Abstract: A real-time system receives a selection structure formed by weighted rules joined by links, each of the weighted rules including a condition part, a conclusion part and a weight. The selection structure is an Algebraic Decision Diagram (ADD) that includes internal nodes, each representing a decision point and terminal nodes, each representing a subset of candidate results having an accumulated weight. In response to a query that specifies a set of conditions, the ADD is traversed by making a series of decisions at decision points of the ADD to reach at least one terminal node having a maximum accumulated weight among terminal nodes that satisfy the set of conditions. The subset of candidate results represented by the at least one terminal node is selected as the output for responding to the query.

Abstract: A real-time system receives a selection structure formed by weighted rules joined by links, each of the weighted rules including a condition part, a conclusion part and a weight. The selection structure is an Algebraic Decision Diagram (ADD) that includes internal nodes, each representing a decision point and terminal nodes, each representing a subset of candidate results having an accumulated weight. In response to a query that specifies a set of conditions, the ADD is traversed by making a series of decisions at decision points of the ADD to reach at least one terminal node having a maximum accumulated weight among terminal nodes that satisfy the set of conditions. The subset of candidate results represented by the at least one terminal node is selected as the output for responding to the query.

Abstract: Systems, methods and apparatus are provided through which in some embodiments, automata learning algorithms and techniques are implemented to generate a more complete set of scenarios for requirements based programming. More specifically, a CSP-based, syntax-oriented model construction, which requires the support of a theorem prover, is complemented by model extrapolation, via automata learning. This may support the systematic completion of the requirements, the nature of the requirement being partial, which provides focus on the most prominent scenarios. This may generalize requirement skeletons by extrapolation and may indicate by way of automatically generated traces where the requirement specification is too loose and additional information is required.

Abstract: The invention relates to a device for selecting data elements that contains a selection description device for creating a selection description data element, a generator device, which generates a selection structure data element from the selection description data element, and contains a selection device, which makes a selection from the input data elements when an inquiry data element is present. Selection description data elements can be created by non-electronic data processing specialists. The generation of the selection structure data element is of significant importance. Due to its nature, the selection device can be designed with a low level of complexity, can be operated while detached from the other devices, and can rapidly make selections. The invention can be used in many areas of application in the field of information technology, particularly in embedded systems, in the personalization of web pages, in e-commerce systems, and in targeted marketing.

Abstract: Systems, methods and apparatus are provided through which in some embodiments, automata learning algorithms and techniques are implemented to generate a more complete set of scenarios for requirements based programming. More specifically, a CSP-based, syntax-oriented model construction, which requires the support of a theorem prover, is complemented by model extrapolation, via automata learning. This may support the systematic completion of the requirements, the nature of the requirement being partial, which provides focus on the most prominent scenarios. This may generalize requirement skeletons by extrapolation and may indicate by way of automatically generated traces where the requirement specification is too loose and additional information is required.

Abstract: The invention relates to a device for selecting data elements that contains a selection description device for creating a selection description data element, a generator device, which generates a selection structure data element from the selection description data element, and contains a selection device, which makes a selection from the input data elements when an inquiry data element is present. Selection description data elements can be created by non-electronic data processing specialists. The generation of the selection structure data element is of significant importance. Due to its nature, the selection device can be designed with a low level of complexity, can be operated while detached from the other devices, and can rapidly make selections. The invention can be used in many areas of application in the field of information technology, particularly in embedded systems, in the personalization of web pages, in e-commerce systems, and in targeted marketing.