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The differences between the programming languages C++ and Java can be traced to their heritage, as they have different design goals. C++ was designed for systems and applications programming (i.e., infrastructure programming), extending the procedural programming language C, which was designed for efficient execution.
Displaying the differences between two or more sets of data, file comparison tools can make computing simpler, and more efficient by focusing on new data and ignoring what did not change. Generically known as a diff [ 1 ] after the Unix diff utility , there are a range of ways to compare data sources and display the results.
The difference is an exact number of quarters of an hour up to 95 (same minutes modulo 15 and seconds) if the file was transported across zones; there is also a one-hour difference within a single zone caused by the transition between standard time and daylight saving time (DST). Some, but not all, file comparison and synchronisation software ...
tkdiff uses colors to suggest differences between files and within shared lines. tkdiff is a graphical diff viewer based on the Tk framework. [1] It is capable of inter-operating with source-control systems like CVS and Subversion to show the differences between the local copy and the repository version.
In computing, the utility diff is a data comparison tool that computes and displays the differences between the contents of files. Unlike edit distance notions used for other purposes, diff is line-oriented rather than character-oriented, but it is like Levenshtein distance in that it tries to determine the smallest set of deletions and insertions to create one file from the other.
Meld is a visual diff and merge tool, targeted at developers. It allows users to compare two or three files or directories visually, color-coding the different lines. Meld can be used for comparing files, directories, and version controlled repositories.
The literature on programming languages contains an abundance of informal claims about their relative expressive power, but there is no framework for formalizing such statements nor for deriving interesting consequences. [52] This table provides two measures of expressiveness from two different sources.
Main concerns for data differencing are usability and space efficiency (patch size).. If one simply wishes to reconstruct the target given the source and patch, one may simply include the entire target in the patch and "apply" the patch by discarding the source and outputting the target that has been included in the patch; similarly, if the source and target have the same size one may create a ...