Shared and mutable data-structures pose major problems in static analysis and most analyzers are unable to keep track of the values of numeric variables stored in the heap. In this paper, we first identify sufficient conditions under which heap allocated numeric variables in object oriented programs (i.e., numeric fields) can be handled as nonheap allocated variables. Then, we present a static ...

Currently, all search algorithms which use discretization of numeric attributes for numeric association rule mining, work in the way that the original distribution of the numeric attributes will be lost. This issue leads to loss of information, so that the association rules which are generated through this process are not precise and accurate. Based on this fact, algorithms which can natively h...

Planning with numeric state variables has been a challenge for many years, and was a part of the 3rd International Planning Competition (IPC-3). Currently one of the most popular and successful algorithmic techniques in STRIPS planning is to guide search by a heuristic function, where the heuristic is based on relaxing the planning task by ignoring the delete lists of the available actions. We ...

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We have developed a method for answering single answer questions automatically using a collection of documents or the Internet as a source of data for the production of the answer. Examples of such questions are ‘What is the melting point of tin?’, and ‘Who wrote the novel Moby Dick?’. The approach we have adopted to the problem uses the Mikrokosmos ontology to represent knowledge about questio...

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A number of questions regarding programs involving heap-based data structures can be phrased as questions about numeric properties of those structures. A data structure traversal might terminate if the length of some path is eventually zero or a function to remove n elements from a collection may only be safe if the collection has size at least n. In this thesis, we develop proof methods for re...

Modern embedding methods focus only on the words in the text. The word or sentence embeddings are trained to represent the semantic meaning of the raw texts. However, many quantified attributes associated with the text, such as numeric attributes associated with Yelp review text, are ignored in the vector representation learning process. Those quantified numeric attributes can provide important...

Numeric abstract domains are key to many verification problems. Their ability to scale hinges on using convex approximations of the possible variable valuations. In certain cases, this approximation is too coarse to verify certain verification conditions, namely those that require disjunctive invariants. A common approach to infer disjunctive invariants is to track a set of states. However, thi...