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Dependable Computing and Security for Software Systems
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Dependable Computing and Security for Software Systems

A special issue of Software (ISSN 2674-113X).

Deadline for manuscript submissions: closed (30 April 2023) | Viewed by 4216

Special Issue Editors

Dr. Junjun Zheng

E-Mail Website
Guest Editor
Department of Information Science and Engineering, Ritsumeikan University, Kyoto, Japan
Interests: software reliability; dependable computing; performance evaluation; computer security
Special Issues, Collections and Topics in MDPI journals
Dr. Xiaoyi Zhang

E-Mail Website
Guest Editor
National Institute of Informatics, Tokyo, Japan
Interests: software testing; fault localization; safety issues for autonomous systems

Special Issue Information

Dear Colleagues,

As we all know, ensuring that software systems behave correctly and reliably is a fundamental challenge especially when facing complexity requirements and cloud computing. Nevertheless, the demand for dependable and secure systems motivates the development of novel techniques or feasible adaptations of existing techniques through addressing more issues, such as components’ interactions, real-time scheduling, self-adaptation, fault tolerance, etc.

This Special Issue aims to highlight advanced discoveries and emerging trends regarding the dependability and security of software systems in both academic society and industry. These findings will explore how we can apply the emerging dependability and security theories and techniques to model and evaluate software systems and also bring insights into how to improve the dependability and security of software.

Dr. Junjun Zheng
Dr. Xiaoyi Zhang
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Software is an international peer-reviewed open access quarterly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Dependability: modeling, evaluation, and techniques
  • Internet of things (IoT) architectures, protocols, security, and privacy
  • Safety-critical systems
  • Self-healing, self-protecting, and self-adaptive systems
  • Quality assurance in software systems
  • Software fault localization
  • Repairing and re-engineering for software systems
  • Security threats and countermeasures for software
  • Malware analysis

Published Papers (2 papers)

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Research

18 pages, 3000 KiB  
Article
Are Infinite-Failure NHPP-Based Software Reliability Models Useful?
by Siqiao Li, Tadashi Dohi and Hiroyuki Okamura
Software 2023, 2(1), 1-18; https://doi.org/10.3390/software2010001 - 23 Dec 2022
Cited by 3 | Viewed by 1893
Abstract
In the literature, infinite-failure software reliability models (SRMs), such as Musa-Okumoto SRM (1984), have been demonstrated to be effective in quantitatively characterizing software testing processes and assessing software reliability. This paper primarily focuses on the infinite-failure (type-II) non-homogeneous Poisson process (NHPP)-based SRMs and [...] Read more.
In the literature, infinite-failure software reliability models (SRMs), such as Musa-Okumoto SRM (1984), have been demonstrated to be effective in quantitatively characterizing software testing processes and assessing software reliability. This paper primarily focuses on the infinite-failure (type-II) non-homogeneous Poisson process (NHPP)-based SRMs and evaluates the performances of these SRMs comprehensively by comparing with the existing finite-failure (type-I) NHPP-based SRMs. In more specific terms, to describe the software fault-detection time distribution, we postulate 11 representative probability distribution functions that can be categorized into the generalized exponential distribution family and the extreme-value distribution family. Then, we compare the goodness-of-fit and predictive performances with the associated 11 type-I and type-II NHPP-based SRMs. In numerical experiments, we analyze software fault-count data, collected from 16 actual development projects, which are commonly known in the software industry as fault-count time-domain data and fault-count time-interval data (group data). The maximum likelihood method is utilized to estimate the model parameters in both NHPP-based SRMs. In a comparison of the type-I with the type-II, it is shown that the type-II NHPP-based SRMs could exhibit better predictive performance than the existing type-I NHPP-based SRMs, especially in the early stage of software testing. Full article
(This article belongs to the Special Issue Dependable Computing and Security for Software Systems)
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12 pages, 298 KiB  
Article
Analysis of Faults in Software Systems Using Tsallis Distribution: A Unified Approach
by Shachi Sharma
Software 2022, 1(4), 473-484; https://doi.org/10.3390/software1040020 - 11 Nov 2022
Viewed by 1410
Abstract
The identification of the appropriate distribution of faults is important for ensuring the reliability of a software system and its maintenance. It has been observed that different distributions explain faults in different types of software. Faults in large and complex software systems are [...] Read more.
The identification of the appropriate distribution of faults is important for ensuring the reliability of a software system and its maintenance. It has been observed that different distributions explain faults in different types of software. Faults in large and complex software systems are best represented by Pareto distribution, whereas Weibull distribution fits enterprise software well. An analysis of faults in open-source software endorses generalized Pareto distribution. This paper presents a model, called the Tsallis distribution, derived using the maximum-entropy principle, which explains faults in many diverse software systems. The effectiveness of Tsallis distribution is ascertained by carrying out experiments on many real data sets from enterprise and open-source software systems. It is found that Tsallis distribution describes software faults better and more precisely than Weibull and generalized Pareto distributions, in both cases. The applications of the Tsallis distribution in (i) software fault-prediction using the Bayesian inference method, and (ii) the Goal and Okumoto software-reliability model, are discussed. Full article
(This article belongs to the Special Issue Dependable Computing and Security for Software Systems)
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