需求理解中图形表示与文本表示效率的实证研究

Zohreh Sharafi, A. Marchetto, A. Susi, G. Antoniol, Yann-Gaël Guéhéneuc
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引用次数: 50

摘要

图形表示用于在软件开发过程的所有阶段中可视化、指定和记录软件工件。与文本相比,图形表示以二维形式呈现,似乎易于处理。然而,很少有实证研究调查了图形表示与文本表示在建模和表示软件需求方面的效率。因此,在本文中,我们报告了一项涉及28名参与者的眼球追踪实验的结果,以研究结构化文本和图形表示对受试者在执行需求理解任务时效率的影响。我们根据正确答案的百分比(准确性)以及完成任务所花费的时间和精力来衡量受试者的效率。我们观察到在准确性方面没有统计学上的显著差异。然而,我们的受试者在使用图形表示时花费了更多的时间和精力,尽管这些额外的时间和精力并不影响准确性。我们的发现挑战了一般的假设,即图形表示比文本表示更有效,至少在开发人员不熟悉图形表示的情况下是这样。事实上,我们的研究结果强调,训练可以显著提高受试者处理图形表示的效率。此外,通过比较受试者的视觉路径,我们观察到图形表示的空间结构导致受试者遵循两种不同的策略(自上而下vs.自下而上),随后这种分层结构帮助开发人员减轻了模型理解任务的难度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An empirical study on the efficiency of graphical vs. textual representations in requirements comprehension
Graphical representations are used to visualise, specify, and document software artifacts in all stages of software development process. In contrast with text, graphical representations are presented in two-dimensional form, which seems easy to process. However, few empirical studies investigated the efficiency of graphical representations vs. textual ones in modelling and presenting software requirements. Therefore, in this paper, we report the results of an eye-tracking experiment involving 28 participants to study the impact of structured textual vs. graphical representations on subjects' efficiency while performing requirement comprehension tasks. We measure subjects' efficiency in terms of the percentage of correct answers (accuracy) and of the time and effort spend to perform the tasks. We observe no statistically-significant difference in term of accuracy. However, our subjects spent more time and effort while working with the graphical representation although this extra time and effort does not affect accuracy. Our findings challenge the general assumption that graphical representations are more efficient than the textual ones at least in the case of developers not familiar with the graphical representation. Indeed, our results emphasise that training can significantly improve the efficiency of our subjects working with graphical representations. Moreover, by comparing the visual paths of our subjects, we observe that the spatial structure of the graphical representation leads our subjects to follow two different strategies (top-down vs. bottomup) and subsequently this hierarchical structure helps developers to ease the difficulty of model comprehension tasks.
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