Change Impact Analysis (CIA) is the process of exploring the tentative effects of a change in other parts of a system. CIA is considered beneficial in practice, since it reduces cost of maintenance and the risk of software development failures. In this paper, we present a systematic mapping study that covers a plethora of CIA methods (by exploring 111 papers), putting special emphasis on how the CIA phenomenon can be quantified: to be efficiently managed. The results of our study suggest that: (a) the practical benefits of CIA cover any type of maintenance request (e.g., feature additions, bug fixing) and can help in reducing relevant cost; (b) CIA quantification relies on four parameters (instability, amount of change, change proneness, and changeability), whose assessment is supported by various metrics and predictors; and (c) in this vast research field, there are still some viewpoints that remain unexplored (e.g., the negative consequences of highly change prone artifacts), whereas others are over-researched (e.g., quantification of instability based on metrics). Based on our results, we provide: (a) useful information for practitioners—i.e., the expected benefits of CIA, and a list of CIA-related metrics, emphasizing on the provision of a detailed interpretation of their relation to CIA; and (b) interesting future research directions—i.e., over- and under-researched sub-fields of CIA.

变更影响分析（CIA）是探索变更对系统其他部分的影响的过程。CIA在实践中被认为是有益的，因为它降低了维护成本和软件开发失败的风险。在本文中，我们提出了系统的制图研究，涵盖了多种CIA方法（探索111篇论文），并特别强调了如何量化CIA现象：如何有效管理。我们的研究结果表明：（a）CIA的实际好处可以满足任何类型的维护要求（例如，功能增加，错误修复），并且可以帮助降低相关成本；（b）中央情报局的量化取决于四个参数（不稳定，变化量，变化倾向性和可变性），其评估得到各种指标和预测因素的支持；（c）在这个广阔的研究领域中，仍然有一些观点尚未得到探索（例如，高度易变工件的负面影响），而另一些观点则得到了过度研究（例如，基于指标的不稳定性量化）。根据我们的结果，我们提供：（a）为从业人员提供有用的信息，即CIA的预期收益以及CIA相关指标的列表，重点是提供他们与CIA关系的详细解释；（b）有趣的未来研究方向，即对CIA子领域的研究过多和研究不足。（a）对从业人员的有用信息，即中央情报局的预期收益以及与中央情报局有关的指标清单，重点是提供对其与中央情报局关系的详细解释；（b）有趣的未来研究方向，即对CIA子领域的研究过多和研究不足。（a）对从业人员的有用信息，即中央情报局的预期收益以及与中央情报局有关的指标清单，重点是提供对其与中央情报局关系的详细解释；（b）有趣的未来研究方向，即对CIA子领域的研究过多和研究不足。