相关论文: Does Using Bazel Help Speed Up Continuous Integrat…

Breakthroughs in the generative AI domain have fueled an explosion of large language model (LLM)-powered applications, whose workloads fundamentally consist of sequences of inferences through transformer architectures. Within this rapidly…

Engineering problems that apply machine learning often involve computationally intensive methods but rely on limited datasets. As engineering data evolves with new designs and constraints, models must incorporate new knowledge over time.…

Nowadays distributed computing environments, large amounts of data are generated from different resources with a high velocity, rendering the data difficult to capture, manage, and process within existing relational databases. Hadoop is a…

Intelligent services provide the power of AI to developers via simple RESTful API endpoints, abstracting away many complexities of machine learning. However, most of these intelligent services-such as computer vision-continually learn with…

Simulators are a primary tool in computer architecture research but are extremely computationally intensive. Simulating modern architectures with increased core counts and recent workloads can be challenging, even on modern hardware. This…

MapReduce and its variants have significantly simplified and accelerated the process of developing parallel programs. However, most MapReduce implementations focus on data-intensive tasks while many real-world tasks are compute intensive…

The advanced capabilities of Large Language Models (LLMs) have inspired the development of various interactive web services or applications, such as ChatGPT, which offer query inference services for users. Unlike traditional DNN model, the…

Preserving invariants while designing distributed applications under weak consistency models is difficult. The CEC (Correct Eventual Consistency Tool) is meant to aid the application designer in this task. It provides information about the…

To alleviate the cost of regression testing in continuous integration (CI), a large number of machine learning-based (ML-based) test case prioritization techniques have been proposed. However, it is yet unknown how they perform under the…

This paper surveys and describes the implementation of parallelization of the Mizar proof checking and of related Mizar utilities. The implementation makes use of Mizar's compiler-like division into several relatively independent passes,…

Buffering architectures and policies for their efficient management constitute one of the core ingredients of a network architecture. In this work we introduce a new specification language, BASEL, that allows to express virtual buffering…

Kernel fuzzing is important for finding critical kernel vulnerabilities. Close-source (e.g., Windows) operating system kernel fuzzing is even more challenging due to the lack of source code. Existing approaches fuzz the kernel by modeling…

Manual development of automatic tests for embedded C software is a strenuous and time-consuming task that does not scale well. With the accelerating pace of software release cycles, verification increasingly becomes the bottleneck in the…

In recent years, recommender systems have advanced rapidly, where embedding learning for users and items plays a critical role. A standard method learns a unique embedding vector for each user and item. However, such a method has two…

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)…

RESTful APIs are a type of web services that are widely used in industry. In the last few years, a lot of effort in the research community has been spent in designing novel techniques to automatically fuzz those APIs to find faults in them.…

In modern software engineering, Continuous Integration (CI) has become an indispensable step towards systematically managing the life cycles of software development. Large companies struggle with keeping the pipeline updated and…

Serverless computing has gained a significant traction in recent times because of its simplicity of development, deployment and fine-grained billing. However, while implementing complex services comprising databases, file stores, or more…

We study the evolution and impact of bloated dependencies in a single software ecosystem: Java/Maven. Bloated dependencies are third-party libraries that are packaged in the application binary but are not needed to run the application. We…

Class Incremental Learning (CIL) requires models to continuously learn new classes without forgetting previously learned ones, while maintaining stable performance across all possible class sequences. In real-world settings, the order in…