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IEEE Computer Society (CS) President Hironori Washizaki kicks off the New Year with an overview of the Society’s goals and strategic areas. In 2025, the CS will focus on three strategic areas: engaging our members, engaging industry, and leading new areas ...

In this study, we consider projects for developing service systems using machine learning (ML) techniques. These projects involve collaboration between various stakeholders. Several types of models representing system architectures are introduced ...

• We propose an enterprise architecture-based metamodel by combining existing models on ML projects.
• The metamodel provides practitioners with a holistic business–IT alignment view on ML projects.
• We define a procedure to enhance the ...

Resource-constrained environments, such as embedded devices, have limited amounts of memory and storage. Practical programming languages such as C++ and Rust tend to output multiple similar functions by monomorphizing polymorphic functions. An ...

Development of machine learning (ML) systems differs from traditional approaches. The probabilistic nature of ML leads to a more experimentative development approach, which often results in a disparity between the quality of ML models with other ...

In this study, we employ causal inference models, specifically Bayesian Networks (BN) and Linear Non-Gaussian Acyclic Models (LiNGAM), to investigate the determinants of Bug Fixing Time (BFT) in software development. Moving beyond traditional ...

Persona --- fictional user profiles --- are used to identify user requirements in software engineering. However, methods targeting revisions, especially for existing B2B services, remain sparse. This paper proposes a method that integrates several models,...

Multi-View Modeling Framework for ML Systems (M³S) provides a framework to synchronize the experimental nature of machine learning and the deterministic side of traditional software engineering. However, understanding the framework's generality and ...

We propose a conceptual framework, named "AI Security Continuum," consisting of dimensions to deal with challenges of the breadth of the AI security risk sustainably and systematically under the emerging context of the computing continuum as well as ...

Although programming is part of primary school curricula in many countries, barriers persist for elementary students learning programming such as an insufficient understanding of the underlying mathematics, complex concepts, and purpose of programming. ...

Teachers often utilize automatic program repair methods to provide feedback on submitted student code using model answer code. A state-of-the-art tool is Refactory, which achieves a high repair success rate and small patch size (less code repair) by ...

Traditional rule-based approaches to system monitoring have many areas for improvement. Rules are time-consuming to maintain, and their ability to detect unforeseen future incidents is limited. Online log anomaly detection workflows have the ...

Welcome to the 27th ACM International Systems and Software Product Line Conference (SPLC 2023). SPLC is a thriving ground for practitioners, researchers, and educators working in areas related to systems and software product lines. With the increasing ...

Most client software employs a bug-tracking system, which utilizes user-submitted reports (bug reports) that contain information necessary for software developers to fix bugs. The quality of bug reports drastically differs. Bug reports can include ...

The purpose of this study is to identify the characteristics of Agile development processes that impact user satisfaction. We used user reviews of OSS smartphone apps and various data from version control systems to examine the relationships, ...

Nowadays, intelligent systems and services are getting increasingly popular as they provide data-driven solutions to diverse real-world problems, thanks to recent breakthroughs in artificial intelligence (AI) and machine learning (ML). However, ...

Machine learning (ML) researchers study the best practices to develop and support ML-based applications to ensure quality and determine the constraints applied to their application pipelines. Such practices are often formalized as software patterns. We ...

Analysis of machine learning models often used canvas-based models such as ML Canvas and AI Project Canvas to facilitate rapid brainstorming of ideas. However, those models often cover only high-level descriptions of requirements. Developers may utilize ...

Common Vulnerabilities and Exposures (CVE) databases contain information about vulnerabilities of software products and source code. If individual elements of CVE descriptions can be extracted and structured, then the data can be used to search and ...

Machine learning-based system requires specific attention towards their safety characteristics while considering the higher-level requirements. This study describes our approach for analyzing machine learning safety requirements top-down from higher-...