Pricing4SaaS: a suite of software libraries for pricing-driven feature toggling
- URL: http://arxiv.org/abs/2403.14004v1
- Date: Wed, 20 Mar 2024 22:08:41 GMT
- Title: Pricing4SaaS: a suite of software libraries for pricing-driven feature toggling
- Authors: Alejandro García-Fernández, José Antonio Parejo, Pablo Trinidad, Antonio Ruiz-Cortés,
- Abstract summary: This paper introduces a novel suite of software libraries named Pricing4SaaS.
It is designed to facilitate the implementation of pricing-driven feature toggles in both the front-end and back-end of systems.
We present a case study based on the popular Spring PetClinic project to illustrate how the suite can be leveraged to optimize developer productivity.
- Score: 42.8610435437513
- License: http://creativecommons.org/licenses/by-nc-nd/4.0/
- Abstract: As the digital marketplace evolves, the ability to dynamically adjust or disable features and services in response to market demands and pricing strategies becomes increasingly crucial for maintaining competitive advantage and enhancing user engagement. This paper introduces a novel suite of software libraries named Pricing4SaaS, designed to facilitate the implementation of pricing-driven feature toggles in both the front-end and back-end of SaaS systems, and discuss its architectural design principles. Including Pricing4React for front-end and Pricing4Java for back-end, the suite enables developers a streamlined and efficient approach to integrating feature toggles that can be controlled based on pricing plans, emphasizing centralized toggle management, and secure synchronization of the toggling state between the client and server. We also present a case study based on the popular Spring PetClinic project to illustrate how the suite can be leveraged to optimize developer productivity, avoiding technical debt, and improving operational efficiency.
Related papers
- Read-ME: Refactorizing LLMs as Router-Decoupled Mixture of Experts with System Co-Design [59.00758127310582]
We propose a novel framework Read-ME that transforms pre-trained dense LLMs into smaller MoE models.
Our approach employs activation sparsity to extract experts.
Read-ME outperforms other popular open-source dense models of similar scales.
arXiv Detail & Related papers (2024-10-24T19:48:51Z) - Racing the Market: An Industry Support Analysis for Pricing-Driven DevOps in SaaS [42.8610435437513]
The paradigm has popularized the usage of pricings, allowing providers to offer customers a wide range of subscription possibilities.
This creates a vast configuration space for users, enabling them to choose the features and support guarantees that best suit their needs.
Regardless of the reasons why changes in these pricings are made, the frequency of changes within the elements of pricings continues to increase.
arXiv Detail & Related papers (2024-09-23T15:59:21Z) - A Primal-Dual Online Learning Approach for Dynamic Pricing of Sequentially Displayed Complementary Items under Sale Constraints [54.46126953873298]
We address the problem of dynamically pricing complementary items that are sequentially displayed to customers.
Coherent pricing policies for complementary items are essential because optimizing the pricing of each item individually is ineffective.
We empirically evaluate our approach using synthetic settings randomly generated from real-world data, and compare its performance in terms of constraints violation and regret.
arXiv Detail & Related papers (2024-07-08T09:55:31Z) - Pricing4SaaS: Towards a pricing model to drive the operation of SaaS [45.98329715499677]
This paper introduces a generalized specification model for the pricing structures of systems that apply the Software as a Service (SaaS) licensing model.
With its proven expressiveness, Pricing4SaaS aims to become the cornerstone of pricing-driven IS engineering.
arXiv Detail & Related papers (2024-03-30T10:23:55Z) - Pricing-driven Development and Operation of SaaS : Challenges and Opportunities [45.98329715499677]
Using PetClinic as a case study, we explore the implications of a Pricing-driven Development and Operation approach of systems.
Our discussion aims to provide strategic insights for the community to navigate the complexities of this integrated approach, fostering a better alignment between business models and technological capabilities for effective cloud-based services.
arXiv Detail & Related papers (2024-03-20T22:11:58Z) - LMaaS: Exploring Pricing Strategy of Large Model as a Service for
Communication [11.337245234301857]
We argue that a pay-as-you-go service mode will be suitable in this context, referred to as Large Model as a Service (LM)
We propose an Iterative Model Pricing (IMP) algorithm that optimize the prices of large models iteratively by reasoning customers' future rental decisions.
In the second step, we optimize customers' selection decisions by designing a robust selecting and renting algorithm.
arXiv Detail & Related papers (2024-01-05T07:19:19Z) - Function Design for Improved Competitive Ratio in Online Resource
Allocation with Procurement Costs [16.68130648568593]
We study the problem of online resource allocation, where multiple customers arrive the seller must allocate resources to each incoming customer while also facing a procurement cost for the total allocation.
arXiv Detail & Related papers (2020-12-23T02:32:47Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.