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Is Algorithm Comprehension Different from Program Comprehension?

机译:算法理解与程序理解不同吗?

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At the beginning of their undergraduate studies, computer science students are exposed to introductory programming, discrete mathematics, and algorithms. A large body of literature has studied how such students comprehend programs. Much less attention has been paid to understanding how students comprehend algorithms, i.e., representations of problem-solving processes accompanied by proofs of their properties. To investigate whether algorithm comprehension is under-researched or whether we can simply transfer results from program comprehension (and, possibly, proof comprehension) to the domain of algorithms, we conducted a larger study following a Grounded-Theory approach. For this study, we worked with twelve participants with varying degrees of prior knowledge regarding algorithms, from technically no prior knowledge to advanced graduate students pursuing a doctoral degree in algorithms-related fields. In this paper, we report on the analysis and interpretation of interview data focused on exploring potential differences between program comprehension and algorithm comprehension. Our analyses and interpretations revealed both similarities and differences between program comprehension and algorithm comprehension: Unsurprisingly, we found that aspects known from program comprehension, e.g., using top-down approaches or utilizing prior knowledge of programming plans, can be found in algorithm comprehension as well. However, some of these aspects manifest themselves in notably different details or are influenced by, e.g., the wording of a proof. Most interesting, we found that novice and advanced students alike benefit from switching between reading the representation of the program-solving process and the accompanying proofs. We present qualitative results illustrating both similarities and differences between program comprehension and algorithm comprehensions and offer first explanations for these.
机译:在本科学习开始时,计算机科学学生接触到介绍性编程,离散数学和算法。大量的文学研究了这些学生如何理解程序。对学生理解算法,即问题解决过程的表示伴随着其性质的证明,所关注的注意力得多。为了调查是否研究了算法理解,或者我们是否可以简单地将结果转移到算法领域的计划理解(以及可能,证明理解),我们在接地理论方法后进行了更大的研究。对于这项研究,我们使用了12位参与者,具有不同程度的关于算法的知识,从技术上没有先前的知识,以先进的研究生在追求算法相关领域的博士学位。在本文中,我们报告了采访数据的分析和解释,其专注于探索计划理解与算法理解之间的潜在差异。我们的分析和解释揭示了方案理解和算法理解之间的相似之处和差异:不想出的,我们发现从计划理解中知道的方面,例如使用自上而下的方法或利用方案制定计划的先验知识,也可以在算法理解中找到。然而,其中一些方面在尤其上表现出不同的细节,或者受到例如证据的措辞的影响。最有趣的是,我们发现新手和高级学生相似地从读取程序解决过程的代表和随附的证据之间的转换中的益处。我们呈现定性结果,说明程序理解和算法适合之间的相似之处和差异,并为这些提供了第一个解释。

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