Jianglin Huang

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Context: Due to the complex nature of software development process, traditional parametric models and statistical methods often appear to be inadequate to model the increasingly complicated relationship between project development cost and the project features (or cost drivers). Machine learning (ML) methods, with several reported successful applications,(More)
Software quality estimation is important yet difficult in software engineering studies. Historical quality datasets are used to build classification models for estimating fault-proneness. However, the missing values in the datasets severely affect the estimation ability and therefore, cause inconclusive decision-making. Among the single imputation(More)
Analogy-based software effort estimation is a method to estimate the project cost of an unseen project based on analogies against previous projects sharing selected features. The validity of the selected features depends on many factors, and one of most crucial factors is the effectiveness of the datapreprocessing techniques applied to the datasets of the(More)
A number of research efforts have focused in the area of programming style. However, to the best of our knowledge, there is little sound and solid evidence of how and to what extent can stylistic inconsistency impact the readability and maintainability of the source code. To bridge the research gap, we design an empirical experiment in which eye tracking(More)
Software quality prediction is an important yet difficult problem in software project development and management. Historical datasets can be used to build models for software quality prediction. However, the missing data significantly affects the prediction ability of models in knowledge discovery. Instead of ignoring missing observations, we investigate(More)
Several defect prediction models proposed are effective when historical datasets are available. Defect prediction becomes difficult when no historical data exist. Cross-project defect prediction (CPDP), which uses projects from other sources/companies to predict the defects in the target projects proposed in recent studies has shown promising results.(More)
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