| Discipline name | Position | Best Scientists | Publications | D-Index |
|---|---|---|---|---|
| Computer Science | 1086 | 5 | 6 | 2 |
The topics of Software engineering, Software, Software development, Software system and Data science are the focal point of discussions in the journal. Topics in Software engineering explored in it were investigated in conjunction with research in Software design, Personal software process, Social software engineering, Software construction and Software development process. While the primary focus in the journal is Social software engineering, it also dissects topics surrounding Knowledge management and Task (project management) as a whole.
While it focused on Software, it was also able to explore topics like Agile software development, Documentation, Test case and Process management. Issues in Test case were discussed, taking into consideration concepts from other disciplines like Data mining, Test Management Approach and White-box testing. Some problems in Data mining that were presented in it overlapped with concepts under Software metric, Mutation (genetic algorithm), Unit testing, Feature model and Test set.
The presented Software development study covers related areas such as Resource-oriented architecture, Component-based software engineering and Software requirements and also touches on topics like Empirical research. It features works in Software system, more specifically Search-based software engineering, and explores their relation to disciplines like Internet of Things. Many of the studies tackled connect Data science with a similar field of study like Identification (information).
The journal papers focus largely on the fields of Software engineering, Software development, Source code, Software system and Software. While the published articles primarily focused on Software engineering, they also opened dialogues on the discipline of Empirical research. Aside from investigating topics in Software construction under Software development, the journal papers also explore concepts in Manifesto and Silver bullet.
The journal mainly tackles studies in Software development, Software, Software engineering, Data science and Proof of concept. Software development research featured in Journal of Software Engineering Research and Development incorporates concerns from various other topics such as Java, Categorization, Microservices and Identification (information). The journal explores Software concepts, specifically Software system and Requirements engineering but expands to research in Context awareness and Internet of Things.
While work presented in Journal of Software Engineering Research and Development provided substantial information on Software engineering, it also covered topics in Cover (telecommunications), Green computing and Software development process. It focuses on Data science but the discussions also offer insight into other areas such as Information privacy, Statistical model and Source code. It aims to bridge the gap between the study of Proof of concept and research in different fields like Ontology (information science), Domain (software engineering), Knowledge management, Usability and Software quality.
A key indicator for each journal is its effectiveness in reaching other researchers with the papers published at that venue.
The chart below presents the interquartile range (first quartile 25%, median 50% and third quartile 75%) of the number of citations of articles over time.
The top authors publishing in Journal of Software Engineering Research and Development (based on the number of publications) are:
The overall trend for top authors publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top authors.
Only papers with recognized affiliations are considered
The top affiliations publishing in Journal of Software Engineering Research and Development (based on the number of publications) are:
The overall trend for top affiliations publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top affiliations.
The publication chance index shows the ratio of articles published by the best research institutions in the journal edition to all articles published within that journal. The best research institutions were selected based on the largest number of articles published during all editions of the journal.
The chart below presents the percentage ratio of articles from top institutions (based on their ranking of total papers).Top affiliations were grouped by their rank into the following tiers: top 1-10, top 11-20, top 21-50, and top 51+. Only articles with a recognized affiliation are considered.
During the most recent 2021 edition, 0.00% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 66.67% were posted by at least one author from the top 10 institutions publishing in the journal. Another 11.11% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 11.11% of all publications and 11.11% were from other institutions.
A very common phenomenon observed among researchers publishing scientific articles is the intentional selection of journals they have already attended in the past. In particular, it is worth analyzing the case when the authors participate in the same journal from year to year.
The Returning Authors Index presented below illustrates the ratio of authors who participated in both a given as well as the previous edition of the journal in relation to all participants in a given year.
The graph below shows the Returning Institution Index, illustrating the ratio of institutions that participated in both a given and the previous edition of the conference in relation to all affiliations present in a given year.
Our experience to innovation index was created to show a cross-section of the experience level of authors publishing in a journal. The index includes the authors publishing at the last edition of a journal, grouped by total number of publications throughout their academic career (P) and the total number of citations of these publications ever received (C).
The group intervals were selected empirically to best show the diversity of the authors' experiences, their labels were selected as a convenience, not as judgment. The authors were divided into the following groups:
The chart below illustrates experience levels of first authors in cases of publications with multiple authors.
While software engineering research and development is an extensive field unto itself, career opportunities within this realm are equally extensive and rewarding. From software developers to data scientists, the industry offers numerous roles that leverage the skills and knowledge gained from in-depth study and research on software engineering topics. One such role is of a preschool teacher assistant, albeit less conventional, this role integrates technology and education. If you’re in Arizona, becoming a preschool teacher assistant involves certain prerequisites and qualifications. These preschool teacher assistant requirements in Arizona explore the ways educational technology can intersect with early childhood education, allowing for innovative teaching methods using the latest software systems. Besides academia, there are opportunities in industries such as gaming, finance, healthcare, and more. Often, these sectors seek professionals who can bridge the gap between traditional practices and new technological applications, in turn creating more efficient and effective processes. Ultimately, the diversity of fields that software engineering research and development can be applied to makes for a robust and dynamic career landscape. Whether specializing in a particular aspect of software engineering or working in a role that intersects with other disciplines, the potential for professional growth and development is vast.
Danyllo Valente da Silva;Bruno Pedraça de Souza;Taisa Guidini Goncalves;Guilherme Horta Travassos
(2021)For students interested in studying Computer Science, exploring related online degrees can provide flexible and accelerated learning opportunities. Many look for the easiest degree to get to build foundational skills before advancing into more specialized fields.
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