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Characteristics that affect preference of decision models for asset selection: an industrial questionnaire survey

机译:影响资产选择决策模型偏好的特征:工业调查问卷调查

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摘要

Modern software development relies on a combination of development and re-use of technical asset, e.g., software components, libraries, and APIs. In the past, re-use was mostly conducted with internal assets but today external; open source, customer off-the-shelf (COTS), and assets developed through outsourcing are also common. This access to more asset alternatives presents new challenges regarding what assets to optimally chose and how to make this decision. To support decision-makers, decision theory has been used to develop decision models for asset selection. However, very little industrial data has been presented in literature about the usefulness, or even perceived usefulness, of these models. Additionally, only limited information has been presented about what model characteristics determine practitioner preference toward one model over another. The objective of this work is to evaluate what characteristics of decision models for asset selection determine industrial practitioner preference of a model when given the choice of a decision model of high precision or a model with high speed. An industrial questionnaire survey is performed where a total of 33 practitioners, of varying roles, from 18 companies are tasked to compare two decision models for asset selection. Textual analysis and formal and descriptive statistics are then applied on the survey responses to answer the study's research questions. The study shows that the practitioners had clear preference toward the decision model that emphasized speed over the one that emphasized decision precision. This conclusion was determined to be because one of the models was perceived faster, had lower complexity, was more flexible in use for different decisions, and was more agile on how it could be used in operation, its emphasis on people, its emphasis on "good enough" precision and ability to fail fast if a decision was a failure. Hence, we found seven characteristics that the practitioners considered important for their acceptance of the model. Industrial practitioner preference, which relates to acceptance, of decision models for asset selection is dependent on multiple characteristics that must be considered when developing a model for different types of decisions such as operational day-to-day decisions as well as more critical tactical or strategic decisions. The main contribution of this work are the seven identified characteristics that can serve as industrial requirements for future research on decision models for asset selection.
机译:现代软件开发依赖于开发和再利用的技术资产,例如,软件组件库和API的组合。在过去,再利用大多由内部的资产,但目前外部进行;开放源代码,客户离现货(COTS),并通过外包开发的资产也很常见。这获得更多资产的替代品提出了新的挑战,关于什么样的资产,以最佳选择,以及如何做出这个决定。为了支持决策者,决策理论已被用于开发决策模型进行资产选择。然而,很少的工业数据已在文献中提出了有关用处,甚至感知有用性,这些车型。此外,只有有限的信息已经提交关于什么样的模式特点决定了对一个模型在另一名学员的偏好。这项工作的目的是评估哪些决策模型的特性资产选择确定模型的工业从业者优先给予高精度的决策模型或高速模式的选择时。这里一共有33名从业者,不同的角色,从18家公司的任务是比较两个决策模型进行资产选择是进行工业问卷调查。文本分析和正式的和描述性统计分析,然后应用在调查的答复来回答这项研究的研究问题。研究表明,从业者不得不向决策模型明显倾向于一个强调速度在一个强调决策精度。这一结论被确定为,因为这些模型的一个被认为快,有较低的复杂性,在使用了不同的决策更灵活,并且是在它如何能在操作中使用,其对人的重视,其重点更敏捷“足够好”的精度,如果决定是失败的快速失败的能力。因此,我们发现有7个特性的从业者认为他们的接受模式很重要。工业从业者的偏好,这涉及接受,决策模型的用于资产选择取决于必须开发用于不同类型的决定,如操作天到一天的决定以及更关键的战术或战略模型时,可以考虑多种特性决定。这项工作的主要贡献是七度识别的特点,可以作为今后决策模型研究了资产选择的工业要求。

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