软件工程

Context: Technical lag accumulates when software systems fail to keep pace with technological advancements, leading to a deterioration in software quality. Objective: This paper aims to consolidate existing research on technical lag,…

Establishing precise traceability between embedded systems datasheets and their corresponding code implementations remains a fundamental challenge in systems engineering, particularly for low-level software where manual mapping between…

We present a production-optimized multi-agent system designed to translate natural language queries into executable Python code for structured data analytics. Unlike systems that rely on expensive frontier models, our approach achieves high…

A core abstraction in early Unix systems was the principle that 'everything is a file', enabling heterogeneous devices and kernel resources to be manipulated via uniform read/write interfaces. This paper explores how an analogous…

Issue resolution, a complex Software Engineering (SWE) task integral to real-world development, has emerged as a compelling challenge for artificial intelligence. The establishment of benchmarks like SWE-bench revealed this task as…

Continuous Integration and Continuous Deployment (CI/CD) pipelines are central to modern software delivery, yet their static workflows often introduce inefficiencies as systems scale. This paper proposes a reinforcement learning (RL) based…

Despite recent advancements in Large Language Models (LLMs), complex Software Engineering (SE) tasks require more collaborative and specialized approaches. This concept paper systematically reviews the emerging paradigm of LLM-based…

The integration of Large Language Models (LLMs), such as ChatGPT and GitHub Copilot, into professional workflows is increasingly reshaping software engineering practices. These tools have lowered the cost of code generation, explanation,…

Unit tests are critical in the hardware design lifecycle to ensure that component design modules are functionally correct and conform to the specification before they are integrated at the system level. Thus developing unit tests targeting…

Self-admitted technical debt (SATD), referring to comments flagged by developers that explicitly acknowledge suboptimal code or incomplete functionality, has received extensive attention in machine learning (ML) and traditional (Non-ML)…

A Software Bill of Materials (SBOM) is a machine-readable artifact that systematically organizes software information, enhancing supply chain transparency and security. To facilitate the exchange and utilization of SBOMs, organizations such…

Trusted Execution Environments (TEEs), such as Intel SGX and ARM TrustZone, provide isolated regions of CPU and memory for secure computation and are increasingly used to protect sensitive data and code across diverse application domains.…

Large Language Models are increasingly deployed as judges (LaaJ) in code generation pipelines. While attractive for scalability, LaaJs tend to overlook domain specific issues raising concerns about their reliability in critical evaluation…

Dynamically executing specific target methods in Android applications remains a critical and unresolved challenge. Despite notable advancements in GUI testing, current tools are insufficient for reliably driving execution toward specific…

Software vulnerabilities often persist or re-emerge even after being fixed, revealing the complex interplay between code evolution and socio-technical factors. While source code metrics provide useful indicators of vulnerabilities, software…

Software Engineering (SE) research involving the use of Large Language Models (LLMs) has introduced several new challenges related to rigour in benchmarking, contamination, replicability, and sustainability. In this paper, we invite the…

Abstraction is a fundamental principle in classical software engineering, which enables modularity, reusability, and scalability. However, quantum programs adhere to fundamentally different semantics, such as unitarity, entanglement, the…

Rust is a modern systems programming language that ensures memory safety by enforcing ownership and borrowing rules at compile time. While the unsafe keyword allows programmers to bypass these restrictions, it introduces significant risks.…

In recent years, Large Language Models (LLMs) have been widely studied in the code translation field on the method, class, and even repository levels. However, most of these benchmarks are limited in terms of Third-Party Library (TPL)…

Large language models (LLMs) have been widely adopted across diverse domains of software engineering, such as code generation, program repair, and vulnerability detection. These applications require understanding beyond surface-level code…