Practical programming assignments are critical parts of programming courses in computerscience education. Students are expected to translate programming concepts learned from lectures into executable implementations ...
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ISBN:
(纸本)9798400704987
Practical programming assignments are critical parts of programming courses in computerscience education. Students are expected to translate programming concepts learned from lectures into executable implementations that solve the tasks outlined in the assignments. These implementations are primarily assessed based on their functional correctness, ensuring that students' code produces the expected output when provided with specific inputs. However, functional correctness is not the only metric that evaluates the quality of programs. Runtime efficiency is a metric that is less frequently evaluated in programming courses, yet it holds significant importance in the context of professional software development. To investigate this gap and its potential ramifications, we conducted a large-scale empirical study on the time efficiency of 250 programming assignments that are evaluated solely on functional correctness. The results demonstrate that students' programming assignments exhibit significant variance in terms of execution time. We further identified 27 recurring inefficient code patterns from these assignments, and observed that most of the inefficient patterns can be optimized by automated tools such as PMD, IntelliJ IDEA and ChatGPT. Our findings provide actionable guidelines for educators to enhance the organization and integration of code performance topics throughout the programming course curriculum.
Choreographies provide a clear way to specify the intended communication behaviour of concurrent and distributed systems. Previous theoretical work investigated the translation of choreographies into (models of) progr...
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Choreographies provide a clear way to specify the intended communication behaviour of concurrent and distributed systems. Previous theoretical work investigated the translation of choreographies into (models of) programs based on message passing. However, existing theories still present a gap between how they model communications-using channel names & agrave;la CCS or p-calculus-and implementations-which use lower-level mechanisms for message routing. We start bridging this gap with a new formal framework called Applied Choreographies. In Applied Choreographies, developers write choreographies in a familiar syntax (from previous work) and reason about their behaviour through simple, abstract name-based communication semantics. The framework offers state-of-the-art features of choreographic models, e.g., modular programming supported via choreographic types. To provide its correctness guarantee, Applied Choreographies comes with a compilation procedure that transforms a choreography into a low-level, implementation-adherent calculus of Service-Oriented Computing (SOC). To manage the complexity of the compilation, we divide its formalisation and proof into three stages, respectively dealing with: (a) the translation of name-based communications into their SOC equivalents, namely, using correlation mechanisms based on message data;(b) the projection of the given choreography into a composition of partial, single-participant choreographies (towards their translation into SOC processes);(c) the translation of partial choreographies and the distribution of global, choreography-level state into local SOC processes. We provide behavioural correspondence results for each stage. Thus, given a choreography specification, we guarantee to synthesise its faithful service-oriented implementation.
In this paper, we address the vehicle routing problem with multiple time windows (VRPMTW), which extends the classic vehicle routing problem to allow customers to be visited only within one or more time windows. We pr...
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ISBN:
(纸本)9783031436116;9783031436123
In this paper, we address the vehicle routing problem with multiple time windows (VRPMTW), which extends the classic vehicle routing problem to allow customers to be visited only within one or more time windows. We propose a constraint programming (CP) model for the VRPMTW and apply model-strengthening techniques such as fixing variables and adding interval variables to improve the model's performance. The model's effectiveness is demonstrated by comparing its performance against an existing mixed-integer programming model. The study also analyzes the differences in solver performance and evaluates the impact of instance characteristics on the solvability of the problem instances. Our study demonstrates the benefits of using a CP model with model-strengthening techniques for solving medium-sized instances of the VRPMTW.
For introductory programming courses, it is crucial to create formative and summarized grading practices that foster growth mindset in students. We explore one way to reimagine and reorient programming assignment grad...
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Unmanned aerial vehicle(UAV)-assisted mobile edge computing(MEC), as a way of coping with delaysensitive and computing-intensive tasks, is considered to be a key technology to solving the challenges of terrestrial MEC...
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Unmanned aerial vehicle(UAV)-assisted mobile edge computing(MEC), as a way of coping with delaysensitive and computing-intensive tasks, is considered to be a key technology to solving the challenges of terrestrial MEC networks. In this work, we study the problem of collaborative service provisioning(CSP) for UAV-assisted MEC. Specifically, taking into account the task latency and other resource constraints, this paper investigates how to minimize the total energy consumption of all terrestrial user equipments, by jointly optimizing computing resource allocation, task offloading, UAV trajectory, and service placement. The CSP problem is a non-convex mixed integer nonlinear programming problem, owing to the complex coupling of mixed integral variables and non-convexity of CSP. To address the CSP problem, this paper proposes an alternating optimization-based solution with the convergence guarantee as follows. We iteratively deal with the joint service placement and task offloading subproblem, and UAV movement trajectory subproblem, by branch and bound and successive convex approximation, respectively,while the closed form of the optimal computation resource allocation can be efficiently obtained. Extensive simulations validate the effectiveness of the proposed algorithm compared to three baselines.
Motivation We learn more effectively through experience and reflection than through passive reception of information. Bioinformatics offers an excellent opportunity for project-based learning. Molecular data are abund...
Motivation We learn more effectively through experience and reflection than through passive reception of information. Bioinformatics offers an excellent opportunity for project-based learning. Molecular data are abundant and accessible in open repositories, and important concepts in biology can be rediscovered by reanalyzing the *** In the manuscript, we report on five hands-on assignments we designed for master's computerscience students to train them in bioinformatics for genomics. These assignments are the cornerstones of our introductory bioinformatics course and are centered around the study of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). They assume no prior knowledge of molecular biology but do require programming skills. Through these assignments, students learn about genomes and genes, discover their composition and function, relate SARS-CoV-2 to other viruses, and learn about the body's response to infection. Student evaluation of the assignments confirms their usefulness and value, their appropriate mastery-level difficulty, and their interesting and motivating *** and Implementation The course materials are freely available on GitHub at https://***/IB-ULFRI.
User-centered thinking is no typical strength of many students, and especially often of tech-savvy computerscience students. We propose a Human-Robot Interaction (HRI) introductory course as a highly suitable opportu...
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Ultradense low-Earth orbit (LEO) satellite-terrestrial network (ULSN) has evolved as a new paradigm to provide ubiquitous and high-capacity communications in next generation wireless networks. However, the direct LEO ...
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Factors have always played an important role in stock analysis, but they are only effective for specific problems in specific scenarios. Therefore, constructing factors timely and quickly for different scenarios is an...
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