Software release life cycle

Summary

The software release life cycle is the process of developing, testing, and distributing a software product. It typically consists of several stages, such as pre-alpha, alpha, beta, and release candidate, before the final version, or "gold", is released to the public. Pre-alpha refers to the early stages of development, when the software is still being designed and built. Alpha testing is the first phase of formal testing, during which the software is tested internally using white-box techniques. Beta testing is the next phase, in which the software is tested by a larger group of users, typically outside of the organization that developed it. The beta phase is focused on reducing impacts on users and may include usability testing. After beta testing, the software may go through one or more release candidate phases, in which it is refined and tested further, before the final version is released. Some software, particularly in the internet and technology industries, is released in a

Official source

https://en.wikipedia.org/wiki/Software_release_life_cycle

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Proposal of a Closed Loop Framework for the Improvement of Industrial Systems' Life Cycle Performances: Experiences from the LinkedDesign Project

Ana Milicic

The context where European manufacturers of industrial systems operate has dramatically changed over recent years: the pressure of emerging countries they have to face, policy makers' environmental laws and industrial companies' interests are pushing towards sustainable manufacturing and a holistic view of industrial systems. Designers and system engineers are the main actors involved, because they have high influence on product life cycle costs and environmental impacts. However they need tools to pursue a holistic view. The aim of this paper is to propose a closed loop framework to improve life cycle performances of industrial systems, focusing on the automotive sector. (C) 2015 The Authors. Published by Elsevier B.V.

Elsevier Science Bv2015

Weighted flow time is a fundamental and very well-studied objective function in scheduling. In this paper, we study the setting of a single machine with preemptions. The input consists of a set of jobs, characterized by their processing times, release times, and weights and we want to compute a (possibly preemptive) schedule for them. The objective is to minimize the sum of the weighted flow times of the jobs, where the flow time of a job is the time between its release date and its completion time. It had been a long-standing open problem to find a polynomial time O(1)-approximation algorithm for this setting. In a recent break-through result, Batra, Garg, and Kumar (FOCS 2018) found such an algorithm if the input data are polynomially bounded integers, and Feige, Kulkarni, and Li (SODA 2019) presented a black-box reduction to this setting. The resulting approximation ratio is a (not explicitly stated) constant which is at least 10000. In this paper we improve this ratio to 2 + epsilon. The algorithm by Batra, Garg, and Kumar (FOCS 2018) reduces the problem to DEMAND MULTICUT ON TREES and solves the resulting instances via LP-rounding and a dynamic program. Instead, we first reduce the problem to a (different) geometric problem while losing only a factor 1 + epsilon, and then solve its resulting instances up to a factor of 2 + epsilon by a dynamic program. In particular, our reduction ensures certain structural properties, thanks to which we do not need LP-rounding methods. We believe that our result makes substantial progress towards finding a PTAS for weighted flow time on a single machine.

ASSOC COMPUTING MACHINERY2021

Integrity and Metadata Protection in Data Retrieval

Kirill Nikitin

Secure retrieval of data requires integrity, confidentially, transparency, and metadata-privacy of the process. Existing protection mechanisms, however, provide only partially these properties: encryption schemes still expose cleartext metadata, protocols for private information retrieval neglect data integrity, and data-distribution architectures forego transparency. In this dissertation, by designing new cryptographic primitives and security architectures that provide a more comprehensive protection, we improve on the current security and privacy practices in data retrieval. First, we propose a new format for encrypted data; it protects both content and all encryption metadata, such as the application, the intended recipients, and the algorithms used. The format comes with a cryptographically-agile encoding scheme that facilitates efficient decryption of such ciphertexts without cleartext markers. Second, to address the lack of integrity in privacy-preserving data-retrieval protocols, we introduce the concept of single-server verifiable private information retrieval. In contrast to existing solutions where, in some deployment scenarios, a malicious server can violate client privacy by selectively tampering with the data, our approach ensures that an honest client either correctly obtains the data from the systemâs server or detects server misbehavior and aborts. Finally, we present a software-update framework that reinforces software-distribution processes. Building on the concepts of decentralization and verifiability, our framework eliminates single points of failure, enforces transparency, and ensures integrity and authenticity of software releases. By implementing and experimentally evaluating our primitives and framework, we demonstrate that better protection is practical and incurs only a modest additional cost.

EPFL2021