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Pact model ========== The model project is responsible for providing: * a model to represent pacts * serialization and deserialization * comparison between two parts of the pact model * conversion between the pact model and whatever third party libraries used by the pact-consumer and pact-provider requires You should never need to include this project directly

Pact model ========== The model project is responsible for providing: * a model to represent pacts * serialization and deserialization * comparison between two parts of the pact model * conversion between the pact model and whatever third party libraries used by the pact-consumer and pact-provider requires You should never need to include this project directly

${project.name} provides several Ant tasks for dealing with GNU Gettext catalog files and Java Properties files, including file conversion and comparison, and also extracting translatable strings from source code using regular expressions.

Swiftly add ocr layers to scanned pdf files. Unfortunately existing open source ocr solutions (tesseract) pale in comparison with the ones commercially available. The azure read api provides particularly good results. It is also easy to set up, but while it can annotate text in images, there is no easy way to upload and ocr a full pdf document. That is, until now. aocr provides an easy way to ocr full pdf documents.

Modelant provides JMI-compliant mechanism to read, process, export models in MOF 1.4, UML 1.3 and UML 1.4, including also an engine for generation of code (any texts) using Object-Oriented Programming and templates. It is an extensible framework allowing adding support of other languages, described using MOF 1.4 metamodels. Modelant provides Maven plugins to automate the creation and comparison of UML 1.3, UML 1.4, MOF 1.4 models; the generation of code from models; the reverse engineering of java code, relational databases and XML DTD/XSD; the transformatoion of models, e.g. tranformation of of UMl 1.3 models to UML 1.4; the comparison and change identification in UML 1.3/UML 1.4 models and MOF 1.4 metamodels. The produced UML 1.3 models are suitable to be imported in Rational Rose 2003 + XMI Plugin, WhiteStar UML / Star UML, Enterprise Architect, other, as they employ MOF 1.3/MOF 1.4 as reading MOF 1.3 is internally converted to MOF1.4 and XMI 1.1 and XMI 1.2. whereas the converted to UML 1.4 models can be imported in Argo UML, Enterprise Architect, other as they employ MOF 1.4 and XMI 1.1 and XMI 1.2. Modelant wraps the NetBeans Meta-Data Repository (MDR).

Sirix is a versioned, treebased storage system. It provides an ID-less diff-algorithm to import differences between two versions. Furthermore an ID-based diff-algorithm facilitates the comparison of versions stored within Sirix. A GUI with several visualizations for comparing these versions visually is available to aid an analyst. Versions are stored using well known versioning strategies (full, incremental, differential). The architecture is especially well suited for flash-disks because of a COW-principle. In the future we aim to provide throughout security as well as a replaced page-structure to speedup our architecture. A brackit(.org) binding will enable XQuery and the XQuery Update Facility. Temporal XPath axis and possibly diff-functions will help analysts to gain quick knowledge from the stored data.

Sirix is a versioned, treebased storage system. It provides an ID-less diff-algorithm to import differences between two versions (currently XML-documents). Furthermore an ID-based diff-algorithm facilitates the comparison of versions stored within Sirix. A GUI with several visualizations for comparing these versions visually is available to aid an analyst. Versions are stored using well known versioning strategies (full, incremental, differential). The architecture is especially well suited for flash-disks because of a COW-principle. In the future we aim to provide throughout security as well as a replaced page-structure to speedup our architecture. A brackit(.org) binding will enable XQuery and the XQuery Update Facility. Temporal XPath axis and possibly diff-functions will help analysts to gain quick knowledge from the stored data.

This module contains a more general approach to construct AlignmentAlgorithms by relying on the theoretical concept of Algebraic Dynamic Programming (ADP) as developed by Giegerich et al. ADP defines four ingredients for an alignment algorithm: 1.) A signature that defines the permitted alignment operations. Operations are just function templates with an associated arity, meaning the number of arguments it takes from the left sequence and from the right sequence. In the TCSAlignmentToolbox we have a fixed signature with the following operations: REPLACEMENT(1, 1), DELETION(1, 0), INSERTION(0, 1), SKIPDELETION(1, 0) and SKIPINSERTION(0, 1) 2.) A regular tree grammar that produces alignments, that is: sequences of operations, in a restricted fashion. 3.) An algebra that can translate such trees to a cost. In the TCSAlignmentToolbox this is a Comparator. 4.) A choice function, in case of the TCSAlignmentToolbox: the strict minimum or the soft minimum. An alignment algorithm in the TCSAlignmentToolbox sense of the word then is the combination of choice function and grammar. While we provide hardcoded versions of these combinations in the main package, the adp package allows you to create your own grammars. You can combine them with a choice function by instantiating one of the Algorithm classes provided in this package with a grammar of your choice. For example: AlignmentAlgorithm algo = new SoftADPScoreAlgorithm(my_grammar, comparator); creates an alignment algorithm that implicitly produces all possible alignments your grammar can construct with the given input, translates them to a cost using the algebra/comparator you provided and applies the soft minimum to return the score. This all gets efficient by dynamic programming. Note that there is runtime overhead when using this method in comparison with the hardcoded algorithms. But for complicated grammars this is a much easier way to go. For more information on the theory, please refer to my master's thesis: "Adaptive Affine Sequence Alignment using Algebraic Dynamic Programming"