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Reusing third-party software packages is a common practice in software development. As the scale and complexity of open-source software (OSS) projects continue to grow (e.g., Linux distributions), the number of reused third-party packages…

We propose an algorithm inspired by optical coherent Ising machines to solve the problem of polynomial unconstrained binary optimization (PUBO). We benchmark the proposed algorithm against existing PUBO algorithms on the extended…

Software ecosystems (e.g., npm, PyPI) are the backbone of modern software developments. Developers add new packages to ecosystems every day to solve new problems or provide alternative solutions, causing obsolete packages to decline in…

Nearly every popular programming language comes with one or more package managers. The software packages distributed by such package managers form large software ecosystems. These packaging ecosystems contain a large number of package…

Many challenges in science and engineering, such as drug discovery and communication network design, involve optimizing complex and expensive black-box functions across vast search spaces. Thus, it is essential to leverage existing data to…

Proximal Policy Optimization (PPO) is central to aligning Large Language Models (LLMs) in reasoning tasks with verifiable rewards. However, standard token-level PPO struggles in this setting due to the instability of temporal credit…

The popularity of Bayesian Optimization (BO) to automate or support the commissioning of engineering systems is rising. Conventional BO, however, relies on the availability of a scalar objective function. The latter is often difficult to…

Dependency analysis is recognized as an important field of software engineering due to a variety of reasons. There exists a large pool of tools providing assistance to software developers and architects. Analysis of inter- and intra-project…

Neural Combinatorial Optimization (NCO) has emerged as a promising approach for NP-hard problems. However, prevailing RL-based methods suffer from low sample efficiency due to sparse rewards and underused solutions. We propose Best-anchored…

Modern software systems, like GNU/Linux distributions or Eclipse-based development environment, are often deployed by selecting components out of large component repositories. Maintaining such software systems by performing component…

Significant effort has been made to solve computationally expensive optimization problems in the past two decades, and various optimization methods incorporating surrogates into optimization have been proposed. However, most optimization…

The alternation of existential and universal quantifiers in a quantified boolean formula (QBF) generates dependencies among variables that must be respected when evaluating the formula. Dependency schemes provide a general framework for…

Software deployment suffers from numerous problems pertaining, for example, to reproducibility and dependency resolution. Many of these problems have been successfully solved by the purely functional approach to package management…

Background: The Node Package Manager (npm) ecosystem plays a vital role in modern software development by providing a vast repository of packages and tools that developers can use to implement their software systems. However, recent…

Open Source Software projects add labels to open issues to help contributors choose tasks. However, manually labeling issues is time-consuming and error-prone. Current automatic approaches for creating labels are mostly limited to…

Particle swarm optimization (PSO) is attracting an ever-growing attention and more than ever it has found many application areas for many challenging optimization problems. It is, however, a known fact that PSO has a severe drawback in the…

We illustrate the advantages the high-level open-source software package Pyomo has in rapidly setting up and solving dynamic simulation and optimization problems. In order to do so, we use the example of the Williams-Otto process. We show…

In this work we are interested in the construction of numerical methods for high dimensional constrained nonlinear optimization problems by particle-based gradient-free techniques. A consensus-based optimization (CBO) approach combined with…

Although it is possible to increase confidence in Free and Open Source Software (FOSS) by reviewing its source code, trusting code is not the same as trusting its executable counterparts. These are typically built and distributed by…

Preferential Bayesian optimization (PBO) is a framework for optimizing a decision-maker's latent preferences over available design choices. While preferences often involve multiple conflicting objectives, existing work in PBO assumes that…