Quality attribute trade-offs in the embedded systems industry: an exploratory case study

Sas, Darius; Avgeriou, Paris

doi:10.1007/s11219-019-09478-x

Cited by 15 publications

(6 citation statements)

References 31 publications

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“…An observation stemming from the results of RQ2.3 is that most projects prioritise other quality attributes over Maintainability. In our previous work [76] on the matter, we found that (industrial) software practitioners prioritise runtime qualities (e.g. Performance, Availability, Evolvability) over design-time qualities (e.g.…”

Section: Discussionmentioning

confidence: 96%

An architectural technical debt index based on machine learning and architectural smells

Sas¹,

Avgeriou²

2023

Preprint

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A key aspect of technical debt (TD) management is the ability to measure the amount of principal accumulated in a system. The current literature contains an array of approaches to estimate TD principal, however, only a few of them focus specifically on architectural TD, and none of these are fully automated, freely available, and thoroughly validated. Moreover, a recent study has shown that many of the current approaches suffer from certain shortcomings, such as relying on hand-picked thresholds. In this paper, we propose a novel approach to estimate architectural technical debt principal based on machine learning and architectural smells to address such shortcomings. Our approach can estimate the amount of technical debt principal generated by a single architectural smell instance. To do so, we adopt novel techniques from Information Retrieval to train a learning-to-rank machine learning model that estimates the severity of an architectural smell and ensure the transparency of the predictions. Then, for each instance, we statically analyse the source code to calculate the exact number of lines of code creating the smell. Finally, we combine these two values to calculate the technical debt principal. To validate the approach, we conducted a case study and interviewed 16 practitioners, from both open source and industry, and asked them about their opinions on the TD principal estimations for several smells detected in their projects. The results show that for 71% of instances, practitioners agreed that the estimations provided were representative of the effort necessary to refactor the smell.

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Section: Discussionmentioning

confidence: 96%

An architectural technical debt index based on machine learning and architectural smells

Sas¹,

Avgeriou²

2023

Preprint

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“…Studies such as Kasunic & Anderson (2004) and Sas & Avgeriou (2020) indicated that scenario-based or architectural styled assessments are better to understand interoperability measures and associated trade-offs involved between systems i.e. IAM data and tools.…”

Section: Uncorrected Proofmentioning

confidence: 99%

Data-driven asset management in urban water pipe networks: a proposed conceptual framework

Okwori

Pericault

Ugarelli

et al. 2021

Journal of Hydroinformatics

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Analytical tools used in infrastructure asset management of urban water pipe networks are reliant on asset data. Traditionally, data required by analytical tools has not been collected by most water utilities because it has not been needed. The data that is collected might be characterised by low availability, integrity and consistency. A process is required to support water utilities in assessing the accuracy and completeness of their current data management approach and defining improvement pathways in relation to their objectives. This study proposes a framework to enable increased data-driven asset management in pipe networks. The theoretical basis of the framework was a literature review of data management for pipe network asset management and its link to the coherence of set objectives. A survey to identify the current state of data management practice and challenges of asset management implementation in five Swedish water utilities and three focus group workshops with the same utilities was carried out. The main findings of this research were that the quality of pipe network datasets and lack of interoperability between asset management tools was a driver for creating data silos between asset management levels, which may hinder the implementation of data-driven asset management. Furthermore, these findings formed the basis for the proposed conceptual framework. The suggested framework aims to support the selection, development and adoption of improvement pathways to enable increased data-driven asset management in municipal pipe networks. Results from a preliminary application of the proposed framework are also presented.

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“…As discussed, in the aforementioned tools [75] considered the best applications for formal authentication security proofs are Tamarin and AVISPA, due to their implementation of ISO 9798 standard and due to the sensitivity of the patient medical data in the authentication scheme. This survey contained statistics of the most used formal methods in proving schemes validity between 2016 and 2020.…”

Section: Authentication Simulation Toolsmentioning

confidence: 99%

Authentication in Wireless Body Area Network: Taxonomy and Open Challenges

Almuhaideb¹,

Alqudaihi²

2021

Journal on Internet of Things

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Wearable body area network (WBAN) aids the communication between the health providers and patients by supporting health monitoring services. It assists the users to maintain their health status records by collecting the body signals and transmitting them for further processing measurements. However, sensor data are publicly transferred through insecure network that facilitates the attacker malicious acts like performing masquerading attack, man in the middle, and snooping. Several authentication techniques were suggested to levitate the security of the communication channels to preserve the user data from exposure. Moreover, authentication schemes aid plenty of security issues related to user and data privacy, anonymity, repudiation, confidentiality, and integrity, but they lack performance efficiency. On the other hand, it is very hard to find the balance between security and efficiency in most of the authentication schemes, especially for the WBAN platform that consists of memory and processing constraint devices. Therefore, this paper surveys and discusses the latest authentication schemes types, techniques, and system features. Also, it highlights their strengths and weaknesses towards common knowingly attacks and provides a comparison between the popular scheme validation proofs and simulation tools. Thence, this paper draws a path for the new direction of the authentication technologies, the authentication schemes open issues, and the potential future evolution in this area.

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Quality attribute trade-offs in the embedded systems industry: an exploratory case study

Cited by 15 publications

References 31 publications

An architectural technical debt index based on machine learning and architectural smells

An architectural technical debt index based on machine learning and architectural smells

Data-driven asset management in urban water pipe networks: a proposed conceptual framework

Authentication in Wireless Body Area Network: Taxonomy and Open Challenges

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