Research methods in computing

Holz, Hilary J.; Applin, Anne G.; Haberman, Bruria; Joyce, Donald; Purchase, Helen C.; Reed, Catherine L.

doi:10.1145/1189215.1189180

Cited by 20 publications

(9 citation statements)

References 0 publications

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“…SORM supports a practical principle as it tries to give practical answers and output 38 in the area of software project development. A design approach that follows build and process procedure, as opposed to the design science research methodology, according to previous studies 39,40 shall be considered. The benefit and beauty of this study are that it proffers practical solutions to challenges facing the development of quality software products.…”

Section: Methodsmentioning

confidence: 99%

Toward ontology‐based risk management framework for software projects: An empirical study

Abioye

Arogundade

Misra

et al. 2020

J Software Evolu Process

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Software risk management is a proactive decision-making practice with processes, methods, and tools for managing risks in a software project. Many existing techniques for software project risk management are textual documentation with varying perspectives that are nonreusable and cannot be shared. In this paper, a life-cycle approach to ontology-based risk management framework for software projects is presented. A dataset from literature, domain experts, and practitioners is used. The identified risks are refined by 19 software experts; risks are conceptualized, modeled, and developed using Protégé. The risks are qualitatively analyzed and prioritized, and aversion methods are provided. The framework is adopted in real-life software projects. Precision recall and F-measure metrics are used to validate the performance of the extraction tool while performance and perception evaluation are carried out using the performance appraisal form and technology acceptance model, respectively. Mean scores from performance and perception evaluation are compared with evaluation concept scale. Results showed that cost is reduced, high-quality projects are delivered on time, and software developers found this framework a potent tool needed for their day-today activities in software development. K E Y W O R D S hierarchical risk classification breakdown structure (HBRS), performance appraisal form (PAF), software development life cycle (SDLC), software ontology-based risk management (SORM), software risk ontology (SRO), technology acceptance model (TAM) 1 | INTRODUCTION A software project is a process involving many activities such as domain analysis, requirement specification, communication with developers and end users, designing and production of various artifacts, evaluating and testing of software products, and installation and maintenance of application at the end user's site. 1 The demands on software development are increasing daily due to an increase in knowledge of information technology. More people are aware of the importance of information systems and how tasks can be carried out easily by adopting them. Also, the consideration of the world as a global village is one of the major quests for information technology, which has led to a global increase in the demand for information systems. With the increase in demand for information systems, it is important to know that software development is a complex task due to various artifacts and the phases involved in its implementation. Although software projects management is gaining more recognition from industry, military, finance, and academia, yet many projects are uncompleted and could not be delivered because of its failure to meet up with the initial requirements. Some projects that are delivered failed to meet up with the scheduled time, which invariably leads to an

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Section: Methodsmentioning

confidence: 99%

Toward ontology‐based risk management framework for software projects: An empirical study

Abioye

Arogundade

Misra

et al. 2020

J Software Evolu Process

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show abstract

“…The Orgfarmob, is underpinned by pragmatism philosophy as it seeks to provide practical solutions and outcomes [27]. It follows the build and process methods from a design research point of view [28,29], rather than design science research methodology strategy. Given the emphasis on practical solutions, the logical design, presented as the design process, is the primary focus of this paper: the development of orgfarmob marketspace.…”

Section: Methodsmentioning

confidence: 99%

“…Before proceeding with 'requirement analysis', 'architectural framework' and 'design and use-case design considerations', we quickly outline the orgfarmob marketspace build and process approach. In line with our pragmatic approach, we built on aspects of the framework for computing research methods [29]. We only utilized aspects that we required and applicable to our study.…”

Section: Methodsmentioning

confidence: 99%

An Intelligent Marketspace Mobile Application for Marketing Organic Products

Arogundade

Abayomi‐Alli

Adesemowo

et al. 2020

Lecture Notes in Computer Science

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Sustainable food security (Sfs) desires not only that people always have passage to ample and nutritious food, but also that this food be formed with minimum environmental impact. This research is aimed at developing a mobile application for marketing organic farm products with the functionality of automated geo-location services, preferred goods delivery services, easy access to different organic farm produce. The mobile user platform consists of the Presentation, Business, Data and Data storage which is a slight variation of the Model-View-Controller architecture. It also takes into deep awareness the configuration, security and communications aspect as these are the underlying factors for the robustness of mobile application. The Presentation Tier consists of the user interface and the logic used to navigate around the user interface meaningfully. It modifies and shows information into a human distinct pattern. The Business Logic tier is essentially efficient for information transfer between the user interface and the database of the project. The last layer of the threetiered architecture is the Data Access tier, which is made up of the Database servers. The application was implemented in Java, SQLite (local) and PHP for the backend server and Amazon Web Services for cloud infrastructure. Farmers were engaged in cursory testing. Users find the application concept very interesting.

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“…The strong connection between computing disciplines including AI allow Hall and Rapanotti assertion of SE of borrowing from IS based on similarity and Kroeze et al aligning IS and transdisciplinarity as way of advancing IS applicable to these computing disciplines especially AI that is transdisciplinary. Computing disciplines borrows and uses solutions from other disciplines and then develops a computing specific solution [48]. With islands of transdisciplinarity in AI, SE and IS computing research is ready to start carrying out transdisciplinary research including developing a computing trans-field.…”

Section: Need For Transdisciplinary Approachesmentioning

confidence: 99%

“…Design science research frameworks have also been introduced in AI expert system development [53]. Design science and other research methods are used in information systems, computer science, information technology and computer engineering [48] these includes Artificial intelligence as being emphasized in computer engineering, computer science and information systems [43] while emphasis was low in Software engineering and IT in 2005 when research was published the emphasis has increased in information technology and SE as well as SE in AI. Aligning SE and AI research with design science and innovation methods will make two disciplines innovation and research activities more scientific [50].…”

Section: Need For Transdisciplinary Approachesmentioning

confidence: 99%

Aligning Software Engineering and Artificial Intelligence With Transdisciplinary

Mambo¹

2022

tjes

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Study examined AI and SE transdisciplinarity to find ways of aligning them to enable development of AI-SE transdisciplinary theory. Literature review and analysis method was used. The findings are AI and SE transdisciplinarity is tacit with islands within and between them that can be linked to accelerate their transdisciplinary orientation by codification, internally developing and externally borrowing and adapting transdisciplinary theories. Lack of theory has been identified as the major barrier toward towards maturing the two disciplines as engineering disciplines. Creating AI and SE transdisciplinary theory would contribute to maturing AI and SE engineering disciplines. Implications of study are transdisciplinary theory can support mode 2 and 3 AI and SE innovations; provide an alternative for maturing two disciplines as engineering disciplines. Study’s originality it’s first in SE, AI or their intersections.

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Research methods in computing

Cited by 20 publications

References 0 publications

Toward ontology‐based risk management framework for software projects: An empirical study

Toward ontology‐based risk management framework for software projects: An empirical study

An Intelligent Marketspace Mobile Application for Marketing Organic Products

Aligning Software Engineering and Artificial Intelligence With Transdisciplinary

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