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Beyond the mere additional complexity introduced by adding additional logic and arithmetic to a program, an obfuscating transformation must be resilient (meaning that it cannot be easily undone). Because many of these transformations add irrelevant instructions that don t really produce valuable data, it is possible to create deobfuscators. A deobfuscator is a program that implements various data-flow analysis algorithms on an obfuscated program which sometimes enable it to separate the wheat from the chaff and automatically remove all irrelevant instructions and restore the code s original structure. Creating resilient obfuscation transformations that are resistant to deobfuscation is a major challenge and is the primary goal of many obfuscators. Finally, an obfuscating transformation will typically have an associated cost. This can be in the form of larger code, slower execution times, or increased memory runtime consumption. It is important to realize that some transformations do not incur any kind of runtime costs, because they involve a simple reorganization of the program that is transparent to the machine, but makes the program less human-readable. In the following sections, I will be going over the common obfuscating transformations. Most of these transformations were meant to be applied programmatically by running an obfuscator on an existing program, either at the source code or the binary level. Still, many of these transformations can be applied manually, while the program is being written or afterward, before it is shipped to end users. Automatic obfuscation is obviously far more effective because it can obfuscate the entire program and not just small parts of it. Additionally, automatic obfuscation is typically performed after the program is compiled, which means that the original source code is not made any less readable (as is the case when obfuscation is performed manually).

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Control flow transformations are transformations that alter the order and flow of a program in a way that reduces its human readability. In Manufacturing Cheap, Resilient, and Stealthy Opaque Constructs by Christian Collberg, Clark Thomborson, and Douglas Low [Collberg1], control flow transformations are categorized as computation transformations, aggregation transformations, and ordering transformations. Computation transformations are aimed at reducing the readability of the code by modifying the program s original control flow structure in ways that make for a functionally equivalent program that is far more difficult to translate back into a high-level language. This is can be done either by removing control flow information from the program or by adding new control flow statements that complicate the program and cannot be easily translated into a high-level language. Aggregation transformations destroy the high-level structure of the program by breaking the high-level abstractions created by the programmer while the program was being written. The basic idea is to break such abstractions so that the high-level organization of the code becomes senseless. Ordering transformations are somewhat less powerful transformations that randomize (as much as possible) the order of operations in a program so that its readability is reduced.

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Apr 22, 2018 · Decode EAN-128 with ByteScout Barcode Reader SDK https://bytescout.com/​articles ...Duration: 0:58 Posted: Apr 22, 2018

Good rigging is essential: measure spar stiffness (shown here by weighing) and control line lengths.

The geotechnical community in the United States has not yet adopted LRFD, although it is now part of practice in Europe and Canada. Federal agencies such as the Federal Highway Administration have introduced it into the practice of highway abutment foundation and retaining wall design in order to achieve consistency between structural and geotechnical practice. The technique is equally applicable to other areas of geotechnical engineering, such as slope stability evaluation, and Taylor s (1948) book shows that much of the basic intellectual framework for partial safety factors in geotechnical engineering has existed for a long time. There are several reasons that the profession has been slow to adopt LRFD, including reluctance to change current and generally successful methods of analysis and design, poor understanding of the LRFD methodology and underlying analysis, and inadequate calibration against actual data. The authors expect that current research and training programs will address these problems. In the mean time, LRFD remains one of the most powerful methods for implementing probabilistic methods into design practice. It was developed for situations involving repeated design, such as estimation of pile capacity or design of conventional retaining walls. It is not applicable for special projects in which a full reliability analysis is called for; 22 gives such an example.

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ilopez/GS1Parser: A GS1 Parser for C - GitHub
Jun 9, 2015 · A GS1 Parser for C#. Contribute to ... http://stackoverflow.com/questions/9721718​/ean128-or-gs1-128-decode-c-sharp/28854802#28854802.

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