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When two people have made changes to copies of the same file, diff3 can produce a merged output that contains both sets of changes together with warnings about conflicts. diff3 can merge three or more sets of changes to a file by merging two change sets at a time. diff3 can incorporate changes from two modified versions into a common preceding ...
Most often, it is necessary when a file is modified on two independent branches and subsequently merged. The result is a single collection of files that contains both sets of changes. In some cases, the merge can be performed automatically, because there is sufficient history information to reconstruct the changes, and the changes do not ...
Show in-line changes Directory comparison Binary comparison Moved lines 3-way comparison Merge Structured comparison [b] Manual compare alignment Image compare Beyond Compare: Yes Yes Yes Yes Yes (Files and Folders) Yes (Pro only) Yes Yes Compare++: Yes Yes Yes Yes Yes (C/C++,C#,Java,Javascript,CSS3) diff: No Yes partly No No No diff3: No No
If you use tables for two-dimensional graphics you might discover a "feature" in HTML that promotes grey hair. It can affect both rows and columns, depending on the use of either rowspan or colspan. In this 7-row table three cells are assigned a rowspan of 3, but the table totals 6 rows. Where is row 4? There is a row 5-4!
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.
Additionally there is a single-row version, UPDATE OR INSERT INTO tablename (columns) VALUES (values) [MATCHING (columns)], but the latter does not give you the option to take different actions on insert versus update (e.g. setting a new sequence value only for new rows, not for existing ones.)
In the merge sort algorithm, this subroutine is typically used to merge two sub-arrays A[lo..mid], A[mid+1..hi] of a single array A. This can be done by copying the sub-arrays into a temporary array, then applying the merge algorithm above. [1] The allocation of a temporary array can be avoided, but at the expense of speed and programming ease.
The sequential merge sort procedure can be described in two phases, the divide phase and the merge phase. The first consists of many recursive calls that repeatedly perform the same division process until the subsequences are trivially sorted (containing one or no element). An intuitive approach is the parallelization of those recursive calls. [19]