Open BOK on Software Engineering Educational Context: A Systematic Literature Review

Quezada–Sarmiento, Pablo Alejandro; Elorriaga, Jon A.; Arruarte, Ana; Washizaki, Hironori

doi:10.3390/su12176858

Cited by 7 publications

(2 citation statements)

References 72 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The window size is managed by the chronological split approach; this is helpful in processing the data in chronological order when they come in streaming format, as suggested by Lokan and Mendes [36]. Moreover, the RQs are answered by taking the guidance of the Software Engineering Body of Knowledge (SWEBOK V.3.0) [55]. The acquired knowledge from RQs could help to enrich the software professionals for building more reliable software systems.…”

Section: Discussionmentioning

confidence: 99%

Cross-Version Software Defect Prediction Considering Concept Drift and Chronological Splitting

Kabir,

Rehman,

Islam

et al. 2023

Symmetry

View full text Add to dashboard Cite

Concept drift (CD) refers to a phenomenon where the data distribution within datasets changes over time, and this can have adverse effects on the performance of prediction models in software engineering (SE), including those used for tasks like cost estimation and defect prediction. Detecting CD in SE datasets is difficult, but important, because it identifies the need for retraining prediction models and in turn improves their performance. If the concept drift is caused by symmetric changes in the data distribution, the model adaptation process might need to account for this symmetry to maintain accurate predictions. This paper explores the impact of CD within the context of cross-version defect prediction (CVDP), aiming to enhance the reliability of prediction performance and to make the data more symmetric. A concept drift detection (CDD) approach is further proposed to identify data distributions that change over software versions. The proposed CDD framework consists of three stages: (i) data pre-processing for CD detection; (ii) notification of CD by triggering one of the three flags (i.e., CD, warning, and control); and (iii) providing guidance on when to update an existing model. Several experiments on 30 versions of seven software projects reveal the value of the proposed CDD. Some of the key findings of the proposed work include: (i) An exponential increase in the error-rate across different software versions is associated with CD. (ii) A moving-window approach to train defect prediction models on chronologically ordered defect data results in better CD detection than using all historical data with a large effect size (δ≥0.427).

show abstract

Section: Discussionmentioning

confidence: 99%

Cross-Version Software Defect Prediction Considering Concept Drift and Chronological Splitting

Kabir,

Rehman,

Islam

et al. 2023

Symmetry

View full text Add to dashboard Cite

show abstract

“…Identification, synthesis, and evaluation of all quantitative and/or qualitative data are required for SLR in order to produce a robust, experimentally derived response to a specific research topic [39][40][41][42]. The EndNote reference management program was used to organize the retrieved articles into libraries and check them for duplications.…”

Section: Systematic Literature Reviewmentioning

confidence: 99%

Blockchain Systems in Embedded Internet of Things: Systematic Literature Review, Challenges Analysis, and Future Direction Suggestions

Darbandi

Al-Khafaji²,

Nasab

et al. 2022

Electronics

View full text Add to dashboard Cite

Internet of Things (IoT) environments can extensively use embedded devices. Without the participation of consumers; tiny IoT devices will function and interact with one another, but their operations must be reliable and secure from various threats. The introduction of cutting-edge data analytics methods for linked IoT devices, including blockchain, may lower costs and boost the use of cloud platforms. In a peer-to-peer network such as blockchain, no one has to be trusted because each peer is in charge of their task, and there is no central server. Because blockchain is tamper-proof, it is connected to IoT to increase security. However, the technology is still developing and faces many challenges, such as power consumption and execution time. This article discusses blockchain technology and embedded devices in distant areas where IoT devices may encounter network shortages and possible cyber threats. This study aims to examine existing research while also outlining prospective areas for future work to use blockchains in smart settings. Finally, the efficiency of the blockchain is evaluated through performance parameters, such as latency, throughput, storage, and bandwidth. The obtained results showed that blockchain technology provides security and privacy for the IoT.

show abstract

Used of Web Scraping on Knowledge Representation Model for Bodies of Knowledge as a Tool to Development Curriculum

Quezada–Sarmiento

Elorriaga

Arruarte

et al. 2021

Advances in Intelligent Systems and Computing

View full text Add to dashboard Cite

Open BOK on Software Engineering Educational Context: A Systematic Literature Review

Cited by 7 publications

References 72 publications

Cross-Version Software Defect Prediction Considering Concept Drift and Chronological Splitting

Cross-Version Software Defect Prediction Considering Concept Drift and Chronological Splitting

Blockchain Systems in Embedded Internet of Things: Systematic Literature Review, Challenges Analysis, and Future Direction Suggestions

Used of Web Scraping on Knowledge Representation Model for Bodies of Knowledge as a Tool to Development Curriculum

Contact Info

Product

Resources

About