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Article Citation - WoS: 20Citation - Scopus: 25Detecting Latent Topics and Trends in Software Engineering Research Since 1980 Using Probabilistic Topic Modeling(Ieee-inst Electrical Electronics Engineers inc, 2022) Gurcan, Fatih; Dalveren, Gonca Gokce Menekse; Cagiltay, Nergiz Ercil; Soylu, AhmetThe landscape of software engineering research has changed significantly from one year to the next in line with industrial needs and trends. Therefore, today's research literature on software engineering has a rich and multidisciplinary content that includes a large number of studies; however, not many of them demonstrate a holistic view of the field. From this perspective, this study aimed to reveal a holistic view that reflects topics, trends, and trajectories in software engineering research by analyzing the majority of domain-specific articles published over the last 40 years. This study first presents an objective and systematic method for corpus creation through major publication sources in the field. A corpus was then created using this method, which includes 44 domain-specific conferences and journals and 57,174 articles published between 1980 and 2019. Next, this corpus was analyzed using an automated text-mining methodology based on a probabilistic topic-modeling approach. As a result of this analysis, 24 main topics were found. In addition, topical trends in the field were revealed. Finally, three main developmental stages of the field were identified as: the programming age, the software development age, and the software optimization age.Article Citation - WoS: 6Citation - Scopus: 8Automated Recovery and Visualization of Test-To Traceability (tct) Links: an Evaluation(Ieee-inst Electrical Electronics Engineers inc, 2021) Aljawabrah, Nadera; Gergely, Tamas; Misra, Sanjay; Fernandez-Sanz, LuisIn the software development process, traceability links between unit tests and code are not explicitly maintained, and dependencies in most cases are manually identified. As a result, a large amount of effort and time is required during the comprehension process to establish the links between these artifacts. Although there are several methods that can infer such links based on different phenomenons, these methods usually produce different set of traceability links. This work expands upon previous traceability link recovery and visualization studies by implementing a combination of traceability recovery methods that automatically retrieve the links, and visualizing them to help developers to overview the links inferred by various recovery techniques, and also to select the right relations for analyses. The results of the usability study show that the visualization model presented herein can effectively support browsing, comprehension, and maintenance of Test-to Code Traceability (TCT) links in a system with enhanced efficiency, as well as visualization of TCT links from multiple sources is better than a visualization of single source of traceability links.
