Lov Kumar
Orcid: 0000-0002-0123-7822
According to our database1,
Lov Kumar
authored at least 90 papers
between 2015 and 2024.
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Bibliography
2024
A Codebert Based Empirical Framework for Evaluating Classification-Enabled Vulnerability Prediction Models.
Proceedings of the 17th Innovations in Software Engineering Conference, 2024
An Empirical Analysis on Leveraging User Reviews with NLP-Enhanced Word Embeddings for App Rating Prediction.
Proceedings of the Advanced Information Networking and Applications, 2024
Investigating BERT Layer Performance and SMOTE Through MLP-Driven Ablation on Gittercom.
Proceedings of the Advanced Information Networking and Applications, 2024
2023
Empirical evaluation of the performance of data sampling and feature selection techniques for software fault prediction.
Expert Syst. Appl., August, 2023
J. Comput. Lang., 2023
A Comparative Analysis on the Detection of Web Service Anti-Patterns Using Various Metrics.
Proceedings of the 16th Innovations in Software Engineering Conference, 2023
Automatic Identification of Video Game Development Problems using Word Embedding and Ensemble Classifiers.
Proceedings of the 16th Innovations in Software Engineering Conference, 2023
Empirical Analysis of Multi-label Classification on GitterCom Using BERT and ML Classifiers.
Proceedings of the Neural Information Processing - 30th International Conference, 2023
An Empirical Framework for Software Aging-Related Bug Prediction using Weighted Extreme Learning Machine.
Proceedings of the Communication Papers of the 18th Conference on Computer Science and Intelligence Systems, 2023
Comparative Analysis of Word Embedding and Machine Learning Techniques for Classification of Software Developer Communications on Gitter.
Proceedings of the 18th Conference on Computer Science and Intelligence Systems, 2023
Empirical Analysis for Investigating the Effect of Machine Learning Techniques on Malware Prediction.
Proceedings of the 18th International Conference on Evaluation of Novel Approaches to Software Engineering, 2023
Software Engineering Comments Sentiment Analysis Using LSTM with Various Padding Sizes.
Proceedings of the 18th International Conference on Evaluation of Novel Approaches to Software Engineering, 2023
Proceedings of the OITS International Conference on Information Technology, 2023
2022
Cross-Project Software Refactoring Prediction Using Optimized Deep Learning Neural Network With the Aid of Attribute Selection.
Int. J. Open Source Softw. Process., 2022
Comput. Stand. Interfaces, 2022
Automatic Identification of Class Level Refactoring Using Abstract Syntax Tree and Embedding Technique.
Proceedings of the Neural Information Processing - 29th International Conference, 2022
Proceedings of the Computational Science and Its Applications - ICCSA 2022 Workshops, 2022
Proceedings of the Computational Science and Its Applications - ICCSA 2022 Workshops, 2022
COVID-19 Article Classification Using Word-Embedding and Different Variants of Deep-Learning Approach.
Proceedings of the Applied Informatics: 5th International Conference, 2022
Software Requirements Classification using Deep-learning Approach with Various Hidden Layers.
Proceedings of the 17th Conference on Computer Science and Intelligence Systems, 2022
Software Sentiment Analysis using Deep-learning Approach with Word-Embedding Techniques.
Proceedings of the 17th Conference on Computer Science and Intelligence Systems, 2022
COVID-19 Article Classification Using Word-Embedding and Extreme Learning Machine with Various Kernels.
Proceedings of the Advanced Information Networking and Applications, 2022
Proceedings of the Advanced Information Networking and Applications, 2022
Software Functional and Non-function Requirement Classification Using Word-Embedding.
Proceedings of the Advanced Information Networking and Applications, 2022
Predicting Cyber-Attacks on IoT Networks Using Deep-Learning and Different Variants of SMOTE.
Proceedings of the Advanced Information Networking and Applications, 2022
2021
An Empirical Study for Method-Level Refactoring Prediction by Ensemble Technique and SMOTE to Improve Its Efficiency.
Int. J. Open Source Softw. Process., 2021
An Empirical Study to investigate the Effectiveness of Different Variants of SMOTE for Improving Web Service Anti-Patterns Prediction.
Proceedings of the ISEC 2021: 14th Innovations in Software Engineering Conference, 2021
Predicting Software Defect Severity Level Using Deep-Learning Approach with Various Hidden Layers.
Proceedings of the Neural Information Processing - 28th International Conference, 2021
Prediction of Video Game Development Problems Based on Postmortems using Different Word Embedding Techniques.
Proceedings of the 18th International Conference on Natural Language Processing (ICON 2021), National Institute of Technology Silchar, Silchar, India, December 16, 2021
An Empirical Analysis on the Prediction of Web Service Anti-patterns Using Source Code Metrics and Ensemble Techniques.
Proceedings of the Computational Science and Its Applications - ICCSA 2021, 2021
A Novel Approach for the Detection of Web Service Anti-Patterns Using Word Embedding Techniques.
Proceedings of the Computational Science and Its Applications - ICCSA 2021, 2021
Deep-Learning Approach with DeepXplore for Software Defect Severity Level Prediction.
Proceedings of the Computational Science and Its Applications - ICCSA 2021, 2021
Proceedings of the Computational Science and Its Applications - ICCSA 2021, 2021
An Ensemble Model for Sentiment Classification on Code-Mixed Data in Dravidian Languages.
Proceedings of the Working Notes of FIRE 2021, 2021
An Empirical Study on Application of Word Embedding Techniques for Prediction of Software Defect Severity Level.
Proceedings of the 16th Conference on Computer Science and Intelligence Systems, 2021
Predicting Software Defect Severity Level using Sentence Embedding and Ensemble Learning.
Proceedings of the 47th Euromicro Conference on Software Engineering and Advanced Applications, 2021
An Empirical Study on Predictability of Software Code Smell Using Deep Learning Models.
Proceedings of the Advanced Information Networking and Applications, 2021
2020
Prediction of Web Service Anti-patterns Using Aggregate Software Metrics and Machine Learning Techniques.
Proceedings of the ISEC 2020: 13th Innovations in Software Engineering Conference, 2020
An Empirical Study to Investigate Data Sampling Techniques for Improving Code-Smell Prediction Using Imbalanced Data.
Proceedings of the Information and Communication Technology and Applications, 2020
Proceedings of the Neural Information Processing - 27th International Conference, 2020
An Empirical Study to Investigate Different SMOTE Data Sampling Techniques for Improving Software Refactoring Prediction.
Proceedings of the Neural Information Processing - 27th International Conference, 2020
An Empirical Analysis on the Role of WSDL Metrics in Web Service Anti-Pattern Prediction.
Proceedings of the 22nd IEEE International Conference on High Performance Computing and Communications; 18th IEEE International Conference on Smart City; 6th IEEE International Conference on Data Science and Systems, 2020
2019
Quality of service (QoS) parameters prediction for web services using hybrid neural network and ensemble methods.
Int. J. Syst. Assur. Eng. Manag., 2019
Estimation of maintainability parameters for object-oriented software using hybrid neural network and class level metrics.
Int. J. Syst. Assur. Eng. Manag., 2019
Software reusability metrics prediction and cost estimation by using machine learning algorithms.
Int. J. Knowl. Based Intell. Eng. Syst., 2019
An EmpiricalAnalysis on Effectiveness of Source Code Metrics for Models Predicting Aging Related Bug.
J. Vis. Lang. Comput., 2019
A Three Dimensional Empirical Study of Logging Questions From Six Popular Q&A Websites.
e Informatica Softw. Eng. J., 2019
Proceedings of the Machine Learning for Networking, 2019
Method Level Refactoring Prediction on Five Open Source Java Projects using Machine Learning Techniques.
Proceedings of the 12th Innovations on Software Engineering Conference (formerly known as India Software Engineering Conference), 2019
Change-Proneness of Object-Oriented Software Using Combination of Feature Selection Techniques and Ensemble Learning Techniques.
Proceedings of the 12th Innovations on Software Engineering Conference (formerly known as India Software Engineering Conference), 2019
Proceedings of the Neural Information Processing - 26th International Conference, 2019
An Empirical Analysis on Effectiveness of Source Code Metrics for Aging Related Bug Prediction.
Proceedings of the 25th International DMS Conference on Visualization and Visual Languages, 2019
Proceedings of the 26th Asia-Pacific Software Engineering Conference, 2019
Android Malware Prediction Using Extreme Learning Machine with Different Kernel Functions.
Proceedings of the AINTEC '19, 2019
2018
An effective fault prediction model developed using an extreme learning machine with various kernel methods.
Frontiers Inf. Technol. Electron. Eng., 2018
Effective fault prediction model developed using Least Square Support Vector Machine (LSSVM).
J. Syst. Softw., 2018
Proceedings of the 30th International Conference on Software Engineering and Knowledge Engineering, 2018
Feature Selection Techniques to Counter Class Imbalance Problem for Aging Related Bug Prediction: Aging Related Bug Prediction.
Proceedings of the 11th Innovations in Software Engineering Conference, ISEC 2018, Hyderabad, India, February 09, 2018
Application of SMOTE and LSSVM with Various Kernels for Predicting Refactoring at Method Level.
Proceedings of the Neural Information Processing - 25th International Conference, 2018
An Empirical Analysis on Web Service Anti-pattern Detection Using a Machine Learning Framework.
Proceedings of the 2018 IEEE 42nd Annual Computer Software and Applications Conference, 2018
2017
The impact of feature selection on maintainability prediction of service-oriented applications.
Serv. Oriented Comput. Appl., 2017
ACM SIGSOFT Softw. Eng. Notes, 2017
Transfer Learning for Cross-Project Change-Proneness Prediction in Object-Oriented Software Systems: A Feasibility Analysis.
ACM SIGSOFT Softw. Eng. Notes, 2017
Software maintainability prediction using hybrid neural network and fuzzy logic approach with parallel computing concept.
Int. J. Syst. Assur. Eng. Manag., 2017
Empirical validation for effectiveness of fault prediction technique based on cost analysis framework.
Int. J. Syst. Assur. Eng. Manag., 2017
Maintainability prediction of web service using support vector machine with various kernel methods.
Int. J. Syst. Assur. Eng. Manag., 2017
An empirical analysis of the effectiveness of software metrics and fault prediction model for identifying faulty classes.
Comput. Stand. Interfaces, 2017
A Comparative Study of Different Source Code Metrics and Machine Learning Algorithms for Predicting Change Proneness of Object Oriented Systems.
CoRR, 2017
CoRR, 2017
Using source code metrics to predict change-prone web services: A case-study on ebay services.
Proceedings of the 2017 IEEE Workshop on Machine Learning Techniques for Software Quality Evaluation, 2017
Using Structured Text Source Code Metrics and Artificial Neural Networks to Predict Change Proneness at Code Tab and Program Organization Level.
Proceedings of the 10th Innovations in Software Engineering Conference, 2017
Empirical Analysis on Effectiveness of Source Code Metrics for Predicting Change-Proneness.
Proceedings of the 10th Innovations in Software Engineering Conference, 2017
Proceedings of the Computational Science and Its Applications - ICCSA 2017, 2017
Neural network with multiple training methods for web service quality of service parameter prediction.
Proceedings of the Tenth International Conference on Contemporary Computing, 2017
Analyzing fault prediction usefulness from cost perspective using source code metrics.
Proceedings of the Tenth International Conference on Contemporary Computing, 2017
Using Source Code Metrics and Multivariate Adaptive Regression Splines to Predict Maintainability of Service Oriented Software.
Proceedings of the 18th IEEE International Symposium on High Assurance Systems Engineering, 2017
An Empirical Analysis on Effective Fault Prediction Model Developed Using Ensemble Methods.
Proceedings of the 41st IEEE Annual Computer Software and Applications Conference, 2017
Application of LSSVM and SMOTE on Seven Open Source Projects for Predicting Refactoring at Class Level.
Proceedings of the 24th Asia-Pacific Software Engineering Conference, 2017
Estimating Web Service Quality of Service Parameters using Source Code Metrics and LSSVM.
Proceedings of the 5th International Workshop on Quantitative Approaches to Software Quality co-located with 24th Asia-Pacific Software Engineering Conference (APSEC 2017), 2017
2016
Hybrid functional link artificial neural network approach for predicting maintainability of object-oriented software.
J. Syst. Softw., 2016
A Bibliometric Study of Asia Pacific Software Engineering Conference from 2010 to 2015.
CoRR, 2016
Thirteen Years of Mining Software Repositories (MSR) Conference - What is the Bibliography Data Telling Us?
CoRR, 2016
Source code metrics for programmable logic controller (PLC) ladder diagram (LD) visual programming language.
Proceedings of the 7th International Workshop on Emerging Trends in Software Metrics, 2016
Proceedings of the 23rd Asia-Pacific Software Engineering Conference, 2016
Predicting Quality of Service (QoS) Parameters using Extreme Learning Machines with Various Kernel Methods.
Proceedings of the Joint Proceedings of the 4th International Workshop on Quantitative Approaches to Software Quality (QuASoQ 2016) and 1st International Workshop on Technical Debt Analytics (TDA 2016) co-located with the 23rd Asia-Pacific Software Engineering Conference (APSEC 2016), 2016
2015
Predicting Object-Oriented Software Maintainability using Hybrid Neural Network with Parallel Computing Concept.
Proceedings of the 8th India Software Engineering Conference, 2015
Proceedings of the 2015 Asia-Pacific Software Engineering Conference, 2015