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Context: Software development effort estimation (SDEE) is the process of predicting the effort required to develop a software system. In order to improve estimation accuracy, many researchers have proposed machine learning (ML) based SDEE models (ML models) since 1990s. However, there has been no attempt to analyze the empirical evidence on ML models in a(More)
Software development cost overruns often induce project managers to cut down manpower cost at the expense of software quality. Accurate effort estimation is beneficial to the prevention of cost overruns. Analogy-based effort estimation predicts the effort of a new project by using the information of its similar historical projects, where the similarity is(More)
—Requirements evolve continuously and inevitably. In order to effectively manage requirements change, an understanding from a quantitative perspective is needed in determining the extent of the propagation of the requirements as they evolve. In this paper, we first look back at the impact analysis in the software life cycle and give an overview of(More)
Traditionally, only " individual-independent " facts are inputted to a reasoner. The reasoner will produce the same answer to the same question, regardless of who the questioner is. However, since ontology reasoners have their facts distributed in the open internet environment, reasoners may contain " individual-dependent " facts. Personalized reasoner is(More)