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Abstract: We evaluate a class of learning algorithms known as inductive logic programming (ILP) methods on the task of predicting fault occurrence in C++ classes. Using these methods, a large space of possible hypotheses is searched in an automated fashion; further, the hypotheses are based directly on an abstract logical representation of the software, rather than on manually proposed numerical metrics that predict fault density. We compare two ILP systems, FOIL and FLIPPER, and conclude that... (Update)
Context of citations to this paper: More
...when creating the model. Examples of the application of inductive or data mining methods, in software engineering include [1, 7, 8, 22, 25, 28, 33]. In this paper we discuss our research that applies inductive methods to aid software maintainers in some of their daily...
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BibTeX entry: (Update)
W. Cohen and P. Devanbu. Automatically Exploring Hypotheses about Fault Prediction: a Comparative Study of Inductive Logic Programming Methods. International Journal of Software Engineering and Knowledge Engineering, 1999. http://citeseer.ist.psu.edu/article/cohen99automatically.html More
@article{ cohen99automatically,
author = "W. W. Cohen and P. T. Devanbu",
title = "Automatically Exploring Hypotheses about Fault Prediction: {A} Comparative Study of Inductive Logic Programming Methods",
journal = "International Journal of Software Engineering and Knowledge Engineering",
volume = "9",
number = "5",
month = "October",
publisher = "World Scientific Publishing Company",
editor = "S. Morasca and G. Ruhe",
pages = "519--546",
year = "1999",
url = "citeseer.ist.psu.edu/article/cohen99automatically.html" }
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