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The relationship between evolutionary coupling and defects in large industrial software.

, , , , , , and . Journal of Software: Evolution and Process, (2017)

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Issue ownership activity in two large software projects., and . ACM SIGSOFT Softw. Eng. Notes, 37 (6): 1-7 (2012)A success story in applying data science in practice., , , , and . Perspectives on Data Science for Software Engineering, Academic Press, (2016)A Novel Point of Interest (POI) Location Based Recommender System Utilizing User Location and Web Interactions., , , and . BigDataService, page 121-130. IEEE Computer Society, (2016)DeepAD: A Generic Framework Based on Deep Learning for Time Series Anomaly Detection., , and . PAKDD (1), volume 10937 of Lecture Notes in Computer Science, page 577-588. Springer, (2018)Predicting defective modules in different test phases., , , and . Softw. Qual. J., 23 (2): 205-227 (2015)Competition-Based Crowdsourcing Software Development: A Multi-Method Study from a Customer Perspective., , and . IEEE Trans. Software Eng., 45 (3): 237-260 (2019)Predicting bug-fixing time: A replication study using an open source software project., , and . J. Syst. Softw., (2018)ST-DenNetFus: A New Deep Learning Approach for Network Demand Prediction., , , and . ECML/PKDD (3), volume 11053 of Lecture Notes in Computer Science, page 222-237. Springer, (2018)Factors characterizing reopened issues: a case study., , , , and . PROMISE, page 1-10. ACM, (2012)The effect of evolutionary coupling on software defects: an industrial case study on a legacy system., , , , and . ESEM, page 6:1-6:7. ACM, (2014)