Detecting code smells using industry-relevant data

Automatic detection of Long Method and God Class code smells through neural source code embeddings

(2022) Aleksandar Kovačević et al.   EXPERT SYSTEMS WITH APPLICATIONS

The impact of using biased performance metrics on software defect prediction research

(2021) Jingxiu Yao et al.   INFORMATION AND SOFTWARE TECHNOLOGY

How far are we from reproducible research on code smell detection? A systematic literature review

(2021) Tomasz Lewowski et al.   INFORMATION AND SOFTWARE TECHNOLOGY

Machine learning techniques for code smell detection: A Systematic literature review and meta-Analysis

(2019) Muhammad Ilyas Azeem et al.   INFORMATION AND SOFTWARE TECHNOLOGY

Machine Learning Techniques for Code Smells Detection: A Systematic Mapping Study

(2019) Frederico Luiz Caram et al.   INTERNATIONAL JOURNAL OF SOFTWARE ENGINEERING AND KNOWLEDGE ENGINEERING

Meta-analysis for families of experiments in software engineering: a systematic review and reproducibility and validity assessment

(2019) Barbara Kitchenham et al.   EMPIRICAL SOFTWARE ENGINEERING

A systematic review on the code smell effect

(2018) José Amancio M. Santos et al.   JOURNAL OF SYSTEMS AND SOFTWARE

A Systematic Literature Review on Bad Smells–5 W's: Which, When, What, Who, Where

(2018) Elder Vicente de Paulo Sobrinho et al.   IEEE TRANSACTIONS ON SOFTWARE ENGINEERING

How developers perceive smells in source code: A replicated study

(2017) Davide Taibi et al.   INFORMATION AND SOFTWARE TECHNOLOGY

Would wider adoption of reproducible research be beneficial for empirical software engineering research?

(2017) Lech Madeyski et al.   JOURNAL OF INTELLIGENT & FUZZY SYSTEMS

Code smell severity classification using machine learning techniques

(2017) Francesca Arcelli Fontana et al.   KNOWLEDGE-BASED SYSTEMS

Robust Statistical Methods for Empirical Software Engineering

(2016) Barbara Kitchenham et al.   EMPIRICAL SOFTWARE ENGINEERING

Co-changing code volume prediction through association rule mining and linear regression model

(2016) Shin-Jie Lee et al.   EXPERT SYSTEMS WITH APPLICATIONS

Dynamic and Automatic Feedback-Based Threshold Adaptation for Code Smell Detection

(2016) Hui Liu et al.   IEEE TRANSACTIONS ON SOFTWARE ENGINEERING

Comparing and experimenting machine learning techniques for code smell detection

(2015) Francesca Arcelli Fontana et al.   EMPIRICAL SOFTWARE ENGINEERING

Mining Version Histories for Detecting Code Smells

(2015) Fabio Palomba et al.   IEEE TRANSACTIONS ON SOFTWARE ENGINEERING

Researcher Bias: The Use of Machine Learning in Software Defect Prediction

(2014) Martin Shepperd et al.   IEEE TRANSACTIONS ON SOFTWARE ENGINEERING

Which process metrics can significantly improve defect prediction models? An empirical study

(2014) Lech Madeyski et al.   SOFTWARE QUALITY JOURNAL

A survey on feature selection methods

(2013) Girish Chandrashekar et al.   COMPUTERS & ELECTRICAL ENGINEERING

A study of cyclic dependencies on defect profile of software components

(2013) Tosin Daniel Oyetoyan et al.   JOURNAL OF SYSTEMS AND SOFTWARE

Characteristics of multiple-component defects and architectural hotspots: a large system case study

(2011) Zude Li et al.   EMPIRICAL SOFTWARE ENGINEERING

DECOR: A Method for the Specification and Detection of Code and Design Smells

(2009) N. Moha et al.   IEEE TRANSACTIONS ON SOFTWARE ENGINEERING