MI

M. Izadi

27 records found

The recent rise in the popularity of large language models has spurred the development of extensive code datasets needed to train them. This has left limited code available for collection and use in the downstream investigation of specific behaviors, or evaluation of large langua ...

HyperSeq

A Hyper-Adaptive Representation for Predictive Sequencing of States

In the rapidly evolving world of software development, the surge in developers’ reliance on AI-driven tools has transformed Integrated Development Environments into powerhouses of advanced features. This transformation, while boosting developers’ productivity to unprecedented lev ...
As GenAI becomes embedded in developer toolchains and practices, and routine code is increasingly generated, human creativity will be increasingly important for generating competitive advantage. This article uses the McLuhan tetrad alongside scenarios of how GenAI may disrupt sof ...

When People Come First

A Human-Centered Approach to Computer Science Education

The rise of AI tools is reshaping computer science education, shifting the focus from coding skills to teaching students how to effectively use these technologies. Understanding students' mental models and fostering computational and metacognitive skills are now essential, as ove ...
Large Language Models are essential coding assistants, yet their training is predominantly English-centric. In this study, we evaluate the performance of code language models in non-English contexts, identifying challenges in their adoption and integration into multilingual workf ...
Integrated Development Environments (IDEs) have become central to modern software development, especially with the integration of Artificial Intelligence (AI) to enhance programming efficiency and decision-making. The study of in-IDE Human-AI Experience is critical in understandi ...
Transformer-based language models are highly effective for code completion, with much research dedicated to enhancing the content of these completions. Despite their effectiveness, these models come with high operational costs and can be intrusive, especially when they suggest to ...

Correction to

The potential of an adaptive computerized dynamic assessment tutor in diagnosing and assessing learners’ listening comprehension (Education and Information Technologies, (2024), 29, 3, (3637-3661), 10.1007/s10639-023-11871-w)

In the PDF of this article, the pages were incorrectly numbered as ‘2303–2327’ when it should have been ‘3637–3661’. The page range was found to be just correct in the HTML version of the article. The original article has been corrected.
Language model-based code completion models have quickly grown in use, helping thousands of developers write code in many different programming languages. However, research on code completion models typically focuses on imperative languages such as Python and JavaScript, which re ...
In recent years, Large Language Models (LLMs) have gained significant popularity due to their ability to generate human-like text and their potential applications in various fields, such as Software Engineering. LLMs for Code are commonly trained on large unsanitized corpora of s ...

Correction to

The potential of an adaptive computerized dynamic assessment tutor in diagnosing and assessing learners’ listening comprehension (Education and Information Technologies, (2024), 29, 3, (3637-3661), 10.1007/s10639-023-11871-w)

The copyright holder in the original publication of this article was incorrect. The original article has been corrected.
Previous work has shown that Large Language Models are susceptible to so-called data extraction attacks. This allows an attacker to extract a sample that was contained in the training data, which has massive privacy implications. The construction of data extraction attacks is cha ...
In today’s environment of growing class sizes due to the prevalence of online and e-learning systems, providing one-to-one instruction and feedback has become a challenging task for teachers. Anyhow, the dialectical integration of instruction and assessment into a seamless and dy ...
Code comments are a key resource for information about software artefacts. Depending on the use case, only some types of comments are useful. Thus, automatic approaches to clas-sify these comments have been proposed. In this work, we address this need by proposing, STACC, a set o ...
Transformer-based pre-trained models have recently achieved great results in solving many software engineering tasks including automatic code completion which is a staple in a developer’s toolkit. While many have striven to improve the code-understanding abilities of such models, ...
We report on the organization and results of the second edition of the tool competition from the International Workshop on Natural Language-based Software Engineering (NLBSE'23). As in the prior edition, we organized the competition on automated issue report classification, with ...
Binary reverse engineering is used to understand and analyse programs for which the source code is unavailable. Decompilers can help, transforming opaque binaries into a more readable source code-like representation. Still, reverse engineering is difficult and costly, involving c ...
Software-related platforms such as GitHub and Stack Overflow, have enabled their users to collaboratively label software entities with a form of metadata called topics. Tagging software repositories with relevant topics can be exploited for facilitating various downstream tasks. ...

CatIss

An Intelligent Tool for Categorizing Issues Reports using Transformers

Users use Issue Tracking Systems to keep track and manage issue reports in their repositories. An issue is a rich source of software information that contains different reports including a problem, a request for new features, or merely a question about the software product. As th ...