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Ask the Engineers: Exploring Repertory Grids and Personal Constructs for Software Data Analysis

机译:询问工程师:探索库网格和用于数据数据分析的个人构造

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Maturity in software projects is often equated with data-driven predictability. However, data collection is expensive and measuring all variables that may correlate with project outcome is neither practical nor feasible. In contrast, a project engineer can identify a handful of factors that he or she believes influence the success of a project. The challenge is to quantify engineers' insights in a way that is useful for data analysis. In this exploratory study, we investigate the repertory grid technique for this purpose. The repertory grid technique is an interview-based procedure for eliciting "constructs" (e.g., Adhering to coding standards) that individuals believe influence a worldly phenomenon (e.g., What makes a high-quality software project) by comparing example elements from their past (e.g., Projects they have worked on). We investigate the relationship between objective metrics of project performance and repertory grid constructs elicited from eight software engineers. Our results show correlations between the engineers' subjective constructs and the objective project outcome measures. This suggests that repertory grids may be of benefit in developing models of project outcomes, particularly when project data is limited.
机译:软件项目的成熟度通常等同于数据驱动的可预测性。但是,数据收集是昂贵的,并且测量可能与项目成果相关的所有变量既不切实际,也不可行。相反,项目工程师可以确定他或她认为会影响项目成功的少数因素。挑战在于以一种对数据分析有用的方式量化工程师的见解。在此探索性研究中,我们为此目的研究了储备格技术。储备格技术是一种基于面试的过程,通过比较过去的示例元素(例如,遵循个人的构想)来引发“构架”(例如,遵循编码标准),该构想会影响世界性的现象(例如,构成高质量软件项目的要素)。例如,他们从事的项目)。我们调查了项目绩效的客观指标与由八位软件工程师得出的储备格结构之间的关系。我们的结果表明工程师的主观构造与客观项目成果度量之间的相关性。这表明,储备格网在开发项目成果模型时可能会有所帮助,尤其是在项目数据有限的情况下。

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