Entropy based Binary Particle Swarm Optimization and classification for ear detection. - Madan Ravi Ganesh; Rahul Krishna; K. Manikantan; S. Ramachandran (Eng. Appl. Artif. Intell., 2014)

Actionable = Cluster + Contrast? - Rahul Krishna; Tim Menzies (ASE Workshops, 2015)

The "BigSE" project: lessons learned from validating industrial text mining. - Rahul Krishna; Zhe Yu 002; Amritanshu Agrawal; Manuel Dominguez; David Wolf (BIGDSE@ICSE, 2016)

Too much automation? the bellwether effect and its implications for transfer learning. - Rahul Krishna; Tim Menzies; Wei Fu 002 (ASE, 2016)

Is "Sampling" better than "Evolution" for Search-based Software Engineering? - Jianfeng Chen; Vivek Nair; Rahul Krishna; Tim Menzies (CoRR, 2016)

Recommendations for Intelligent Code Reorganization. - Rahul Krishna; Tim Menzies; Lucas Layman (CoRR, 2016)

Learning effective changes for software projects. - Rahul Krishna (ASE, 2017)

Simpler Transfer Learning (Using "Bellwethers"). - Rahul Krishna; Tim Menzies (CoRR, 2017)

Don't Tell Me What Is, Tell Me What Ought To Be! Learning Effective Changes for Software Projects. - Rahul Krishna (CoRR, 2017)

Learning Effective Changes For Software Projects. - Rahul Krishna; Tim Menzies (CoRR, 2017)

Continuous Integration: The Silver Bullet? - Akond Rahman; Amritanshu Agrawal; Rahul Krishna; Alexander Sobran; Tim Menzies (CoRR, 2017)

Less is more: Minimizing code reorganization using XTREE. - Rahul Krishna; Tim Menzies; Lucas Layman (Inf. Softw. Technol., 2017)

We don't need another hero?: the impact of "heroes" on software development. - Amritanshu Agrawal; Akond Rahman; Rahul Krishna; Alexander Sobran; Tim Menzies (ICSE (SEIP), 2018)

What is the connection between issues, bugs, and enhancements?: lessons learned from 800+ software projects. - Rahul Krishna; Amritanshu Agrawal; Akond Rahman; Alexander Sobran; Tim Menzies (ICSE (SEIP), 2018)

Applications of psychological science for actionable analytics. - Di Chen; Wei Fu 002; Rahul Krishna; Tim Menzies (ESEC/SIGSOFT FSE, 2018)

Characterizing the influence of continuous integration: empirical results from 250+ open source and proprietary projects. - Akond Rahman; Amritanshu Agrawal; Rahul Krishna; Alexander Sobran (SWAN@ESEC/SIGSOFT FSE, 2018)

Transfer Learning with Bellwethers to find Good Configurations. - Vivek Nair; Rahul Krishna; Tim Menzies; Pooyan Jamshidi (CoRR, 2018)

Bad Smells in Software Analytics Papers. - Rahul Krishna; Suvodeep Majumder; Tim Menzies; Martin J. Shepperd (CoRR, 2018)

Hyperparameter Optimization for Effort Estimation. - Tianpei Xia; Rahul Krishna; Jianfeng Chen; George Mathew; Xipeng Shen; Tim Menzies (CoRR, 2018)

Effective Automated Decision Support for Managing Crowdtesting. - Junjie Wang 001; Ye Yang; Rahul Krishna; Tim Menzies; Qing Wang 001 (CoRR, 2018)

iSENSE: completion-aware crowdtesting management. - Junjie Wang 001; Ye Yang; Rahul Krishna; Tim Menzies; Qing Wang 001 (ICSE, 2019)

Learning GENERAL Principles from Hundreds of Software Projects. - Suvodeep Majumder; Rahul Krishna; Tim Menzies (CoRR, 2019)

"Sampling" as a Baseline Optimizer for Search-Based Software Engineering. - Jianfeng Chen; Vivek Nair; Rahul Krishna; Tim Menzies (IEEE Trans. Software Eng., 2019)

Bellwethers: A Baseline Method for Transfer Learning. - Rahul Krishna; Tim Menzies (IEEE Trans. Software Eng., 2019)

MTFuzz: fuzzing with a multi-task neural network. - Dongdong She; Rahul Krishna; Lu Yan; Suman Jana; Baishakhi Ray (ESEC/SIGSOFT FSE, 2020)

CADET: A Systematic Method For Debugging Misconfigurations using Counterfactual Reasoning. - Rahul Krishna; Md Shahriar Iqbal; Mohammad Ali Javidian; Baishakhi Ray; Pooyan Jamshidi (CoRR, 2020)

Learning actionable analytics from multiple software projects. - Rahul Krishna; Tim Menzies (Empir. Softw. Eng., 2020)

Lessons learned from hyper-parameter tuning for microservice candidate identification. - Rahul Yedida; Rahul Krishna; Anup K. Kalia; Tim Menzies; Jin Xiao; Maja Vukovic (ASE, 2021)

Mono2Micro: a practical and effective tool for decomposing monolithic Java applications to microservices. - Anup K. Kalia; Jin Xiao; Rahul Krishna; Saurabh Sinha; Maja Vukovic; Debasish Banerjee (ESEC/SIGSOFT FSE, 2021)

Partitioning Cloud-based Microservices (via Deep Learning). - Rahul Yedida; Rahul Krishna; Anup K. Kalia; Tim Menzies; Jin Xiao; Maja Vukovic (CoRR, 2021)

Whence to Learn? Transferring Knowledge in Configurable Systems Using BEETLE. - Rahul Krishna; Vivek Nair; Pooyan Jamshidi; Tim Menzies (IEEE Trans. Software Eng., 2021)

Unicorn: reasoning about configurable system performance through the lens of causality. - Md Shahriar Iqbal; Rahul Krishna; Mohammad Ali Javidian; Baishakhi Ray; Pooyan Jamshidi (EuroSys, 2022)

CARGO: AI-Guided Dependency Analysis for Migrating Monolithic Applications to Microservices Architecture. - Vikram Nitin; Shubhi Asthana; Baishakhi Ray; Rahul Krishna (ASE, 2022)

Methods for Stabilizing Models Across Large Samples of Projects (with case studies on Predicting Defect and Project Health). - Suvodeep Majumder; Tianpei Xia; Rahul Krishna; Tim Menzies (MSR, 2022)

Deep Learning Based Vulnerability Detection: Are We There Yet? - Saikat Chakraborty; Rahul Krishna; Yangruibo Ding; Baishakhi Ray (IEEE Trans. Software Eng., 2022)

ConEx: Efficient Exploration of Big-Data System Configurations for Better Performance. - Rahul Krishna; Chong Tang 001; Kevin J. Sullivan; Baishakhi Ray (IEEE Trans. Software Eng., 2022)

SeamFormer: High Precision Text Line Segmentation for Handwritten Documents. - Niharika Vadlamudi; Rahul Krishna; Ravi Kiran Sarvadevabhatla (ICDAR (4), 2023)

Advanced machine learning models for Depression level categorization using DSM 5 and personality traits. - Rahul Krishna; Ravi Teja; N. Neelima; Nikhita Peddi (ICMLDE, 2023)

Understanding the Effectiveness of Large Language Models in Code Translation. - Rangeet Pan; Ali Reza Ibrahimzada; Rahul Krishna; Divya Sankar; Lambert Pouguem Wassi; Michele Merler; Boris Sobolev; Raju Pavuluri; Saurabh Sinha; Reyhaneh Jabbarvand (CoRR, 2023)

An expert system for redesigning software for cloud applications. - Rahul Yedida; Rahul Krishna; Anup K. Kalia; Tim Menzies; Jin Xiao; Maja Vukovic (Expert Syst. Appl., 2023)

Lost in Translation: A Study of Bugs Introduced by Large Language Models while Translating Code. - Rangeet Pan; Ali Reza Ibrahimzada; Rahul Krishna; Divya Sankar; Lambert Pouguem Wassi; Michele Merler; Boris Sobolev; Raju Pavuluri; Saurabh Sinha; Reyhaneh Jabbarvand (ICSE, 2024)

Multi-language Unit Test Generation using LLMs. - Rangeet Pan; Myeongsoo Kim; Rahul Krishna; Raju Pavuluri; Saurabh Sinha (CoRR, 2024)

ASTER: Natural and Multi-Language Unit Test Generation with LLMs. - Rangeet Pan; Myeongsoo Kim; Rahul Krishna; Raju Pavuluri; Saurabh Sinha (SEIP@ICSE, 2025)

Codellm-Devkit: A Framework for Contextualizing Code LLMs with Program Analysis Insights. - Rahul Krishna; Rangeet Pan; Saurabh Sinha; Srikanth Tamilselvam; Raju Pavuluri; Maja Vukovic (SIGSOFT FSE Companion, 2025)

C2SaferRust: Transforming C Projects into Safer Rust with NeuroSymbolic Techniques. - Vikram Nitin; Rahul Krishna; Luiz Lemos do Valle; Baishakhi Ray (CoRR, 2025)