Quality Assessment of Web Services Using Multivariate Adaptive Regression Splines. - Lov Kumar; Santanu Kumar Rath (APSEC, 2015)

Predicting Object-Oriented Software Maintainability using Hybrid Neural Network with Parallel Computing Concept. - Lov Kumar; Santanu Ku. Rath (ISEC, 2015)

Predicting Quality of Service (QoS) Parameters using Extreme Learning Machines with Various Kernel Methods. - Lov Kumar; Santanu Kumar Rath; Ashish Sureka (QuASoQ/TDA@APSEC, 2016)

A Review of Six Years of Asia-Pacific Software Engineering Conference. - Lov Kumar; Saikrishna Sripada; Ashish Sureka (APSEC, 2016)

Source code metrics for programmable logic controller (PLC) ladder diagram (LD) visual programming language. - Lov Kumar; Raoul Jetley; Ashish Sureka (WETSoM@ICSE, 2016)

Thirteen Years of Mining Software Repositories (MSR) Conference - What is the Bibliography Data Telling Us? - Lov Kumar; Ashish Sureka (CoRR, 2016)

A Bibliometric Study of Asia Pacific Software Engineering Conference from 2010 to 2015. - Lov Kumar; Saikrishna Sripada; Ashish Sureka (CoRR, 2016)

Hybrid functional link artificial neural network approach for predicting maintainability of object-oriented software. - Lov Kumar; Santanu Ku. Rath (J. Syst. Softw., 2016)

Estimating Web Service Quality of Service Parameters using Source Code Metrics and LSSVM. - Lov Kumar; Santanu Kumar Rath; Ashish Sureka (QuASoQ@APSEC, 2017)

Application of LSSVM and SMOTE on Seven Open Source Projects for Predicting Refactoring at Class Level. - Lov Kumar; Ashish Sureka (APSEC, 2017)

An Empirical Analysis on Effective Fault Prediction Model Developed Using Ensemble Methods. - Lov Kumar; Santanu Kumar Rath; Ashish Sureka (COMPSAC (1), 2017)

Using Source Code Metrics and Multivariate Adaptive Regression Splines to Predict Maintainability of Service Oriented Software. - Lov Kumar; Santanu Kumar Rath; Ashish Sureka (HASE, 2017)

Analyzing fault prediction usefulness from cost perspective using source code metrics. - Lov Kumar; Ashish Sureka (IC3, 2017)

Neural network with multiple training methods for web service quality of service parameter prediction. - Lov Kumar; Ashish Sureka (IC3, 2017)

Nearness and Influence Based Link Prediction (NILP) in Distributed Platform. - Ranjan Kumar Behera; Lov Kumar; Monalisa Jena; Sambit Mahapatra; Abhishek Sai Shukla; Santanu Kumar Rath (ICCSA (6), 2017)

Empirical Analysis on Effectiveness of Source Code Metrics for Predicting Change-Proneness. - Lov Kumar; Santanu Kumar Rath; Ashish Sureka (ISEC, 2017)

Using Structured Text Source Code Metrics and Artificial Neural Networks to Predict Change Proneness at Code Tab and Program Organization Level. - Lov Kumar; Ashish Sureka (ISEC, 2017)

Using source code metrics to predict change-prone web services: A case-study on ebay services. - Lov Kumar; Santanu Kumar Rath; Ashish Sureka (MaLTeSQuE, 2017)

Using Source Code Metrics and Ensemble Methods for Fault Proneness Prediction. - Lov Kumar; Santanu Kumar Rath; Ashish Sureka (CoRR, 2017)

A Comparative Study of Different Source Code Metrics and Machine Learning Algorithms for Predicting Change Proneness of Object Oriented Systems. - Lov Kumar; Ashish Sureka (CoRR, 2017)

An empirical analysis of the effectiveness of software metrics and fault prediction model for identifying faulty classes. - Lov Kumar; Sanjay Misra; Santanu Ku. Rath (Comput. Stand. Interfaces, 2017)

Maintainability prediction of web service using support vector machine with various kernel methods. - Lov Kumar; Mukesh Kumar 005; Santanu Ku. Rath (Int. J. Syst. Assur. Eng. Manag., 2017)

Empirical validation for effectiveness of fault prediction technique based on cost analysis framework. - Lov Kumar; Santanu Ku. Rath (Int. J. Syst. Assur. Eng. Manag., 2017)

Software maintainability prediction using hybrid neural network and fuzzy logic approach with parallel computing concept. - Lov Kumar; Santanu Ku. Rath (Int. J. Syst. Assur. Eng. Manag., 2017)

Transfer Learning for Cross-Project Change-Proneness Prediction in Object-Oriented Software Systems: A Feasibility Analysis. - Lov Kumar; Ranjan Kumar Behera; Santanu Kumar Rath; Ashish Sureka (ACM SIGSOFT Softw. Eng. Notes, 2017)

A Bibliometric Study of ACM SIGSOFT Software Engineering Notes from 2007 to 2016. - Lov Kumar; Ranjan Kumar Behera; Santanu Kumar Rath; Ashish Sureka (ACM SIGSOFT Softw. Eng. Notes, 2017)

The impact of feature selection on maintainability prediction of service-oriented applications. - Lov Kumar; Aneesh Krishna; Santanu Ku. Rath (Serv. Oriented Comput. Appl., 2017)

An Empirical Analysis on Web Service Anti-pattern Detection Using a Machine Learning Framework. - Lov Kumar; Ashish Sureka (COMPSAC (1), 2018)

Application of SMOTE and LSSVM with Various Kernels for Predicting Refactoring at Method Level. - Lov Kumar; Shashank Mouli Satapathy; Aneesh Krishna (ICONIP (5), 2018)

Feature Selection Techniques to Counter Class Imbalance Problem for Aging Related Bug Prediction: Aging Related Bug Prediction. - Lov Kumar; Ashish Sureka (ISEC, 2018)

Bayesian Logistic Regression for software defect prediction (S). - Jinu M. Sunil; Lov Kumar; Lalita Bhanu Murthy Neti (SEKE, 2018)

Effective fault prediction model developed using Least Square Support Vector Machine (LSSVM). - Lov Kumar; Saikrishna Sripada; Ashish Sureka; Santanu Ku. Rath (J. Syst. Softw., 2018)

An effective fault prediction model developed using an extreme learning machine with various kernel methods. - Lov Kumar; Anand Tirkey; Santanu Ku. Rath (Frontiers Inf. Technol. Electron. Eng., 2018)

Android Malware Prediction Using Extreme Learning Machine with Different Kernel Functions. - Lov Kumar; Chinmay Hota; Arvind Mahindru; Lalita Bhanu Murthy Neti (AINTEC, 2019)

Anatomizing Android Malwares. - Anand Tirkey; Ramesh Kumar Mohapatra; Lov Kumar (APSEC, 2019)

An Empirical Analysis on Effectiveness of Source Code Metrics for Aging Related Bug Prediction. - Chinmay Hota; Lov Kumar; Lalita Bhanu Murthy Neti (DMSVIVA, 2019)

Prediction of Refactoring-Prone Classes Using Ensemble Learning. - Vamsi Krishna Aribandi; Lov Kumar; Lalita Bhanu Murthy Neti; Aneesh Krishna (ICONIP (5), 2019)

Change-Proneness of Object-Oriented Software Using Combination of Feature Selection Techniques and Ensemble Learning Techniques. - Lov Kumar; Sangeeta Lal; Anjali Goyal; N. L. Bhanu Murthy (ISEC, 2019)

Method Level Refactoring Prediction on Five Open Source Java Projects using Machine Learning Techniques. - Lov Kumar; Shashank Mouli Satapathy; Lalita Bhanu Murthy Neti (ISEC, 2019)

A Novel Approach Towards Analysis of Attacker Behavior in DDoS Attacks. - Himanshu Gupta; Tanmay Girish Kulkarni; Lov Kumar; Lalita Bhanu Murthy Neti (MLN, 2019)

An Evolutionary GA-Based Approach for Community Detection in IoT. - Sanket Mishra; Chinmay Hota; Lov Kumar; Abhaya Nayak (IEEE Access, 2019)

A Three Dimensional Empirical Study of Logging Questions From Six Popular Q&A Websites. - Harshit Gujral; Abhinav Sharma; Sangeeta Lal; Lov Kumar (e Informatica Softw. Eng. J., 2019)

An EmpiricalAnalysis on Effectiveness of Source Code Metrics for Models Predicting Aging Related Bug. - Chinmay Hota; Lov Kumar; Lalita Bhanu Murthy Neti (J. Vis. Lang. Comput., 2019)

Software reusability metrics prediction and cost estimation by using machine learning algorithms. - Rasmita Panigrahi; Sanjay K. Kuanar; Lov Kumar; Neelamadhab Padhy; Suresh Chandra Satapathy (Int. J. Knowl. Based Intell. Eng. Syst., 2019)

Estimation of maintainability parameters for object-oriented software using hybrid neural network and class level metrics. - Lov Kumar; Sangeeta Lal; Lalita Bhanu Murthy Neti (Int. J. Syst. Assur. Eng. Manag., 2019)

Quality of service (QoS) parameters prediction for web services using hybrid neural network and ensemble methods. - Lov Kumar; Ashish Sureka (Int. J. Syst. Assur. Eng. Manag., 2019)

An Empirical Analysis on the Role of WSDL Metrics in Web Service Anti-Pattern Prediction. - Sahithi Tummalapalli; Lov Kumar; Lalita Bhanu Murthy Neti; Aneesh Krishna (HPCC/DSS/SmartCity, 2020)

An Empirical Study to Investigate Different SMOTE Data Sampling Techniques for Improving Software Refactoring Prediction. - Rasmita Panigrahi; Lov Kumar; Sanjay Kumar Kuanar (ICONIP (4), 2020)

Detection of Web Service Anti-patterns Using Neural Networks with Multiple Layers. - Sahithi Tummalapalli; Lov Kumar; N. L. Bhanu Murthy; Aneesh Krishna (ICONIP (5), 2020)

An Empirical Study to Investigate Data Sampling Techniques for Improving Code-Smell Prediction Using Imbalanced Data. - Himanshu Gupta; Sanjay Misra; Lov Kumar; N. L. Bhanu Murthy (ICTA, 2020)

Prediction of Web Service Anti-patterns Using Aggregate Software Metrics and Machine Learning Techniques. - Sahithi Tummalapalli; Lov Kumar; N. L. Bhanu Murthy (ISEC, 2020)

An Empirical Study on Predictability of Software Code Smell Using Deep Learning Models. - Himanshu Gupta; Tanmay Girish Kulkarni; Lov Kumar; Lalita Bhanu Murthy Neti; Aneesh Krishna (AINA (2), 2021)

Predicting Software Defect Severity Level using Sentence Embedding and Ensemble Learning. - Lov Kumar; Prakhar Gupta; Lalita Bhanu Murthy Neti; Santanu Ku. Rath; Shashank Mouli Satapathy; Vipul Kocher; Srinivas Padmanabhuni (SEAA, 2021)

An Empirical Study on Application of Word Embedding Techniques for Prediction of Software Defect Severity Level. - Lov Kumar; Mukesh Kumar 005; Lalita Bhanu Murthy Neti; Sanjay Misra; Vipul Kocher; Srinivas Padmanabhuni (FedCSIS, 2021)

An Ensemble Model for Sentiment Classification on Code-Mixed Data in Dravidian Languages. - S. R. Mithun Kumar; Nihal Reddy; Aruna Malapati; Lov Kumar (FIRE (Working Notes), 2021)

Empirical Analysis on Effectiveness of NLP Methods for Predicting Code Smell. - Himanshu Gupta; Abhiram Anand Gulanikar; Lov Kumar; Lalita Bhanu Murthy Neti (ICCSA (9), 2021)

Deep-Learning Approach with DeepXplore for Software Defect Severity Level Prediction. - Lov Kumar; Triyasha Ghosh Dastidar; Lalita Bhanu Murthy Neti; Shashank Mouli Satapathy; Sanjay Misra; Vipul Kocher; Srinivas Padmanabhuni (ICCSA (7), 2021)

A Novel Approach for the Detection of Web Service Anti-Patterns Using Word Embedding Techniques. - Sahithi Tummalapalli; Lov Kumar; Lalita Bhanu Murthy Neti; Vipul Kocher; Srinivas Padmanabhuni (ICCSA (7), 2021)

An Empirical Analysis on the Prediction of Web Service Anti-patterns Using Source Code Metrics and Ensemble Techniques. - Sahithi Tummalapalli; Juhi Mittal; Lov Kumar; Lalita Bhanu Murthy Neti; Santanu Kumar Rath (ICCSA (7), 2021)

Prediction of Video Game Development Problems Based on Postmortems using Different Word Embedding Techniques. - Anirudh A; Aman RAJ Singh; Anjali Goyal; Lov Kumar; N. L. Bhanu Murthy (ICON, 2021)

Predicting Software Defect Severity Level Using Deep-Learning Approach with Various Hidden Layers. - Lov Kumar; Triyasha Ghosh Dastidar; Anjali Goyal; Lalita Bhanu Murthy Neti; Sanjay Misra; Vipul Kocher; Srinivas Padmanabhuni (ICONIP (6), 2021)

An Empirical Study to investigate the Effectiveness of Different Variants of SMOTE for Improving Web Service Anti-Patterns Prediction. - Sahithi Tummalapalli; Lov Kumar; Lalita Bhanu Murthy Neti; Santanu Kumar Rath (ISEC, 2021)

An Empirical Study for Method-Level Refactoring Prediction by Ensemble Technique and SMOTE to Improve Its Efficiency. - Rasmita Panigrahi; Sanjay Kumar Kuanar; Lov Kumar (Int. J. Open Source Softw. Process., 2021)

Predicting Cyber-Attacks on IoT Networks Using Deep-Learning and Different Variants of SMOTE. - Bathini Sai Akash; Pavan Kumar Reddy Yannam; Bokkasam Venkata Sai Ruthvik; Lov Kumar; Lalita Bhanu Murthy Neti; Aneesh Krishna (AINA (2), 2022)

Software Functional and Non-function Requirement Classification Using Word-Embedding. - Lov Kumar; Siddarth Baldwa; Shreya Manish Jambavalikar; Lalita Bhanu Murthy Neti; Aneesh Krishna (AINA (2), 2022)

Web Service Anti-patterns Prediction Using LSTM with Varying Embedding Sizes. - Sahithi Tummalapalli; Lov Kumar; Lalita Bhanu Murthy Neti (AINA (1), 2022)

COVID-19 Article Classification Using Word-Embedding and Extreme Learning Machine with Various Kernels. - Sanidhya Vijayvargiya; Lov Kumar; Aruna Malapati; Lalita Bhanu Murthy Neti; Aneesh Krishna (AINA (3), 2022)

Software Sentiment Analysis using Deep-learning Approach with Word-Embedding Techniques. - Venkata Krishna Chandra Mula; Lov Kumar; Lalita Bhanu Murthy Neti; Aneesh Krishna (FedCSIS, 2022)

Software Requirements Classification using Deep-learning Approach with Various Hidden Layers. - Sanidhya Vijayvargiya; Lov Kumar; Lalita Bhanu Murthy Neti; Sanjay Misra (FedCSIS, 2022)

COVID-19 Article Classification Using Word-Embedding and Different Variants of Deep-Learning Approach. - Sanidhya Vijayvargiya; Lov Kumar; Lalita Bhanu Murthy Neti; Sanjay Misra (ICAI, 2022)

Software Sentiment Analysis Using Machine Learning with Different Word-Embedding. - Venkata Krishna Chandra Mula; Sanidhya Vijayvargiya; Lov Kumar; Surender Singh Samant; N. L. Bhanu Murthy (ICCSA (Workshops 5), 2022)

Software Functional Requirements Classification Using Ensemble Learning. - Sanidhya Vijayvargiya; Lov Kumar; Aruna Malapati; N. L. Bhanu Murthy; Sanjay Misra (ICCSA (Workshops 5), 2022)

Automatic Identification of Class Level Refactoring Using Abstract Syntax Tree and Embedding Technique. - Rasmita Panigrahi; Sanjay K. Kuanar; Lov Kumar (ICONIP (3), 2022)

Detection of web service anti-patterns using weighted extreme learning machine. - Sahithi Tummalapalli; Lov Kumar; Lalita Bhanu Murthy Neti; Aneesh Krishna (Comput. Stand. Interfaces, 2022)

Cross-Project Software Refactoring Prediction Using Optimized Deep Learning Neural Network With the Aid of Attribute Selection. - Rasmita Panigrahi; Sanjay Kumar Kuanar; Lov Kumar (Int. J. Open Source Softw. Process., 2022)

An Empirical Framework for Malware Prediction Using Multi-Layer Perceptron. - Vikram Singh 005; Lov Kumar; Anoop Kumar Patel; Aneesh Krishna (OCIT, 2023)

Software Engineering Comments Sentiment Analysis Using LSTM with Various Padding Sizes. - Sanidhya Vijayvargiya; Lov Kumar; Lalita Bhanu Murthy Neti; Sanjay Misra; Aneesh Krishna; Srinivas Padmanabhuni (ENASE, 2023)

Empirical Analysis for Investigating the Effect of Machine Learning Techniques on Malware Prediction. - Sanidhya Vijayvargiya; Lov Kumar; Lalita Bhanu Murthy Neti; Sanjay Misra; Aneesh Krishna; Srinivas Padmanabhuni (ENASE, 2023)

Comparative Analysis of Word Embedding and Machine Learning Techniques for Classification of Software Developer Communications on Gitter. - Tumu Akshar; Lov Kumar; Yogita; Lalita Bhanu Murthy Neti (FedCSIS, 2023)

An Empirical Framework for Software Aging-Related Bug Prediction using Weighted Extreme Learning Machine. - Lov Kumar; Vikram Singh 005; Lalita Bhanu Murthy Neti; Sanjay Misra; Aneesh Krishna (FedCSIS (Communication Papers), 2023)

Empirical Analysis of Multi-label Classification on GitterCom Using BERT and ML Classifiers. - Bathini Sai Akash; Lov Kumar; Vikram Singh 005; Anoop Kumar Patel; Aneesh Krishna (ICONIP (5), 2023)

Automatic Identification of Video Game Development Problems using Word Embedding and Ensemble Classifiers. - Anirudh A; Lov Kumar; N. L. Bhanu Murthy; Aneesh Krishna (ISEC, 2023)

A Comparative Analysis on the Detection of Web Service Anti-Patterns Using Various Metrics. - Sahithi Tummalapalli; Lov Kumar; Lalita Bhanu Murthy Neti; Aneesh Krishna (ISEC, 2023)

New Results on Single User Massive MIMO. - Kasturi Vasudevan; Surendra Kota; Lov Kumar; Himanshu Bhusan Mishra (CoRR, 2023)

Turbo Coded OFDM-OQAM Using Hilbert Transform. - Kasturi Vasudevan; Surendra Kota; Lov Kumar; Himanshu Bhusan Mishra (CoRR, 2023)

Machine learning with word embedding for detecting web-services anti-patterns. - Lov Kumar; Sahithi Tummalapalli; Sonika Chandrakant Rathi; Lalita Bhanu Murthy Neti; Aneesh Krishna; Sanjay Misra (J. Comput. Lang., 2023)

Empirical evaluation of the performance of data sampling and feature selection techniques for software fault prediction. - Sonika Chandrakant Rathi; Sanjay Misra; Ricardo Colomo-Palacios; R. Adarsh; Lalita Bhanu Murthy Neti; Lov Kumar (Expert Syst. Appl., 2023)

Investigating BERT Layer Performance and SMOTE Through MLP-Driven Ablation on Gittercom. - Bathini Sai Akash; Vikram Singh 005; Aneesh Krishna; Lalita Bhanu Murthy Neti; Lov Kumar (AINA (2), 2024)

An Empirical Analysis on Leveraging User Reviews with NLP-Enhanced Word Embeddings for App Rating Prediction. - Pratyush Mishra; Vikram Singh 005; Aneesh Krishna; Lov Kumar (AINA (3), 2024)

Ensemble Learning for Recommending Job Categories. - Swati Garg; Chandra Sekhar; Lov Kumar (OCIT, 2024)

Embracing NLP-Enhanced Word Embeddings for Contextually Enriched Technical Debt Estimation in Software Code Comments: An Empirical Study. - Ishpreet Kaur; Lov Kumar; Vikram Singh 005; Pratyush Mishra; Proksh (OCIT, 2024)

Exploring Meta-Embeddings in Ensemble and Deep Learning for Gittercom Message Category Prediction. - Ashutosh Kr Sinha; Lov Kumar; Vikram Singh 005 (OCIT, 2024)

A Codebert Based Empirical Framework for Evaluating Classification-Enabled Vulnerability Prediction Models. - Tumu Akshar; Vikram Singh 005; N. L. Bhanu Murthy; Aneesh Krishna; Lov Kumar (ISEC, 2024)

An Empirical Framework for Automatic Identification of Video Game Development Problems Using Multilayer Perceptron. - Pratham Maan; Lov Kumar; Vikram Singh 005; Lalita Bhanu Murthy Neti; Aneesh Krishna (ENASE, 2025)

An empirical evaluation of the effectiveness of various ML, DL, and CodeBERT models to enhance the quality of software with the application of AST and Embedding techniques. - Sonika Chandrakant Rathi; N. L. Bhanu Murthy; Lov Kumar (ISEC, 2025)

Enhanced Software Fault Prediction by Analyzing Code Comments using CodeBERT. - Monika Yadav; Lov Kumar; Vishal Passricha (ISEC, 2025)

Nested deep learning with learned network embeddings for software defect prediction. - Sweta Mehta; Lov Kumar; Sanjay Misra; K. Sridhar Patnaik; Vikram Singh 005 (Appl. Soft Comput., 2025)

MLAPW: A framework to assess the impact of feature selection and sampling techniques on anti-pattern prediction using WSDL metrics. - Lov Kumar; Vikram Singh 005; N. L. Bhanu Murthy; Aneesh Krishna; Sanjay Misra (J. Comput. Lang., 2025)