软件工程
Most coding-agent benchmarks are static: an agent receives a complete task description up front and is judged only by its final code. Real coding assistance is interactive, with users clarifying goals, adding constraints, and correcting…
Spreadsheets are widely used for business analysis, financial modeling, reporting, and decision-making. However, most existing spreadsheet benchmarks evaluate isolated operations such as single-formula generation or local cell edits, and…
Build-versus-buy decisions remain a persistent challenge in enterprise software development, shaped by competing strategic, technical, cost, and risk considerations. The increasing availability of third-party solutions alongside the growing…
In this study, we present a large-scale, in-depth study of package replication in PyPI. As a vital platform, PyPI streamlines Python package distribution for developers. However, beyond small-scale code cloning, we observe that many…
The adoption of Microservice Architecture (MSA) has revolutionized software engineering by enhancing scalability, agility, and maintainability over traditional monolithic applications. As more developers transition their legacy systems to…
Bash script comprehension is challenging due to Bash's syntactic freedom and complex command structures. Despite its critical role in system administration, Bash scripts often lack adequate comments, hindering readability and…
In mid-2026 a slogan reorganized how practitioners talk about coding agents: stop prompting your agent, start designing the loop that prompts it. We take this claim seriously and give it a careful treatment. We call the object of the new…
Spec-Driven Development (SDD) frameworks guide Large Language Model (LLM)-powered code generation through formal specifications, yet they differ fundamentally in how they enforce traceability between requirements and generated code. This…
A key element of Model-Driven Engineering is the construction of domain-specific modelling environments to improve productivity and quality. In theory, dedicated technologies like EMF, ATL, Epsilon, Xtext, etc. would boost the construction…
Forks share git history, so a commit surfaces in many repositories and any spread- or popularity-based measure over raw repositories is inflated by orders of magnitude. We release a curated deforking map for the World of Code (WoC) version…
Skills are a useful abstraction for software agents, turning human and agent experience into reusable procedural knowledge. Yet existing skill libraries are mostly hand-written, text-centric, or derived from agent traces, leaving tutorial…
Large Language Models (LLMs) are increasingly used as assistants across the software development lifecycle, yet their ability to reason about software architecture remains largely unmeasured. Architectural decision-making depends on quality…
Context: Software-intensive systems are integral to nearly all facets of modern society [1]. Consequently, both their sustainability and their role in facilitating sustainable processes must be established by design [2], [3]. Software…
LLM-based agents are reshaping microservice operations into AgentOps, where benchmarks are key to evaluating failure diagnosis over multimodal observability data. However, existing benchmarks remain largely outcome-oriented: they score only…
Large Language Models (LLMs) have recently shown promise in automated binary analysis, yet they remain brittle under commercial-grade obfuscation. We present OASIF, an Obfuscation-Aware Self-evolving Instruction-Following framework for…
There are various benchmarks to evaluate bugfixing capabilities of Large Language Models. However, most widespread benchmarks do not fully reflect real-world bugfixing practices. They are small, weakening statistical reliability, and the…
Current examples of SysML-based verification of discipline-specific models in the literature typically have two flaws. Firstly, they are developed in a tool-specific manner using proprietary APIs, limiting portability. Secondly, they focus…
Large Language Model (LLM) alignment trains an LLM using preference data to produce outputs that better meet established quality standards. While LLM alignment techniques are studied for non-coding tasks, we know little about their…
Software engineering is experiencing its most significant transformation since the emergence of high-level programming languages. As large language models (LLMs) increasingly enable sustained, multi-step, tool-mediated execution,…
Background: Developers frequently reuse code by copying fragments and adapting them to fit new contexts. Existing benchmarks for evaluating large language models (LLMs) on code adaptation either rely on explicit step-by-step instructions,…