114 citations · 275 across the 17 of their papers we have counts for
20 papers
Towards Causal Deep Learning for Vulnerability Detection
Md Mahbubur Rahman, Ira Ceka, Chengzhi Mao +3
Deep learning vulnerability detection has shown promising results in recent years. However, an important challenge that still blocks it from being very useful in practice is that t…
CONCORD: Clone-aware Contrastive Learning for Source Code
Yangruibo Ding, Saikat Chakraborty, Luca Buratti +4
Deep Learning (DL) models to analyze source code have shown immense promise during the past few years. More recently, self-supervised pre-training has gained traction for learning…
Automated Code Editing with Search-Generate-Modify
Changshu Liu, Pelin Cetin, Yogesh Patodia +3
Code editing is essential in evolving software development. Many automated code editing tools have been proposed that leverage both Information Retrieval-based techniques and Machi…
GrACE: Generation using Associated Code Edits
Priyanshu Gupta, Avishree Khare, Yasharth Bajpai +6
Developers expend a significant amount of time in editing code for a variety of reasons such as bug fixing or adding new features. Designing effective methods to predict code edits…
REINFOREST: Reinforcing Semantic Code Similarity for Cross-Lingual Code Search Models
Anthony Saieva, Saikat Chakraborty, Gail Kaiser
This paper introduces a novel code-to-code search technique that enhances the performance of Large Language Models (LLMs) by including both static and dynamic features as well as u…
Towards Generating Functionally Correct Code Edits from Natural Language Issue Descriptions
Sarah Fakhoury, Saikat Chakraborty, Madan Musuvathi +1
Large language models (LLMs), such as OpenAI's Codex, have demonstrated their potential to generate code from natural language descriptions across a wide range of programming tasks…
On ML-Based Program Translation: Perils and Promises
Aniketh Malyala, Katelyn Zhou, Baishakhi Ray +1
With the advent of new and advanced programming languages, it becomes imperative to migrate legacy software to new programming languages. Unsupervised Machine Learning-based Progra…
NatGen: Generative pre-training by "Naturalizing" source code
Saikat Chakraborty, Toufique Ahmed, Yangruibo Ding +2
Pre-trained Generative Language models (e.g. PLBART, CodeT5, SPT-Code) for source code yielded strong results on several tasks in the past few years, including code generation and…
Summarize and Generate to Back-translate: Unsupervised Translation of Programming Languages
Wasi Uddin Ahmad, Saikat Chakraborty, Baishakhi Ray +1
Back-translation is widely known for its effectiveness in neural machine translation when there is little to no parallel data. In this approach, a source-to-target model is coupled…
Towards Learning (Dis)-Similarity of Source Code from Program Contrasts
Yangruibo Ding, Luca Buratti, Saurabh Pujar +3
Understanding the functional (dis)-similarity of source code is significant for code modeling tasks such as software vulnerability and code clone detection. We present DISCO(DIS-si…
Retrieval Augmented Code Generation and Summarization
Md Rizwan Parvez, Wasi Uddin Ahmad, Saikat Chakraborty +2
Software developers write a lot of source code and documentation during software development. Intrinsically, developers often recall parts of source code or code summaries that the…
On Multi-Modal Learning of Editing Source Code
Saikat Chakraborty, Baishakhi Ray
In recent years, Neural Machine Translator (NMT) has shown promise in automatically editing source code. Typical NMT based code editor only considers the code that needs to be chan…
AVATAR: A Parallel Corpus for Java-Python Program Translation
Wasi Uddin Ahmad, Md Golam Rahman Tushar, Saikat Chakraborty +1
Program translation refers to migrating source code from one programming language to another. It has tremendous practical value in software development, as porting software across…
Unified Pre-training for Program Understanding and Generation
Wasi Uddin Ahmad, Saikat Chakraborty, Baishakhi Ray +1
Code summarization and generation empower conversion between programming language (PL) and natural language (NL), while code translation avails the migration of legacy code from on…
Deep Learning based Vulnerability Detection: Are We There Yet?
Saikat Chakraborty, Rahul Krishna, Yangruibo Ding +1
Automated detection of software vulnerabilities is a fundamental problem in software security. Existing program analysis techniques either suffer from high false positives or false…
A Transformer-based Approach for Source Code Summarization
Wasi Uddin Ahmad, Saikat Chakraborty, Baishakhi Ray +1
Generating a readable summary that describes the functionality of a program is known as source code summarization. In this task, learning code representation by modeling the pairwi…
CODIT: Code Editing with Tree-Based Neural Models
Saikat Chakraborty, Yangruibo Ding, Miltiadis Allamanis +1
The way developers edit day-to-day code tends to be repetitive, often using existing code elements. Many researchers have tried to automate repetitive code changes by learning from…
A Case Study on the Impact of Similarity Measure on Information Retrieval based Software Engineering Tasks
Md Masudur Rahman, Saikat Chakraborty, Gail Kaiser +1
Information Retrieval (IR) plays a pivotal role in diverse Software Engineering (SE) tasks, e.g., bug localization and triaging, code retrieval, requirements analysis, etc. The cho…
Building Language Models for Text with Named Entities
Md Rizwan Parvez, Saikat Chakraborty, Baishakhi Ray +1
Text in many domains involves a significant amount of named entities. Predict- ing the entity names is often challenging for a language model as they appear less frequent on the tr…
Entropy Guided Spectrum Based Bug Localization Using Statistical Language Model
Saikat Chakraborty, Yujian Li, Matt Irvine +2
Locating bugs is challenging but one of the most important activities in software development and maintenance phase because there are no certain rules to identify all types of bugs…