Journal of Software Engineering & Intelligent Systems

ISSN: 2518-8739 (Online)
DECEMBER 2020 | VOLUME. 5  ISSUE. 3
Title:

CONTEXT METAMODEL IN PERVASIVE SYSTEMS FOR DYNAMIC SOFTWARE PRODUCT LINES

Authors:

Amougou Ngoumou, Marcel Fouda Ndjodo

Abstract:

Driven by the emergence of new computing environments, dynamically evolving software product lines makes it impossible for developers to adapt software with human-centric processes. Instead, there is an increasing need for automation tools that continuously adapt software into execution, in order to push updates or adapt existing software regarding contextual and business changes. Existing solutions fall short on providing fault tolerant, reproducible adaptations that would scale on heterogeneous environments. This article focuses on providing context meta-model in dynamic environments, such as Pervasive Computing (Ubiquitous Computing) environments, for dynamic software product lines. This kind, of context models, is required to describe the changes of Pervasive Computing environments. By providing an abstract model, we are thus implementation-independent and allow existing context modeling approaches to rely on this model to extend their support.

Keywords: product line engineering; dynamic software product lines; dynamic environments; pervasive computing environments; context metamodel;
Available: CONTEXT METAMODEL IN PERVASIVE SYSTEMS FOR DYNAMIC SOFTWARE PRODUCT LINES by Amougou Ngoumou, Marcel Fouda Ndjodo will be available under cc by-nc 4.0 License on 31st December 2020. Permissions beyond the scope of this license may be available at JSEIS.
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Title:

DATA MINING BASED PREDICTION OF INTERNAL SOFTWARE QUALITY USING OO-METRIC AND MACHINE LEARNING TECHNIQUES

Authors:

Iqra Batool

Abstract:

The data mining field uses methods like artificial intelligence, machine learning, deep learning and statistics. The most notable data mining strategy is classification. Data mining and machine learning techniques have great impact on software quality and fault prediction. The development of software is a very critical process. Software Engineers are doing their best to get high quality software at every stage of the software development life cycle. Software quality can be measured in multi perspectives like internal and external perspective as determine by McCall’s quality model. The main concern of this research is internal quality of the software. By using object-oriented metric, we can measure the internal quality. The code quality can be assessed with the use of object-oriented metrics. A good idea of the code under review illustrates these metrics. In this article, to distinguish the methods of the code into two forms as Function Envy or not, we merged the OO metrics with some data mining algorithms. In an open source Java initiative, the paper applied the methodology. Furthermore, with numerous methods, test the outcomes with other chosen detection methods. During cross validation against the use of the training set alternatives in the K-Nearest Neighbor algorithm, the results showed high accuracy.

Keywords: internal software quality; data mining; machine learning; oo-metrics; k-nearest neighbour; code quality;
Available: DATA MINING BASED PREDICTION OF INTERNAL SOFTWARE QUALITY USING OO-METRIC AND MACHINE LEARNING TECHNIQUES by Iqra Batool will be available under cc by-nc 4.0 License on 31st December 2020. Permissions beyond the scope of this license may be available at JSEIS.
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Title:

IMPORTANCE OF INTERNET OF THINGS AND UNDERSTANDING THE FACTORS AFFECTING ITS PERFORMANCE

Authors:

Marrium Mehmood

Abstract:

Internet of Things (IoT) is an environment where things (physical objects) that have some intelligence are connected through the internet and they communicate and share data with each other. The coming era is the era of the Internet of things. The IoT technology has given game-changing boundless opportunities to mankind and industries. For the success of the IoT system operational and non-functional both requirements should be given equal importance. The handling of requirements is the key challenge to IoT technology. Some main requirements on the Internet of things technology are presented in this paper. IoT is transforming the way of living by providing numerous benefits but it faces several issues, security and privacy are the most critical challenges to IoT. This paper will emphasize on different researches conducted on different studies of IoT and will give a roadmap for the further research studies. This paper aims to highlight the importance and open challenges to IoT technology, we examined different survey papers on IoT and found limitations in them. The growth of the Internet and IoT technology is analyzed and presented. Moreover, IoT applications in routine life and industries are discussed in this study.

Keywords: internet of things; machine-to-machine; non-functional requirements; operational requirements; compound annual growth rate; IOT
Available: IMPORTANCE OF INTERNET OF THINGS AND UNDERSTANDING THE FACTORS AFFECTING ITS PERFORMANCE by Marrium Mehmood will be available under cc by-nc 4.0 License on 31st December 2020. Permissions beyond the scope of this license may be available at JSEIS.
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Title:

EVALUATION OF PRODUCTIVITY USING SCRUM-VERSION CONTROL ON DEVELOPMENT MANAGEMENT

Authors:

Alnour Ibrahim Alnour Ali, Haysam E. Elamin , Ashraf Osman Ibrahim

Abstract:

This paper describes the extent of enhancements that can be gained from combining scrum methodology with version control, to achieve the objectives of reducing the development time and enhancing the communication between developers in case of them being spatially separated, and also to mitigate some of the causes that lead to work slop to the next iteration in addition to the facilitation of code integration. This combination is represented in the form of Gitlab Scrum version control tool. The goals of the research were achieved by comparing the results gained from software estimation generated by using the function point and team experience factors using it as a base for the comparison, with the actual results collected from the interviews meeting with the University of Khartoum development team scrum master and the statistics from Gitlab tool. The results showed that the enhancement presented after the combination is implemented in ERP system was 46.68% less effort, 40% less schedule, 53.43% less staff, 99% code success ratio, and 19% enhancement in the task slop to the next iteration. Given the great results gained from the combination of scrum version control research recommends the development of ERP systems using the combined method.

Keywords: scrum methodology; version control; scrum method enhancement; Gitlab; ERP systems; team productivity;
Available: EVALUATION OF PRODUCTIVITY USING SCRUM-VERSION CONTROL ON DEVELOPMENT MANAGEMENT by Alnour Ibrahim Alnour Ali, Haysam E. Elamin , Ashraf Osman Ibrahim will be available under cc by-nc 4.0 License on 31st December 2020. Permissions beyond the scope of this license may be available at JSEIS.
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