18 citations · 20 across the 7 of their papers we have counts for
8 papers
A Tertiary Review of Large Language Model-Based Code Generating Tasks: Trends, Challenges, and Future Directions
Muslim Chochlov, Michael English, Jim Buckley
Context. Large language models (LLMs) are increasingly applied to code-generating tasks (CGTs) in software engineering. While reported results are promising, the broader effects of…
Selecting and Combining Large Language Models for Scalable Code Clone Detection
Muslim Chochlov, Gul Aftab Ahmed, James Vincent Patten +4
Source code clones pose risks ranging from intellectual property violations to unintended vulnerabilities. Effective and efficient scalable clone detection, especially for diverged…
Industrial-Scale Neural Network Clone Detection with Disk-Based Similarity Search
Gul Aftab Ahmed, Muslim Chochlov, Abdul Razzaq +5
Code clones are similar code fragments that often arise from copy-and-paste programming. Neural networks can classify pairs of code fragments as clone/not-clone with high accuracy.…
Do Weibo platform experts perform better at predicting stock market?
Ziyuan Ma, Conor Ryan, Jim Buckley +1
Sentiment analysis can be used for stock market prediction. However, existing research has not studied the impact of a user's financial background on sentiment-based forecasting of…
Using Ensemble Inference to Improve Recall of Clone Detection
Gul Aftab Ahmed, James Vincent Patten, Yuanhua Han +4
Large-scale source-code clone detection is a challenging task. In our previous work, we proposed an approach (SSCD) that leverages artificial neural networks and approximates neare…
Using Changeset Descriptions as a Data Source to Assist Feature Location
Muslim Chochlov, Michael English, Jim Buckley
Feature location attempts to assist developers in discovering functionality in source code. Many textual feature location techniques utilize information retrieval and rely on comme…
Using a Nearest-Neighbour, BERT-Based Approach for Scalable Clone Detection
Muslim Chochlov, Gul Aftab Ahmed, James Vincent Patten +4
Code clones can detrimentally impact software maintenance and manually detecting them in very large codebases is impractical. Additionally, automated approaches find detection of T…
BoostNSift: A Query Boosting and Code Sifting Technique for Method Level Bug Localization
Abdul Razzaq, Jim Buckley, James Vincent Patten +2
Locating bugs is an important, but effort-intensive and time-consuming task, when dealing with large-scale systems. To address this, Information Retrieval (IR) techniques are incre…