Causal Knowledge Modelling for Agile Development of Enterprise Application Systems
Volume 34, Issue 1 (2023), pp. 121–146
Pub. online: 14 March 2023
Type: Research Article
Open Access
Open Access
Received
1 July 2022
1 July 2022
Accepted
1 February 2023
1 February 2023
Published
14 March 2023
14 March 2023
Abstract
Experience shows that Agile project management tools such as Atlassian Jira capture the state of EAS projects by relying solely on expert judgement that is not supported by any knowledge model. Therefore, the assessment of project content against strategic objectives and business domain features are not supported by any tool. This is one of the reasons why Agile project management still does not provide sufficient EAS project delivery results. In order to address this problem, the Enterprise Application Software (EAS) development using Agile project management is summarized in a conceptual model. The model highlights the knowledge used and indicates its nature (empirical or causal digitized). The modified Agile management process we have developed and described in previous works is based on causal knowledge models that supports EAS development and Agile management processes. The purpose of this article is to specify knowledge repository to ensure the Agile management solutions of an EAS project are aligned with strategic goals and business domain causality. It is worth noticing that strategic goals have been identified and specified as capabilities using some enterprise architecture framework (NAF, MODAF, ArchiMate, etc.). The novelty of the proposed method is incorporating the business domain causal knowledge modelling approach into the Agile project management process. The causal knowledge unit is considered as a Management Transaction (MT), which includes closed loop dependence of its components. The modified Agile activity hierarchy (theme, initiative, epic, user story) defines the required content of their mutual interactions. An important new results obtained are the conceptual model of causal knowledge base (KB) and specification of enhanced Agile management tool components: project management database and project state assesment knowledge base. Causal KB includes specification of causal knowledge unit (MT metamodel) and specifications of traditional and causal Agile hierarchy meta-models. These conceptual models define the causal knowledge components necessary to evaluate the state of Agile activities in the EAS development project using intelligent Agile project management tool.
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Biographies
Noreika Karolis
K. Noreika obtained master’s degree in 2015 from Vilnius University. He is a PhD student at Vilnius University Institute of Data Science and Digital Technologies. His research interests include Agile software development management, business and IT alignment methods. K. Noreika has published an article in the cited journal (indexed by the Web of Science database) and also papers in peer-reviewed conference proceedings (indexed by Scopus). He is a member of the Lithuanian Computer Society. Karolis has over 14 years of experience in Agile software development management working as project manager, business analyst, and Agile consultant in national and international companies.
Gudas Saulius
S. Gudas is a head of the Cyber-Social Systems Engineering Department, professor at the Faculty of Mathematics and Informatics of Vilnius University. He received a doctoral degree in technical sciences (PhD) in 1982. In 2005 he completed the habilitation procedure in informatics engineering at Kaunas University of Technology. He was conferred the title of professor at the Kaunas University of Technology (2005), and at Vilnius University (2005). He is the author of the monograph Foundations of the Information Systems Engineering Theory, 2 book chapters, 5 textbooks, and more than 180 scientific papers. The field of research interests focuses on enterprise software engineering, causal modelling approach, knowledge-based CASE methods. He is a supervisor of eight PhD theses. Member of Lithuanian Computer Society. Scientific internship: Warsaw Technical University, Poland, 2018; Riga Technical University, Latvia, 2016; Tartu University, Estonia, 2015; Brandenburg University of Technology (Germany, Cottbus-Senftenberg), 2013, London City University, 1996; Stockholm University, 1995.
