Dietmar Seipel

Martin Atzmueller, Cicek Güven, Dietmar Seipel

The explication and the generation of explanations are prominent topics in artificial intelligence and data science, in order to make methods and systems more transparent and understandable for humans. This paper investigates the problem of link analysis, specifically link prediction and anomalous link discovery in social networks using the declarative method of Answer set programming (ASP). Applying ASP for link prediction provides a powerful declarative approach, e.g., for incorporating domain knowledge for explicative prediction. In this context, we propose a novel method for generating explanations - as offline justifications - using declarative program transformations. The method itself is purely based on syntactic transformations of declarative programs, e.g., in an ASP formalism, using rule instrumentation. We demonstrate the efficacy of the proposed approach, exemplifying it in an application on link analysis in social networks, also including domain knowledge.

Frank Flederer, Ludwig Ostermayer, Dietmar Seipel et al.

System relevant embedded software needs to be reliable and, therefore, well tested, especially for aerospace systems. A common technique to verify programs is the analysis of their abstract syntax tree (AST). Tree structures can be elegantly analyzed with the logic programming language Prolog. Moreover, Prolog offers further advantages for a thorough analysis: On the one hand, it natively provides versatile options to efficiently process tree or graph data structures. On the other hand, Prolog's non-determinism and backtracking eases tests of different variations of the program flow without big effort. A rule-based approach with Prolog allows to characterize the verification goals in a concise and declarative way. In this paper, we describe our approach to verify the source code of a flash file system with the help of Prolog. The flash file system is written in C++ and has been developed particularly for the use in satellites. We transform a given abstract syntax tree of C++ source code into Prolog facts and derive the call graph and the execution sequence (tree), which then are further tested against verification goals. The different program flow branching due to control structures is derived by backtracking as subtrees of the full execution sequence. Finally, these subtrees are verified in Prolog. We illustrate our approach with a case study, where we search for incorrect applications of semaphores in embedded software using the real-time operating system RODOS. We rely on computation tree logic (CTL) and have designed an embedded domain specific language (DSL) in Prolog to express the verification goals.

Dietmar Seipel

Modern knowledge base systems frequently need to combine a collection of databases in different formats: e.g., relational databases, XML databases, rule bases, ontologies, etc. In the deductive database system DDBASE, we can manage these different formats of knowledge and reason about them. Even the file systems on different computers can be part of the knowledge base. Often, it is necessary to handle different versions of a knowledge base. E.g., we might want to find out common parts or differences of two versions of a relational database. We will examine the use of abstractions of rule bases by predicate dependency and rule predicate graphs. Also the proof trees of derived atoms can help to compare different versions of a rule base. Moreover, it might be possible to have derivations joining rules with other formalisms of knowledge representation. Ontologies have shown their benefits in many applications of intelligent systems, and there have been many proposals for rule languages compatible with the semantic web stack, e.g., SWRL, the semantic web rule language. Recently, ontologies are used in hybrid systems for specifying the provenance of the different components.