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Background: Many relevancy filters have been proposed to select training data for building cross-project defect prediction (CPDP) models. However, up to now, there is no consensus about which relevancy filter is better for CPDP. Goal: In this paper, we conduct a thorough experiment to compare nine relevancy filters proposed in the recent literature. Method: Based on 33 publicly available data sets,...
Background: An increasing research effort has devoted to just-in-time (JIT) defect prediction. A recent study by Yang et al. at FSE'16 leveraged individual change metrics to build unsupervised JIT defect prediction model. They found that many unsupervised models performed similarly to or better than the state-of-the-art supervised models in effort-aware JIT defect prediction. Goal: In Yang et al.'s...
When there exists not enough historical defect data for building accurate prediction model, semi-supervised defect prediction (SSDP) and cross-project defect prediction (CPDP) are two feasible solutions. Existing CPDP methods assume that the available source data is well labeled. However, due to expensive human efforts for labeling a large amount of defect data, usually, we can only make use of the...
Software effort estimation (SEE) is a crucial step in software development. Effort data missing usually occurs in real-world data collection. Focusing on the missing data problem, existing SEE methods employ the deletion, ignoring, or imputation strategy to address the problem, where the imputation strategy was found to be more helpful for improving the estimation performance. Current imputation methods...
A dependence cluster is a set of mutually inter-dependent program elements. Prior studies have found that large dependence clusters are prevalent in software systems. It has been suggested that dependence clusters have potentially harmful effects on software quality. However, little empirical evidence has been provided to support this claim. The study presented in this paper investigates the relationship...
A typical approach utilized for automated test case generation is to create a model of the implementation under test. Extended Finite State Machine (EFSM) is among the most popular models for model-based testing. However, automated test case generation on EFSM models is still a challenge task as a result of the fact that an EFSM model may contain infeasible paths. In this article we present a novel...
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