General
The formal-deductive analysis is a logical-analytical procedure in which specific statements or individual insights are derived from formally specified models (e.g., mathematical or logical-symbolic models). The focus is on the application of formal rules of logic to clearly defined premises so that conclusions are traceable and free of contradictions, independent of individual interpretations [1].
Purpose
The purpose of formal-deductive analysis is to derive logically compelling conclusions for concrete problems or research questions from a given formal model. In this way, properties of models can be examined, hypotheses about system behaviour can be derived, and the consequences of certain assumptions can be investigated in a systematic manner [1].
Procedure
The starting point is a formally specified model that describes the relevant elements, relations, and boundary conditions of the object of investigation in a formal language (e.g., using equations, logical formulas, or other formally defined symbol systems). Based on this model, new statements are derived by means of established rules of logical inference, which refer to specific questions and are interpreted in view of the underlying problem. In doing so, consistency, completeness, or particular implications of the model can be analysed and used for the respective research or application context [1].
Example
A simple example is a formally specified authorization system for an information system, in which the premises state that “only users with the role administrator may delete records” and that “user A has the role administrator”. From these formal premises, one can deductively derive the concrete statement that user A is allowed to delete records in the system. If further rules are added (e.g., restrictions to certain data domains), the same formal model can be used to systematically derive additional logically consistent statements about the authorization behaviour [1].
Core literature
- [1] Wilde, T., & Hess, T. (2006). Methodenspektrum der Wirtschaftsinformatik: Überblick und Portfoliobildung (Working Paper No. 2/2006). Institut für Wirtschaftsinformatik und Neue Medien, Ludwig-Maximilians-Universität München.