Current Issue : July-September Volume : 2025 Issue Number : 3 Articles : 5 Articles
To address the current situation where many small enterprises lack efficient management of customer data, this paper proposes a design and implementation plan of a customer relationship management (CRM) system based on email service. It aims to solve the problems of data dispersion, untimely update and information redundancy in customer management of small and mediumsized enterprises. The system includes four core functional modules: historical email analysis, lead pool management, customer management and email archiving. Through email mining and web crawler technology, the system can extract potential customer information from historical emails and enrich lead data; the lead pool management module supports lead information maintenance, status tracking and conversion of high-value leads; the customer management module realizes the maintenance and dynamic tracking of customer information; the email management module provides the archiving of emails and attachments and the structured storage of basic email information. The system provides automated and intelligent customer information management, improves the work efficiency of sales staff, and provides an efficient customer relationship management solution for enterprises....
The study on the functional foods of the fundamental kind gives the formation of rules development and optimization in the Engineering software program. The computation study implements functionally integrated MAEs using the rules and their division into the developing and operating phases of the software platform. The technology used for the software platform is based on the knowledge of software technology and computational algorithms. This includes the creation of the required mathematical formulas responsible for making the program as efficient as possible. New study forces us to pay greater attention to the mathematical roots of linear algebra while teaching the increasing inclusion of ML in software systems, because ML needs a full understanding of the AI and the ML relationships as well as the ML mathematical foundation, such as the inclusion of the mathematical ideas of the software. The advantage of using mathematics in software systems is to make them important, become ubiquitous, and base accurate reasoning on them. This viewpoint is unexplored. It estimates the empirical performance of the course materials on real motors using static mathematical modeling to predict the forthcoming data sets produced. The present investigation shows that mathematical principles can boost machine learning model performance to an extent where software programmers can warrant the creation of even more efficient and stable software systems. To illustrate, optimization methods such as gradient descent, probabilistic model-based methods, and dimension reduction techniques such as PCA have been successful in managing version performance and computational functionality No wonder, the investigation affirms that the hassle is expressed in the processing of high-dimensional data and the large system understanding issues, and also points out the probable future research areas such as designing better algorithms and uncertainty control methods for real-world issues. To sum up, the research stresses the significance of the underpinning mathematical methodologies in the process of learning tools and software engineering disciplines....
This paper presents our endeavors in developing the large-scale, ultra-highresolution E3SM Land Model (uELM), specifically designed for exascale computers furnished with accelerators such as Nvidia GPUs. The uELM is a sophisticated code that substantially relies on High-Performance Computing (HPC) environments, necessitating particular machine and software configurations. To facilitate community-based uELM developments employing GPUs, we have created a portable, standalone software environment preconfigured with uELM input datasets, simulation cases, and source code. This environment, utilizing Docker, encompasses all essential code, libraries, and system software for uELM development on GPUs. It also features a functional unit test framework and an offline model testbed for comprehensive numerical experiments. From a technical perspective, the paper discusses GPU-ready container generations, uELM code management, and input data distribution across computational platforms. Lastly, the paper demonstrates the use of environment for functional unit testing, end-to-end simulation on CPUs and GPUs, and collaborative code development....
Large Language Models (LLMs) are increasingly integrated into software applications, with prompts serving as the primary ‘programming’ interface to guide their behavior. As a result, a new software paradigm, promptware, has emerged, using natural language prompts to interact with LLMs and enabling complex tasks without traditional coding. Unlike traditional software, which relies on formal programming languages and deterministic runtime environments, promptware is based on ambiguous, unstructured, and contextdependent natural language and operates on LLMs as runtime environments, which are probabilistic and nondeterministic. These fundamental differences introduce unique challenges in prompt development. In practice, prompt development is largely ad hoc and experimental, relying on a time-consuming trial-and-error process — a challenge we term the ‘promptware crisis.’ To address this, we propose promptware engineering, a new methodology that adapts established software engineering principles to the process of prompt development. Building on decades of success in traditional software engineering, we envision a systematic framework that includes prompt requirements engineering, design, implementation, testing, debugging, and evolution. Unlike traditional software engineering, our framework is specifically tailored to the unique characteristics of prompt development. This paper outlines a comprehensive roadmap for promptware engineering, identifying key research directions and offering actionable insights to advance LLM-based software development....
Software ecosystem services are essential for the sustainability and functionality of software ecosystems, but they lack comprehensive categorization, hindering further study. This study explores the concept of software ecosystem services through a systematic literature review and brief survey. Drawing analogies from natural ecosystems, we define software ecosystem services as the conditions and processes through which software ecosystems create, provide, and sustain innovation and value creation via software. Software ecosystem services are categorized into four primary types: provisioning, regulating, cultural, and supporting services. Our findings highlight the crucial role of services that do not directly add customer value but are essential for the software ecosystem's functionality, such as authentication and authorization services, collaboration and communication platforms, and app stores. By highlighting these vital yet often overlooked services, the research identifies potential sustainability threats for software ecosystems, such as the dominance of a few major players, which mirrors the risks of monocultures in natural ecosystems. This study lays the groundwork for further research aimed at ensuring the long- term sustainability and resilience of software ecosystems....
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