CNN-based bug positioning method combining source code semantics and grammatical features
A positioning method and source code technology, applied in the direction of code compilation, program code conversion, neural learning method, etc., can solve the problem of high cost of manual bug positioning, and achieve the effect of promoting the overall maintenance level, improving the maintenance efficiency, and reducing the time cost.
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[0019] Several key technologies involved in the present invention are related knowledge and technologies of word2vec word vector model, convolutional neural network, natural language processing technology, gradient descent algorithm and abstract syntax tree extraction.
[0020] 1. word2vec word embedding model
[0021] Word vectors are vectors used to represent words, and can also be considered as feature vectors of words. The technique of mapping words into real number field vectors is also called word embedding. word2vec represents each word as a fixed-length vector, and enables these vectors to better express the similarity and analogy between different words. word2vec contains two models: Skip-gram and CBOW (continuousbagofwords). In the present invention, mainly use the Skip-gram model in word2vec to carry out word embedding to bug report and source code.
[0022] 2. Natural language processing tools and technologies
[0023] Natural Language Processing (NLP) is a subd...
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