the original data size is not obvious before the decompression. This causes a performance mismatch in the filesystem level. This paper proposes a novel method to address the performance mismatch by applying a notification mechanism of compression size from the compressor. This paper describes the mechanism focusing on the system call usage. Through experimental evaluations, we show the performance improvement of the decompression performance for handling data stream.
IoT edge platform has become popular in various distributed environments. The edge devices need to communicate BigData among them or with the cloud servers by collaborating with AI technologies for finding events from...
IoT edge platform has become popular in various distributed environments. The edge devices need to communicate BigData among them or with the cloud servers by collaborating with AI technologies for finding events from the applications. Those devices exchange data streams from such as distributed sensors and remote image/video devices. We focus on an acceleration technique for the communication performance using a stream-based lossless data compression technology. This paper proposes a parallelization technique for the compression process in a software environment running on a multicore processor. The technique invokes concurrent compression processes assigned to multiple threads with splitting a data stream to chunks. The paper exposes three scheduling methods for assigning the chunks to the threads: in-order, hybrid and out-of-order. As an original data order of chunks must be obtained in decompression side, the proposed technique introduces packeting mechanisms in each chunk by adding headers to support the scheduling methods. Through experimental performance evaluations, we discuss the packeting overhead focusing on compression ratio and speedup by the parallelization with three scheduling methods.
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