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Found 18 papers, 8 papers with code
Model-driven Engineering for Machine Learning Components: A Systematic Literature Review
Through this SLR, we wanted to analyze existing studies, including their motivations, MDE solutions, evaluation techniques, key benefits and limitations.
Large Language Models for Software Engineering: A Systematic Literature Review
Nevertheless, a comprehensive understanding of the application, effects, and possible limitations of LLMs on SE is still in its early stages.
Requirements Engineering Framework for Human-centered Artificial Intelligence Software Systems
[Method] In this paper, we present a new framework developed based on human-centered AI guidelines and a user survey to aid in collecting requirements for human-centered AI-based software.
An Information-Theoretic and Contrastive Learning-based Approach for Identifying Code Statements Causing Software Vulnerability
In this paper we propose a novel end-to-end deep learning-based approach to identify the vulnerability-relevant code statements of a specific function.
Cross Project Software Vulnerability Detection via Domain Adaptation and Max-Margin Principle
However, there are still two open and significant issues for SVD in terms of i) learning automatic representations to improve the predictive performance of SVD, and ii) tackling the scarcity of labeled vulnerabilities datasets that conventionally need laborious labeling effort by experts.
SQAPlanner: Generating Data-Informed Software Quality Improvement Plans
Thus, our SQAPlanner paves a way for novel research in actionable software analytics-i. e., generating actionable guidance on what should practitioners do and not do to decrease the risk of having defects to support SQA planning.
Explainable AI for Software Engineering
Artificial Intelligence/Machine Learning techniques have been widely used in software engineering to improve developer productivity, the quality of software systems, and decision-making.
On the Replicability and Reproducibility of Deep Learning in Software Engineering
Experimental results show the importance of replicability and reproducibility, where the reported performance of a DL model could not be replicated for an unstable optimization process.
Beware the evolving 'intelligent' web service! An integration architecture tactic to guard AI-first components
Intelligent services provide the power of AI to developers via simple RESTful API endpoints, abstracting away many complexities of machine learning.
Generating Question Titles for Stack Overflow from Mined Code Snippets
Stack Overflow has been heavily used by software developers as a popular way to seek programming-related information from peers via the internet.
Software Engineering
Interpreting Cloud Computer Vision Pain-Points: A Mining Study of Stack Overflow
The objective of this study is to determine the various pain-points developers face when implementing systems that rely on the most mature of these intelligent services, specifically those that provide computer vision.
Checking Smart Contracts with Structural Code Embedding
However, many bugs and vulnerabilities have been identified in many contracts which raises serious concerns about smart contract security, not to mention that the blockchain systems on which the smart contracts are built can be buggy.
Software Engineering
SmartEmbed: A Tool for Clone and Bug Detection in Smart Contracts through Structural Code Embedding
In addition to the uses by individual developers, SmartEmbed can also be applied to studies of smart contracts in a large scale.
Software Engineering
Losing Confidence in Quality: Unspoken Evolution of Computer Vision Services
Multiple vendors now offer this technology as cloud services and developers want to leverage these advances to provide value to end-users.
Towards effective AI-powered agile project management
The rise of Artificial intelligence (AI) has the potential to significantly transform the practice of project management.
A deep tree-based model for software defect prediction
Defects are common in software systems and can potentially cause various problems to software users.
Software Engineering
Automatic feature learning for vulnerability prediction
Code flaws or vulnerabilities are prevalent in software systems and can potentially cause a variety of problems including deadlock, information loss, or system failure.
Software Engineering
DeepSoft: A vision for a deep model of software
Although software analytics has experienced rapid growth as a research area, it has not yet reached its full potential for wide industrial adoption.
