Using Structured Text Source Code Metrics and Artificial Neural Networks to Predict Change Proneness at Code Tab and Program Organization Level-Reference-Cited by-同舟云学术

Using Structured Text Source Code Metrics and Artificial Neural Networks to Predict Change Proneness at Code Tab and Program Organization Level

Published:2017-02-05 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 10th Innovations in Software Engineering Conference
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Author:

Kumar Lov¹,Sureka Ashish¹

Affiliation:

1. ABB Corporate Research Center, Bangalore, India

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3021460.3021481

Reference13 articles.

1. Janez Demšar. Statistical comparisons of classifiers over multiple data sets. Journal of Machine learning research 7(Jan):1--30 2006. Janez Demšar. Statistical comparisons of classifiers over multiple data sets. Journal of Machine learning research 7(Jan):1--30 2006.

2. Feature Selection Based on the Rough Set Theory and Expectation-Maximization Clustering Algorithm

3. Identifying and characterizing change-prone classes in two large-scale open-source products

4. Source code metrics for programmable logic controller (PLC) ladder diagram (LD) visual programming language

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