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The test pyramid is a conceptual model that describes how quality checks can be organized to ensure coverage of all components of a system, at all scales. Originally conceived to help aerospace engineers plan tests to determine how material…

Software Engineering · Computer Science 2020-11-03 Nicole Radziwill , Graham Freeman

Positive experience of agile development methods in smaller projects has created interest in the applicability of such methods in larger scale projects. However, there is a lack of conceptual clarity regarding what large-scale agile…

Software Engineering · Computer Science 2018-01-29 Torgeir Dingsøyr , Tor Erlend Fægri , Juha Itkonen

The aim of the paper is to introduce general techniques in order to optimize the parallel execution time of sorting on a distributed architectures with processors of various speeds. Such an application requires a partitioning step. For…

Distributed, Parallel, and Cluster Computing · Computer Science 2016-08-16 Christophe Cérin , Jean-Christophe Dubacq , Jean-Louis Roch , the SafeScale Collaboration

High Performance Distributed Computing is essential to boost scientific progress in many areas of science and to efficiently deploy a number of complex scientific applications. These applications have different characteristics that require…

Distributed, Parallel, and Cluster Computing · Computer Science 2014-12-04 Mariza Ferro , Antonio R. Mury , Laion F. Manfroi , Bruno Schlze

In distributed computing systems slow working nodes, known as stragglers, can greatly extend finishing times. Coded computing is a technique that enables straggler-resistant computation. Most coded computing techniques presented to date…

Information Theory · Computer Science 2021-02-02 Shahrzad Kiani , Nuwan Ferdinand , Stark C. Draper

Exascale systems, expected to emerge by the end of the next decade, will require the exploitation of billion-way parallelism at multiple hierarchical levels in order to achieve the desired sustained performance. The task of assessing future…

Distributed, Parallel, and Cluster Computing · Computer Science 2011-09-27 Matthew Anderson , Maciej Brodowicz , Hartmut Kaiser , Thomas Sterling

To achieve scalability with today's heterogeneous HPC resources, we need a dramatic shift in our thinking; MPI+X is not enough. Asynchronous Many Task (AMT) runtime systems break down the global barriers imposed by the Bulk Synchronous…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-01-09 Thomas Heller , Patrick Diehl , Zachary Byerly , John Biddiscombe , Hartmut Kaiser

During the initialization of a supercomputer job, no useful calculations are performed. A high proportion of initialization time results in idle computing resources and less computational efficiency. Certain methods and algorithms combining…

Distributed, Parallel, and Cluster Computing · Computer Science 2023-12-01 Lyakhovets D. S. , Baranov A. V. , Telegin P. N

In the Hydro project we are designing a compiler toolkit that can optimize for the concerns of distributed systems, including scale-up and scale-down, availability, and consistency of outcomes across replicas. This invited paper overviews…

Distributed, Parallel, and Cluster Computing · Computer Science 2023-05-25 Joseph M. Hellerstein , Shadaj Laddad , Mae Milano , Conor Power , Mingwei Samuel

With the continuous development of business process management technology, the increasing business process models are usually owned by large enterprises. In large enterprises, different stakeholders may modify the same business process…

Software Engineering · Computer Science 2023-03-31 Linyue Liu , Xi Guo , Chun Ouyang , Patrick C. K. Hung , Hong-Yu Zhang , Keqing He , Chen Mo , Zaiwen Feng

Object-Oriented Programming (OOP) has become a crucial paradigm for managing the growing complexity of modern software systems, particularly in fields like machine learning, deep learning, large language models (LLM), and data analytics.…

Computation and Language · Computer Science 2025-12-24 Tianyang Wang , Ziqian Bi , Keyu Chen , Jiawei Xu , Qian Niu , Junyu Liu , Benji Peng , Ming Li , Sen Zhang , Xuanhe Pan , Jinlang Wang , Pohsun Feng , Yizhu Wen , Xinyuan Song , Ming Liu

Developing parallel algorithms efficiently requires careful management of concurrency across diverse hardware architectures. C++ executors provide a standardized interface that simplifies the development process, allowing developers to…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-10-22 Karame Mohammadiporshokooh , Steven R. Brandt , Hartmut Kaiser

The convergence of IoT, Edge, Cloud, and HPC technologies creates a compute continuum that merges cloud scalability and flexibility with HPC's computational power and specialized optimizations. However, integrating cloud and HPC resources…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-05-20 Aasish Kumar Sharma , Christian Boehme , Patrick Gelß , Ramin Yahyapour , Julian Kunkel

Given the complexity of modern software systems, it is of great importance that such systems be able to autonomously modify themselves, i.e., self-adapt, with minimal human supervision. It is critical that this adaptation both results in…

Software Engineering · Computer Science 2022-05-13 Todd Wareham , Ronald de Haan

Nowadays agile software development is used in greater extend but for small organizations only, whereas MDA is suitable for large organizations but yet not standardized. In this paper the pros and cons of Model Driven Architecture (MDA) and…

Software Engineering · Computer Science 2011-11-01 Pritha Guha , Kinjal Shah , Shiv Shankar Prasad Shukla , Shweta Singh

The most important way to achieve higher performance in computer systems is through heterogeneous computing, i.e., by adopting hardware platforms containing more than one type of processor, such as CPUs, GPUs, and FPGAs. Several types of…

Software Engineering · Computer Science 2020-05-19 Hugo Andrade , Ivica Crnkovic , Jan Bosch

In this paper, we address the challenges in running enterprise experimentation with hierarchical entities and present the methodologies behind the implementation of the Enterprise Experimentation Platform (EEP) at LinkedIn, which plays a…

Methodology · Statistics 2025-01-24 Shan Ba , Shilpa Garg , Jitendra Agarwal , Hanyue Zhao

Training Long-Context Large Language Models (LLMs) is challenging, as hybrid training with long-context and short-context data often leads to workload imbalances. Existing works mainly use data packing to alleviate this issue, but fail to…

Machine Learning · Computer Science 2025-10-14 Yongqiang Yao , Jingru Tan , Kaihuan Liang , Feizhao Zhang , Jiahao Hu , Shuo Wu , Yazhe Niu , Ruihao Gong , Dahua Lin , Ningyi Xu

The trend toward specialized processing devices such as TPUs, DPUs, GPUs, and FPGAs has exposed the weaknesses of PCIe in interconnecting these devices and their hosts. Several attempts have been proposed to improve, augment, or downright…

Databases · Computer Science 2024-09-04 Alberto Lerner , Gustavo Alonso

Business Process Reengineering increases enterprise's chance to survive in competition among organizations , but failure rate among reengineering efforts is high, so new methods that decrease failure, are needed, in this paper a business…

Software Engineering · Computer Science 2015-03-27 Pedram Bahramnejad , Sayed Mehran Sharafi , Akbar Nabiollahi
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