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The increasing demand for programmers has led to a surge in participants in programming courses, making it increasingly challenging for instructors to assess student code manually. As a result, automated programming assessment systems…
Few-shot learning problem focuses on recognizing unseen classes given a few labeled images. In recent effort, more attention is paid to fine-grained feature embedding, ignoring the relationship among different distance metrics. In this…
This paper considers Aspect-based Opinion Summarization (AOS) of reviews on particular products. To enable real applications, an AOS system needs to address two core subtasks, aspect extraction and sentiment classification. Most existing…
In this paper, an attempt has been made to analyze the Activeness of an Object Oriented Component Library and develop a special type of software metric called Component Activeness Quotient which is defined as the degree of readiness of an…
Context: Free and Open Source Software (FOSS) communities' ability to stay viable and productive over time is pivotal for society as they maintain the building blocks that digital infrastructure, products, and services depend on.…
We introduce One-shot Open Affordance Learning (OOAL), where a model is trained with just one example per base object category, but is expected to identify novel objects and affordances. While vision-language models excel at recognizing…
The success of vision-language models is primarily attributed to effective alignment across modalities such as vision and language. However, modality gaps persist in existing alignment algorithms and appear necessary for human perception as…
Understanding or comprehending source code is one of the core activities of software engineering. Understanding object-oriented source code is essential and required when a programmer maintains, migrates, reuses, documents or enhances…
Open Source Software (OSS) has been widely used in the educational environment largely due to its reduced cost of ownership. While OSS has evolved over the years, challenges exist in its implementation and wide adoption. Foremost among…
Edge computing in person re-identification (ReID) is crucial for reducing the load on central cloud servers and ensuring user privacy. Conventional compression methods for obtaining compact models require computations for each individual…
It is generally acknowledged that software testing is both challenging and time-consuming. Understanding the factors that may positively or negatively affect testing effort will point to possibilities for reducing this effort. Consequently…
Artificial Intelligence has gained a lot of attention recently, it has been utilized in several fields ranging from daily life activities, such as responding to emails and scheduling appointments, to manufacturing and automating work…
People demand for software quality is growing increasingly, thus different scales for the software are growing fast to handle the quality of software. The software complexity metric is one of the measurements that use some of the internal…
Real-world software applications must constantly evolve to remain relevant. This evolution occurs when developing new applications or adapting existing ones to meet new requirements, make corrections, or incorporate future functionality.…
Estimating software testability can crucially assist software managers to optimize test budgets and software quality. In this paper, we propose a new approach that radically differs from the traditional approach of pursuing testability…
Most recent existing aspect-term level sentiment analysis (ATSA) approaches combined various neural network models with delicately carved attention mechanisms built upon given aspect and context to generate refined sentence representations…
Modularity is one of the most important principles in software engineering and a necessity for every practical software. Since the design space of software is generally quite large, it is valuable to provide automatic means to help…
Humans have the remarkable ability to perceive objects as a whole, even when parts of them are occluded. This ability of amodal perception forms the basis of our perceptual and cognitive understanding of our world. To enable robots to…
This paper explores the problem of class-agnostic anomaly detection (AD), where the objective is to train one class-agnostic AD model that can generalize to detect anomalies in diverse new classes from different domains without any…
Instance segmentation on 3D point clouds is one of the most extensively researched areas toward the realization of autonomous cars and robots. Certain existing studies have split input point clouds into small regions such as 1m x 1m; one…