| Discipline name | Position | Best Scientists | Publications | D-Index |
|---|---|---|---|---|
| Computer Science | 481 | 56 | 57 | 12 |
Software engineering, Software, Software quality, Software development and Quality (business) are the subjects of interest in Software Quality Journal. The studies in Software engineering featured incorporate elements of Engineering management, Systems engineering, Software construction, Software requirements and Software development process. While the journal focused on Software, it was also able to explore topics like Reliability engineering, Empirical research, Data mining and Artificial intelligence.
Data mining research featured in Software Quality Journal incorporates concerns from various other topics such as Machine learning and Test case. The journal focuses on Software quality but the discussions also offer insight into other areas such as Risk analysis (engineering), Software peer review and Quality management. Software development research presented in the journal encompasses a variety of subjects, including Knowledge management and Process management.
It focused on Quality (business) research but expanded to cover Process (engineering). The work on Software quality control tackled in Software Quality Journal brings together disciplines like Software quality management and Software quality analyst. Team software process, Software Engineering Process Group and Social software engineering are some topics wherein Personal software process research discussed in Software Quality Journal have an impact.
The most cited papers mainly deal with areas of study such as Software quality, Software engineering, Software, Data mining and Software development. While the primary focus in the most cited papers is Software engineering, they also dissect topics surrounding Personal software process and Team software process, Software Engineering Process Group, Social software engineering, Process management and Knowledge management as a whole. While the published articles focused on Software, they were also able to explore topics like Quality (business), Feature (machine learning), Software deployment and Process (engineering).
The journal mainly tackles studies in Software, Quality (business), Machine learning, Artificial intelligence and Process (engineering). The majority of Software studies presented zero in on Software metric. The journal explores topics in Quality (business) which can be helpful for research in disciplines like Test (assessment), Software testing, Complement (set theory), Software engineering and Software quality.
In it, Construct (python library), Software system and Resource (project management) are investigated in conjunction with one another to address concerns in Machine learning research. Some problems in Process (engineering) that were presented in the journal overlapped with concepts under Software development process and Process management. The journal addresses concerns in the field of Maintainability by exploring it in line with topics in Empirical research which intersect with Software development, Reliability engineering and Information quality subjects.
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 Software Quality Journal (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 Software Quality Journal (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, 2.56% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 7.89% were posted by at least one author from the top 10 institutions publishing in the journal. Another 5.26% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 10.53% of all publications and 76.32% 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 we touch on a variety of technical topics both broad and specific, understanding the career progression and requirements in these fields is equally as important. As such, we would be remiss not to highlight the path to becoming educators in these technical fields. To understand this better, let's take an example of a middle school math educator.
If one were interested in becoming a middle school math teacher in Nevada, there are specific requirements and steps to accomplish this career goal. The journey typically involves getting a Bachelor’s degree in Education or a related field, completing a teacher preparation program, passing the required teaching certification exams, and then apply for a teacher's license from the Nevada Department of Education. Continuous professional development is also a must in this career path.
If you ever wondered "how long does it take to become a middle school math teacher in nevada?", head over to the linked article. It provides a comprehensive guide on the time lines, along with complete details about qualifications needed, teacher training programs and licensure processes specific to Nevada.
This example of a career pathway is just one among many in the realm of education, and it’s vital to recognize the dedication, learning, and continuous professional development that educators undertake to foster the next generation of leaders in various industries.
Rudolf Ferenc;Zoltán Tóth;Gergely Ladányi;István Siket
(2020)Marc Oriol;Silverio Martínez-Fernández;Silverio Martínez-Fernández;Woubshet Behutiye;Carles Farré
(2020)Miltiadis G. Siavvas;Dionisis D. Kehagias;Dimitrios Tzovaras;Erol Gelenbe;Erol Gelenbe
(2021)Matheus Torquato;Paulo R. M. Maciel;Marco Vieira
(2020)Javier Mancebo;Coral Calero;Félix García
(2021)Darius Sas;Paris Avgeriou
(2020)J . Jenny Li;Andreas Ulrich;Xiaoying Bai;Antonia Bertolino
(2020)Ruchika Malhotra;Kusum Lata
(2020)Pursuing a Computer Science degree in the USA opens doors to various educational and career opportunities. For students seeking advanced credentials, exploring online doctorate programs offers a flexible way to achieve the highest level of expertise without interrupting their careers.
Many professionals prioritize efficiency, which makes one year graduate programs an attractive choice. These programs accelerate learning and help graduates enter or advance in the workforce quickly.
When selecting a degree or certification, it's important to consider earning potential. Some online programs that pay well provide fast tracks to lucrative tech-related roles, making them ideal for those driven by return on investment.
Looking further ahead, evaluating the best degrees for the future ensures that your education aligns with evolving industry demands and technological advancements. Computer Science remains a top choice due to its relevance and growth potential.
