Systematic literature review on software quality for AI-based software

Gezici, Bahar; Tarhan, Ayça

doi:10.1007/s10664-021-10105-2

Cited by 14 publications

(2 citation statements)

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“…The evaluation indicators of the work developed by the developers were mainly the system (i.e., its functionalities and design, including the appearance and size of the device and both mobile and web application interfaces), although the quality of the software code, the software documentation [10] and the project documentation [31] provided, as well as just-in-time delivery, were also considered. At the end of the development period, they achieved varying degrees of compliance, as reflected in the continuous evaluations of the deliverables that resulted from the development of the assigned systems.…”

Section: Validation Of the Development Methodologymentioning

confidence: 99%

Internet of Things (IoT)-based indoor plant care system

Guerrero-Ulloa

Méndez-García

Torres-Lindao

et al. 2023

AIS

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The list of Sustainable Development Goals created by the United Nations include good health and well-being as one of its primary objectives. Pollution is a concern worldwide, and pollution levels inside buildings (homes or workplaces) can be higher than outdoors. To alleviate this problem and improve air quality, ornamental plants can be used. This paper presents the application of Internet of Things (IoT) technologies to develop a system called P4L, an acronym for “Plants for Life”. The objective of P4L is the automated care of potted plants to improve air quality and make the indoor environments of a building healthier. This IoT-based system (IoTS) has been developed through low-cost Arduino-compatible components. In addition, the Test-Driven Development Methodology for IoT-based Systems (TDDM4IoTS) has been used to guide P4L development. In fact, this article shows the result of the application of this methodology (phase by phase), with the help of the Test-Driven Development Tool for IoT-based Systems (TDDT4IoTS), which supports the aforementioned methodology, to develop P4L. To validate the methodology, we conducted a survey among developers that have used it, the results of which show that it is efficient and covers all aspects of IoTS development.

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Section: Validation Of the Development Methodologymentioning

confidence: 99%

Internet of Things (IoT)-based indoor plant care system

Guerrero-Ulloa

Méndez-García

Torres-Lindao

et al. 2023

AIS

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“…Thus, automatic analysis of NFRs can have great influence on the software development lifecycle. When NFRs are poorly defined, misunderstood, or neglected during the development process, the resulting software product can suffer in several ways, such as security vulnerabilities, lack of scalability, poor usability, maintenance difficulties, and various performance and reliability issues [31], [32].…”

Section: Legal (L)mentioning

confidence: 99%

BERT-Based Approach for Greening Software Requirements Engineering Through Non-Functional Requirements

Subahi

2023

IEEE Access

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The incorporation of sustainability principles during the requirements engineering phase of the development life cycle constitutes greening software requirements. This incorporation can have a variety of effects on the software design employed in modern and cutting-edge information technology (IT) systems. When sustainability principles are incorporated into requirements engineering, software design priorities can change and address current design issues such as energy and resource consumption, modularity, maintainability, and adaptability. In contrast to other green approaches that consider sustainable development, there is a further need to investigate the relationship between software development and the relevant green principles of sustainability during the requirements engineering phase. We present a new mechanism for mapping software nonfunctional requirements (NFRs) to defined dimensions of green software sustainability, consisting of two mapping steps: 1) between NFRs and sustainability dimensions; and 2) between sustainability dimensions and two clusters of green IT aspects defined in this work. The overall architecture of the promising approach is based on the use of the Bidirectional Encoder Representations from Transformers (BERT) language model with an expanded dataset. We consider transfer learning and domainspecific fine-tuning capabilities for constructing and evaluating a model specifically tailored for developing a proof of concept of the greening software requirements engineering task, as language models have recently emerged as a potent technique in the field of software engineering, with numerous applications in code analysis, automated documentation, and code generation. In addition, we test the model's performance using an extended version of the PROMISE_exp dataset after adding a new binary classification column for categorizing sustainability dimensions into two defined clusters: Eco-technical and Socioeconomic, and having a selected domain expert label the raw data. The model's efficiency is evaluated using four matrices-1) accuracy; 2) precision; 3) recall; and 4) F1 score-across a variety of epoch and batch sizes. Our numerical results demonstrate the viability of the approach in text classification tasks via performing well in mapping NFRs to software sustainability dimensions. This acts as a proof of concept for automating the sustainability measurement of software awareness at the early development stage. In addition, the results emphasize the importance of domain-specific fine-tuning and transfer learning for obtaining high performance in classification tasks in requirements engineering.

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