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 The Decision Model and Notation (DMN) is an OMG standard for the representation of company decision logic. This tool can be used for the decision logic level verification of DMN tables. In this context, Smit et al. (2017) have recently proposed the so-called business rule management (BRM) capability framework. This framework identifies specific decision logic level verification capabilities, derived from qualitative re-search with industrial partners. Thus, the framework presented by those authors presents a comprehensive set of verification capabilities actually needed in practice. These capabilities are as follows:
 
 *  **Identical rule verification.** Detecting rules which have an identical input,i.e. are redundant. Our tool can find identical rules within a single table, oridentical rules distributed across multiple tables.–  
-*  **Equivalent rule verification.**Detecting rules which are not identical, butstill semantically equivalent. Here, our tool can verify if there exist multiplerules which use synonyms as inputs and are therefore equivalent, based onsynonym relations via Wordnet. TODO–  
+*  **Equivalent rule verification.** Detecting rules which are not identical, butstill semantically equivalent. Here, our tool can verify if there exist multiplerules which use synonyms as inputs and are therefore equivalent, based onsynonym relations via Wordnet. TODO–  
 *  **Subsumed  rule  verification.** Detecting  individual  rules  which  are  sub-sumed by other rules, i.e. they are not necessary. For example, rules contain-ing wildcards often render more specific rules unnessessary due to subsump-tion.–  
-*  **Interdeterminism verification.**Detecting rules which willalwaysbe acti-vated together, but have differing or contradicting conclusions. For example,rules must not yield that a customer is both credit worthy, and not creditworthy, as this is logically inconsistent,–  
-*  **Partial reduction verification.Checking wether ranges can be combinedto simplify decision tables. For example, TODO.–  
-*  **Overlapping  condition  verification.**Detecting  whether  there  are  anyoverlaps in rule conditions. TODO disambiguation
+*  **Interdeterminism verification.** Detecting rules which willalwaysbe acti-vated together, but have differing or contradicting conclusions. For example,rules must not yield that a customer is both credit worthy, and not creditworthy, as this is logically inconsistent,–  
+*  **Partial reduction verification.** Checking wether ranges can be combinedto simplify decision tables. For example, TODO.–  
+*  **Overlapping  condition  verification.** Detecting  whether  there  are  anyoverlaps in rule conditions. TODO disambiguation
 4C. Corea et al.–  
-*  **Missing rule verification.**Detecting whether there are any missing busi-ness rules.
+*  **Missing rule verification.**Detecting whether there are any missing busi-ness rules.
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+Our tool implements the verification capabilities proposed by Smit et al. (2017). Please note that we did not implement "unnessesary fact verification" as this is geared towards analyzing case-dependent facts and is beyond the scope of this project. In the following, we present examples for the individual verification capabilities.
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