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Continuous Integration (CI) has evolved from a tooling strategy to a fundamental mindset in modern CI engineering. It enables teams to develop, test, and deliver software rapidly and collaboratively. Among CI services, GitHub Actions (GHA)…
Static data-flow analysis has proven its effectiveness in assessing security of applications. One major challenge it faces is scalability to large software. This issue is even exacerbated when additional limitations on computing and storage…
Agile practices are receiving considerable attention from industry as an alternative to traditional software development approaches. However, there are a number of challenges in combining Agile [2] with Test-driven development (TDD) [10]…
Some mission critical systems, such as fraud detection, require accurate, real-time metrics over long time windows on applications that demand high throughputs and low latencies. As these applications need to run "forever", cope with large…
The demand for quick and reliable DevOps operations pushed distributors of repository platforms to implement workflows. Workflows allow automating code management operations directly on the repository hosting the software. However, this…
We present SwiftEmbed, a production-oriented serving system for static token embeddings that achieves 1.12\,ms p50 latency for single-text requests while maintaining a 60.6 MTEB average score across 8 representative tasks. Built around the…
Python is the de-facto language for software development in artificial intelligence (AI). Commonly used libraries, such as PyTorch and TensorFlow, rely on parallelization built into their BLAS backends to achieve speedup on CPUs. However,…
GitHub is a popular repository for hosting software projects, both due to ease of use and the seamless integration with its testing environment. Native GitHub Actions make it easy for software developers to validate new commits and have…
The data mining field is an important source of large-scale applications and datasets which are getting more and more common. In this paper, we present grid-based approaches for two basic data mining applications, and a performance…
One of the more complex tasks for researchers using HPC systems is performance monitoring and tuning of their applications. Developing a practice of continuous performance improvement, both for speed-up and efficient use of resources is…
Stream processing is a compute paradigm that promises safe and efficient parallelism. Modern big-data problems are often well suited for stream processing's throughput-oriented nature. Realization of efficient stream processing requires…
AI-driven software development has rapidly advanced with the emergence of software development agents that leverage large language models (LLMs) to tackle complex, repository-level software engineering tasks. These agents go beyond just…
As the need for more computing power grows, traditional methods are hitting limits. To boost performance, we're expanding Central Processing Unit (CPU) capabilities and using specialized hardware accelerators. For example, mobile devices…
Centralized cloud computing with 100+ milliseconds network latencies cannot meet the tens of milliseconds to sub-millisecond response times required for emerging 5G applications like autonomous driving, smart manufacturing, tactile…
Token-based replay used to be the standard way to conduct conformance checking. With the uptake of more advanced techniques (e.g., alignment based), token-based replay got abandoned. However, despite decomposition approaches and heuristics…
The practice of continuous deployment has enabled companies to reduce time-to-market by increasing the rate at which software can be deployed. However, deploying more frequently bears the risk that occasionally defective changes are…
Audit trails are evidential indications of activities performers in any logs. Modern reactive systems such as transaction processing systems, management information systems, decision support systems and even executive management systems log…
GitOps has emerged as a foundational paradigm for managing cloud-native infrastructures by enabling declarative configuration, version-controlled state, and automated reconciliation between intents and runtime deployments. Despite its…
The data processing model for the CDF experiment is described. Data processing reconstructs events from parallel data streams taken with different combinations of physics event triggers and further splits the events into datasets of…
There exists a verification gap between formal protocol specifications and their actual implementations, which this work aims to bridge via monitoring for compliance to the formal specification. We instrument the networking and…