相关论文: Detection of Performance Changes in MooBench Resul…

As enterprises move to a cloud-first approach, their network becomes crucial to their daily operations and has to be continuously monitored. Although passive monitoring can be convenient from a deployment viewpoint, inferring the state of…

Network performance problems are notoriously difficult to diagnose. Prior profiling systems collect performance statistics by keeping information about each network flow, but maintaining per-flow state is not scalable on…

The fragmented landscape of quantum computer benchmarks, characterized by system-specific tools and inconsistent evaluation methodologies, hinders reliable cross-platform performance assessment. We introduce Metriq, an open-source…

Content providers build serving stacks to deliver content to users. An important goal of a content provider is to ensure good user experience, since user experience has an impact on revenue. In this paper, we describe a system at Yahoo…

The growing number of implementations of blockchain systems stands in stark contrast with still limited research on a systematic comparison of performance characteristics of these solutions. Such research is crucial for evaluating…

Processor design validation and debug is a difficult and complex task, which consumes the lion's share of the design process. Design bugs that affect processor performance rather than its functionality are especially difficult to catch,…

Contemporary social coding platforms like GitHub promote collaborative development. Many open-source software repositories hosted in these platforms use machine accounts (bots) to automate and facilitate a wide range of effort-intensive and…

Large Language Models have advanced automated software development, however, it remains a challenge to correctly infer dependencies, namely, identifying the internal components and external packages required for a repository to successfully…

Learned database components, which deeply integrate machine learning into their design, have been extensively studied in recent years. Given the dynamism of databases, where data and workloads continuously drift, it is crucial for learned…

Continuous Integration/Continuous Delivery (CI/CD) caching is widely used to reduce repeated computation and improve CI/CD efficiency, yet maintaining effective caching requires ongoing maintenance effort. In this paper, we present the…

Performance unpredictability is a major roadblock towards cloud adoption, and has performance, cost, and revenue ramifications. Predictable performance is even more critical as cloud services transition from monolithic designs to…

Modern software development demands code that is maintainable, testable, and scalable by organizing the implementation into modular components with iterative reuse of existing codes. We formalize this iterative, multi-turn paradigm as…

The pace and volume of code churn necessary to evolve modern software systems present challenges for analyzing the performance impact of any set of code changes. Traditional methods used in performance analysis rely on extensive data…

Choosing the right resource can speed up job completion, better utilize the available hardware, and visibly reduce costs, especially when renting computers in the cloud. This was demonstrated in earlier studies on HEPCloud. However, the…

Software performance modeling plays a crucial role in developing and maintaining software systems. A performance model analytically describes the relationship between the performance of a system and its runtime activities. This process…

As more and more multi-tier services are developed from commercial components or heterogeneous middleware without the source code available, both developers and administrators need a precise request tracing tool to help understand and debug…

The performance of database management systems (DBMS) is traditionally evaluated using benchmarks that focus on workloads with (almost) fixed record lengths. However, some real-world workloads in key/value stores, document databases, and…

Climate projections using data driven machine learning models acting as emulators, is one of the prevailing areas of research to enable policy makers make informed decisions. Use of machine learning emulators as surrogates for…

Making serverless computing widely applicable requires detailed performance understanding. Although contemporary benchmarking approaches exist, they report only coarse results, do not apply distributed tracing, do not consider asynchronous…

Regression bugs occur whenever software functionality that previously worked as desired stops working, or no longer works as expected. Code changes, such as bug fixes or new feature work, may result in a regression bug. Regression bugs are…