Finding Trends in Software Research

Mathew, George; Agrawal, Amritanshu

doi:10.1109/tse.2018.2870388

Cited by 27 publications

(34 citation statements)

References 53 publications

(66 reference statements)

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“…Several studies have used bibliometrics data to reflect on various aspects of software engineering (SE) research. Mathew et al (2019) used topic modeling and bibliometric data (author names, venues, and citations) to identify ten major topics in SE research. Their study showed the changes in the major topics over the years as well.…”

Section: Related Workmentioning

confidence: 99%

An analysis of top author citations in software engineering and a comparison with other fields

Petersen

Ali

2021

Scientometrics

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Ioannidis et al. provided a science-wide database of author citations. The data offers an opportunity to researchers in a field to compare the citation behavior of their field with others. In this paper, we conduct a systematic analysis of citations describing the situation in software engineering and compare it with the fields included in the data provided by Ioannidis et al. For comparison, we take the measures used by Ioannidis into consideration. We also report the top-scientists and investigate software engineering researchers’ activities in other fields. The data was obtained and provided by Ioannidis et al. based on the Scopus database. Our method for analysis focuses on descriptive statistics. We compared software engineering with other fields and reported demographic information for the top authors. The analysis was done without any modifications to the ranking. In the later analysis, we observed that 37% of researchers listed as software engineers were not in the software engineering field. On the other hand, the database included a large portion of top authors (ca. 60% to 80%) identified in other software engineering rankings. Other fields using the database are advised to review the author lists for their fields. Our research’s main risk was that researchers are listed that do not belong to our studied field.

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Section: Related Workmentioning

confidence: 99%

An analysis of top author citations in software engineering and a comparison with other fields

Petersen

Ali

2021

Scientometrics

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“…MacDonell et al [9] consider it as a useful and a common research instrument tool. Study of Mathew et al [10] emphasizes that using text mining in systemic review, large scale trends in empirical research in contemporary software engineering can be detected. In terms of bibliographic search, also a step in our study, the importance of specifying the bibliographic search conducted for a systematic review is considered important [11], whereas the need for "a comprehensive bibliometric assessment" for a better understanding of the vast and dynamic literature is argued [1].…”

Section: Introductionmentioning

confidence: 99%

Deneysel Yazılım Mühendisliğindeki Araştırma Eğilimleri için Metin Madenciliği

Tokdemir

2021

Politeknik Dergisi

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This paper aims to examine the research trends in Empirical Software Engineering domain by applying topic modelling. Figure. Topic Modeling for research trends in Empirical Software Engineering AimThis paper intends to investigate and analzye the research trends in Empirical Software Engineering domain within the last two decades using text mining. Design & MethodologyThe abstracts of 10658 articles published in the literature were analyzed using topic modeling, and the research topics in this field were investigated and analyzed comparatively. OriginalityThis study is the first in applying the topic modeling technique in Emprical Software Engineering literature. FindingsThe analysis for the last 20-year period have shown that; Organization, Software Development Process and Human topics got the most attention from researchers and the fastest growing research topics are Performance, Coding, Testing and Software Practice. ConclusionIt can be expected that the Empirical Software Engineering research will gain more interest from the research community as software industry needs for more evidence on the practical applications of the theory.

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“…As discussed below, when compared to other community monitoring methods (e.g. artifact tracks or bibliometric searches [3,10]), these reuse graphs are less effort to build and verify. For example, it took around 12 minutes per paper for our team from Hong Kong, Canada, the United States, Italy, Sweden, Finland, and Australia to apply this reuse graph methodology to software engineering 1 .…”

Section: Introductionmentioning

confidence: 99%

“…Such studies can lag significantly behind current work. For example, our citation analysis of SE [10] only went up to 2016, the study itself was conducted in 2017, but not fully published till 2018. Given the enormous effort required for that work, we have vowed never to do it again.…”

Section: Introductionmentioning

confidence: 99%

“…That would be a significant achievement, if we could document it (but using Google Scholar, we cannot). EXAMPLE #2: In our recent large scale text-mining studies of 30,000+ SE papers [10] , it was found that papers can appear in our citation server, but not in others. Also, examples were found where some papers had twenty times the citations in one server than in another.…”

Section: Introductionmentioning

confidence: 99%

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Crowdsourcing the State of the Art(ifacts)

Baldassarre,

Ernst,

Hermann

et al. 2021

Preprint

Self Cite

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In any field, finding the "leading edge" of research is an on-going challenge. Researchers cannot appease reviewers and educators cannot teach to the leading edge of their field if no one agrees on what is the state-of-the-art.Using a novel crowdsourced "reuse graph" approach, we propose here a new method to learn this state-of-the-art. Our reuse graphs are less effort to build and verify than other community monitoring methods (e.g. artifact tracks or citation-based searches). Based on a study of 170 papers from software engineering (SE) conferences in 2020, we have found over 1,600 instances of reuse; i.e., reuse is rampant in SE research. Prior pessimism about a lack of reuse in SE research may have been a result of using the wrong methods to measure the wrong things.

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Finding Trends in Software Research

Cited by 27 publications

References 53 publications

An analysis of top author citations in software engineering and a comparison with other fields

An analysis of top author citations in software engineering and a comparison with other fields

Deneysel Yazılım Mühendisliğindeki Araştırma Eğilimleri için Metin Madenciliği

Crowdsourcing the State of the Art(ifacts)

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