Please wait ...
0% Complete
Home
/
13th International Conference on Computer and Knowledge Engineering
An Exploratory Study of the Relationship between SATD and Other Software Development Activities
Authors :
Shima Esfandiari
1
Ashkan Sami
2
1- Shiraz university
2- Shiraz university
Keywords :
Self-Admitted Technical Debt،Repository mining،Software refactoring،Bug fixing
Abstract :
Technical Debt is a common issue that arises when short-term gains are prioritized over long-term costs, leading to a degradation in the quality of the code. Self-Admitted Technical Debt (SATD) is a specific type of Technical Debt that involves documenting code to remind developers of its debt. Previous research has explored various aspects of SATD, including detection methods, distribution, and its impact on software quality. To better understand SATD, one comprehension technique is to examine its co-occurrence with other activities, such as refactoring and bug fixing. This study investigates the relationship between removing and adding SATD and activities such as refactoring, bug fixing, adding new features, and testing. To do so, we analyzed 77 open-source Java projects using TODO/FIXME/XXX removal or addition in inline comments as indicators of SATD. We examined the co-occurrence of SATD with each activity in each project through chi-square and odds ratio evaluations. Our results show that SATD removal occurs simultaneously with refactoring in 95% of projects, while its addition occurs in 89% of projects. Furthermore, we found that three types of refactoring - "move class", "remove method", and "move attribute" - occur more frequently in the presence of SATD. However, their distribution is similar in projects with and without SATD.
Papers List
List of archived papers
An Automated Visual Defect Segmentation for Flat Steel Surface Using Deep Neural Networks
Dorna Nourbakhsh Sabet - Mohammad Reza Zarifi - Javad Khoramdel - Yasamin Borhani - Esmaeil Najafi
Probabilistic Short-Term Load Forecasting Using GBDT-Based Sister Forecasts and Ensemble Methods
Hossein Shahinzadeh - Hamed Nafisi - Amirafshin Zamani - Saiedeh Mehrabani-Najafabadi - Arezou Mahmoudi - Farshad Ebrahimi
Attention-Boosted Ensemble of Pre-trained Convolutional Neural Networks for Accurate Diabetic Retinopathy Detection
Benyamin Mirab Golkhatmi - Mohammad Hossein Moattar
An effective hybrid algorithm for locating splicing forgery image
Seyed Hesamoddin Hosseini - Amene Vatanparast - Amir Hossein Taherinia
Adaptive-A-GCRNN: Enhancing Real-time Multi-band Spectrum Prediction through Attention-based Spatial-Temporal Modeling
Seyed majid Hosseini - Seyedeh Mozhgan Rahmatinia - Seyed Amin Hosseini Seno - Hadi Sadoghi yazdi
Intelligent Interpretation of Frequency Response Signatures to Diagnose Radial Deformation in Transformer Windings Using Artificial Neural Network
Reza Behkam - Hossein Karami - Mehdi Salay Naderi - Gevork B. Gharehpetian
Deep Learning-based Processing of Autonomous Vehicle Radar Data to Achieve High Resolution
Nima Abdolrahimi Shahamat - Vahideh Moghtadaiee - Esfandiar Mehrshahi
Explainable Error Detection Method for Structured Data using HoloDetect framework
Abolfazl Mohajeri Khorasani - Sahar Ghassabi - Behshid Behkamal - Mostafa Milani
Predicting cascading failure with machine learning methods in the interdependent networks
Mohamad Hossein Maghsoodi - Mohamad Khansari
Frame Classification in Video Capsule Endoscopy Using an Improved Capsule Network
Amirhossein Ghaemi - Habibollah Danyali - Alireza Ghaemi
more
Samin Hamayesh - Version 44.9.3