520,180 research outputs found

    Declaratively solving Google Code Jam problems with Picat

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    In this paper we present several examples of solving algorithmic problems from the Google Code Jam programming contest with Picat programming language using declarative techniques: constraint logic programming and tabled logic programming. In some cases the use of Picat simplifies the implementation compared to conventional imperative programming languages, while in others it allows to directly convert the problem statement into an efficiently solvable declarative problem specification without inventing an imperative algorithm

    The impact of using pair programming on system evolution a simulation-based study

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    In this paper we investigate the impact of pair--programming on the long term evolution of software systems. We use system dynamics to build simulation models which predict the trend in system growth with and without pair programming. Initial results suggest that the extra effort needed for two people to code together may generate sufficient benefit to justify pair programming.Peer reviewe

    Testing Object-Oriented Programs: Making it Simple

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    One of the major difficulties facing anyone trying to teach the first programming course is how to encourage students to thoroughly test their programs. We would argue that the main reasons for this are the lack of suitable tools for testing and the need to write extra "debug" code in order to verify correct operation. We further argue that the problem is even worse with object-oriented languages because of multiple classes and encapsulation. In this paper we describe the testing tools within the Blue programming environment which allow object-oriented programs to be thoroughly tested without writing a single line of new code

    A Syntactic Neural Model for General-Purpose Code Generation

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    We consider the problem of parsing natural language descriptions into source code written in a general-purpose programming language like Python. Existing data-driven methods treat this problem as a language generation task without considering the underlying syntax of the target programming language. Informed by previous work in semantic parsing, in this paper we propose a novel neural architecture powered by a grammar model to explicitly capture the target syntax as prior knowledge. Experiments find this an effective way to scale up to generation of complex programs from natural language descriptions, achieving state-of-the-art results that well outperform previous code generation and semantic parsing approaches.Comment: To appear in ACL 201

    Multilingual investigation of theory-based intervention for program comprehension

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    This thesis is the continuation of an experiment called “Eye-movement Modeling Examples in Source Code Comprehension: A Classroom Study”. This first experiment studies how effective is showing novice programmers how experts read code with a video with the expert’s gaze guided by a verbal explanation. Therefore, this thesis studies, using a similar experiment, whether only verbal explanation and visual stimuli without the expert’s gaze could be also helpful for the programming novices.Grado en Ingeniería Informática de Servicios y Aplicacione
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