At this year’s PoEM, Simon and Dominik will present the work of their student Robin, who developed an extension to the CM2KG to be able to store historical data and the differences between the single states of the model. This will allow a first step into the direction to analyze EA Smells that consider changes …
June 3, 2022 is the date on which we were able to go back to in presence presentations again. After almost 2.5 years and the presentation of the concept of EA Smells at the WI 2020 in Potsdam, Simon and Dominik presented their work on automatizing the detection of EA Smells in EA models. Besides …
Simon had the honor to present the joint work with Muhammad and Dominik on identifying EA Smells in knowledge graphs at the PoEM conference. In their work, they transformed EA models to knowledge graphs and defined cypher queries for 14 EA Smells to automate their detection. To validate their approach, they analyzed 347 ArchiMate models …
Two papers have been accepted for publication that are related to EA Debts research. The first paper presents a workshop approach to identify EA Debts and their symptoms (i.e., EA Smells) in organization and illustrates it on two case studies. The work will be presented at the SoEA4EE workshop hosted at the EDOC conference. The …
Background Technical Debt (TD) is a well-established concept in software development and means that a solution that is “quick and dirty” is applied in order to earn time in short term and be able to provide a function in a system more quickly. This primitive implementation will at a later stage need to be corrected …
Background In the software development industry, technical debt is regarded as a critical issue in terms of the negative consequences such as increased software development cost, low product quality, decreased maintainability, and slowed progress to the long-term success of developing software. Technical debt describes the delayed technical development activities for getting short-term payoffs such as …