即时软件缺陷预测研究进展
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摘要
软件缺陷预测一直是软件工程研究中最活跃的领域之一,研究人员己经提出了大量的缺陷预测技术,根据预测粒度不同,主要包括模块级、文件级和变更级(change-level)缺陷预测.其中,变更级缺陷预测旨在于开发者提交代码时,对其引入的代码是否存在缺陷进行预测,因此又被称作即时(just-in-time)缺陷预测.近年来,即时缺陷预测技术由于其即时性、细粒度等优势,成为缺陷预测领域的研究热点,取得了一系列研究成果;同时也在数据标注、特征提取、模型评估等环节面临诸多挑战,迫切需要更先进、统一的理论指导和技术支撑.鉴于此,从即时缺陷预测技术的数据标注、特征提取和模型评估等方面对近年来即时缺陷预测研究进展进行梳理和总结.主要内容包括:(1)归类并梳理了即时缺陷预测模型构建中数据标注常用方法及其优缺点;(2)对即时缺陷预测的特征类型和计算方法进行了详细分类和总结;(3)总结并归类现有模型构建技术;(4)总结了模型评估中使用的实验验证方法与性能评估指标;(5)归纳出了即时缺陷预测技术的关键问题;(6)最后展望了即时缺陷预测的未来发展.
Software defect prediction is always one of the most active research areas in software engineering. Researchers have proposed a lot of defect prediction techniques. These techniques consist of module-level, file-level, and change-level defect prediction according to the granularity. Change-level defect prediction can predict the defect-proneness of changes when they are initially submitted.Hence, such a technique is referred to as just-in-time defect prediction. Recently, just-in-time defect prediction becomes the hot area in defect prediction because of its timely manner and fine granularity. There are a lot of achievements in this area and there are also many challenges in data labeling, feature extraction, and model evaluation. More advanced and unified theoretic and technical guidelines are needed to enhance just-in-time defect prediction. Therefore, in this study, a literature review for prior just-in-time defect prediction studies is presented in three folds, data labeling, feature extraction, and model evaluation. In summary, the contributions of this study are:(1) The data labeling methods and their advantages and disadvantages are concluded;(2) The feature categories and computing methods are concluded and classified;(3) The modeling techniques are concluded and classified;(4) The model validation and performance measures in model evaluation are concluded;(5) The current problems in this area are highlighted; and(6) The trends of Just-in-Time defect prediction are concluded.
Software defect prediction is always one of the most active research areas in software engineering. Researchers have proposed a lot of defect prediction techniques. These techniques consist of module-level, file-level, and change-level defect prediction according to the granularity. Change-level defect prediction can predict the defect-proneness of changes when they are initially submitted.Hence, such a technique is referred to as just-in-time defect prediction. Recently, just-in-time defect prediction becomes the hot area in defect prediction because of its timely manner and fine granularity. There are a lot of achievements in this area and there are also many challenges in data labeling, feature extraction, and model evaluation. More advanced and unified theoretic and technical guidelines are needed to enhance just-in-time defect prediction. Therefore, in this study, a literature review for prior just-in-time defect prediction studies is presented in three folds, data labeling, feature extraction, and model evaluation. In summary, the contributions of this study are:(1) The data labeling methods and their advantages and disadvantages are concluded;(2) The feature categories and computing methods are concluded and classified;(3) The modeling techniques are concluded and classified;(4) The model validation and performance measures in model evaluation are concluded;(5) The current problems in this area are highlighted; and(6) The trends of Just-in-Time defect prediction are concluded.
引文
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