Free rush hour puzzle solutions software for linux

Cryptogram Puzzle Tool project helps solve the simple cryptogram puzzles that appear in the daily newspapers. While these puzzles can often be solved almost by inspection, CPT4 provides a handy tool for the ones that turn out to be not quite so easy.
If you just want a little bookkeeping help, CPT4 will instantly update all occurrences of the new assignments as well as provide frequency and used/not-used letter lists as you drag-and-drop or key in suspected solution letters. But if youd rather have the computer do the work, the automatic solution algorithm will usually come very close to a complete solution in just a few seconds.
Bonus: CPT4 can also create new puzzles: simply key in or load plaintext from a file, and select the Encrypt item from the Options menu.
Installing / Building / Running:
Start by unpacking in a directory where you have write permissions; all tar files create and populate a cpt4/ directory and contain sample puzzles as well as various information.
For the source distribution, change to the cpt4 directory and just type make. You may get a few warnings while compiling do_hart.c, but otherwise the executables cpt4 and do_hart should be built after a short time and a few intermediate steps. If this does not happen and you are not knowledgeable about such things, you might try the shared library executable distribution instead.
For the 4.1.x shared library executables, you may need to supply a font alias file in a location that the precompiled Pango routines can find; the easiest way to do this is to just copy the two files .pangorc and pangox.aliases from the installation directory into to your $HOME directory. If you use the source distributions, of course, you will need to have a complete Pango installation before you start.
Once you have the executables, try out the program by changing to the installation directory and issuing the command line:
./cpt4
Use the File->Load menu item to load one of the samples (xxxxx.cpt) and play with the controls. Try the Options->Hart Solution menu item to see the automatic solution in action.
If the puzzle text is uncomfortably small or large on your system, you can specify a different font on the command line like this:
./cpt4 -large
./cpt4 -small
With the 4.0.x and 4.1.x versions (but not the 4.2.x versions) you can also specify a font by name like this:
./cpt4 -font="font-name"
For the 4.0.1 versions (with GTK 1.2), the font MUST be monospaced and is expected to be iso8859-1; other characters sets may also work but might produce a different effect. The font-name for these versions of cpt4 must be an X logical font name such as "*clean-bold-r*--16*".
For the 4.1.x versions (with Pango), monospaced fonts will generally produce more pleasing results, but proportional fonts of sufficiently small size may also work; the main requirement is that the ASCII characters ! through ~ be portrayed as expected. Font-name for these versions must be a Pango font name, such as "courier bold 11", "sans 8", "Times 8", and so forth.
If you want just want to run CPT4 from the command line, it is sufficient to put a soft link to cpt4 from somewhere in your PATH and leave both the cpt4 and do_hart executables in the installation directory. For example, as root:
cd /usr/bin
ln -s /home/johndoe/cpt4/cpt4
A 32x32 CPT4 icon in .xpm format is included in all distributions for use in desktop shortcuts.
Enhancements:
- This release changes fixed width font logic, including special cursor logic using the fixed fonts, to preprocessed fonts supplied as C header files, instead of using Pango routines and arbitrary fonts.
- It has been updated to use glib 2.6.1, Gtk+2.6.1, Pango 1.8.0, atk 1.9.0, and associated packages as supplied in Slackware 10.0. Functionality is virtually unchanged.

Turts Puzzle Blocks multi-platform puzzle game, designed for both Linux and Windows. Turts Puzzle Blocks is also the current project of Turt99 Productions. The goal of the project is to gain experience C++ and Object Oriented Design, as well as to help in the learn process of Linux as a development platform.

Turts Puzzle Blocks has actually gone through many stages; it started its life as "Turts Breakdown". At this point the graphics where being designed so the "blocks" didnt exists. Once the "blocks" where created there was a need for the name to be changed, and a lot of new modes (or mini games) seemed to fall into the design. As of the Beta release you are basically seeing what "Turts Breakdown" was to be, however there are many more plans for Turts Puzzle Blocks.

Turts Puzzle Blocks is created using KDevelop 2.1 under Linux Redhat 9.0, and uses the SDL libraries. SDL was chosen because it is a multi-platform library that would allow the seamless development for 2 operating systems. SDL main library supplies the support for the windows and the display, but Turts Puzzle Blocks also uses two additional SDL libraries SDL_image and SDL_Mixer. SDL_image supports the use for PNG and TGA files, which allows for Alpha blending and results in clean lines and smooth graphics. SDL_mixer is used for playing sounds and the background music.

Einstein puzzle is a free cross-platform open source remake of old DOS game Sherlock which was inspired by Albert Einsteins puzzle.

Einstein said that only those with an intelligence quotient of 98 percentile and higher should be able to solve it.

The game goal is to open all cards in square of 6x6 cards. For this, a number of hints describing relations between card positions are given. Use them to find the correct layout.

Einstein 2.0 features sound support, full internalization, Russian localization, reengineered resource subsystem to allow custom graphics themes and in-game rules browser.

E/AS Automation Solutions is open source software system for help automate your solutions even for personal and/or corporate ones.
E/AS written on CLIP language (CA-Clipper dialect, compiler can be obtained from ITK.ru) and uses CODB (CLIP Object Database) as data storage.
Main features:
- client-server technology (both data and interface forms)
- component infrastructure with interaction between components by messages
- interface forms on XML
- MDI
E/AS contains in typical distribution:
- client software written on clip-ui library
- server software with wrapper for run as daemon
- maintenance tools: CODB console and component manager
- base (form, auth) and example (contact) components
Enhancements:
- completely rewrite code for implement E/AS architecture
- component infrastructure
- own server program instead COBRA
- maintenance tools: CODB console and component manager
- base and example components
- autoupdate views

PolyPuzzle project is a cute game, based on the original puzzle #0.

Poly Puzzle is my first original program to make use of Tks canvas widget. It was inspired by a plastic puzzle named Beat The Computer which came in an array of
sizes and loud colours.

It now has trays with polygons based on hexagons, squares and equilateral triangles. The new round tray is based on smooth triangles, and isnt quite as cute as
the original puzzle #0.

I had planned to incorporate a computer solution feature. This would be handy for the actual plastic game - which you have to put away at the end of the day - but
on the computer there are no little pieces to lose under the carpet ;>. More to the point - it would require quite a bit of programming / math!

Puzzle Maps is a software version of the Montessori Puzzle Maps activity.

Puzzle Maps presents users with a choice of maps in which they can remove and replace the various countries or states that make up the map.

In this way, they familiarize themselves with the geography of the world.

A Sudoku Solver in C is a console-based Linux program, written in C language, that solves Su Doku puzzles using deductive logic. It will only resort to trial-and-error and backtracking approaches upon exhausting its deductive moves.
Puzzles must be of the standard 9x9 variety using the (ASCII) characters 1 through 9 for the puzzle symbols. Puzzles should be submitted as 81 character strings which, when read left-to-right will fill a 9x9 Sudoku grid from left-to-right and top-to-bottom. In the puzzle specification, the characters 1 - 9 represent the puzzle givens or clues. Any other non-blank character represents an unsolved cell.
The puzzle solving algorithm is home grown. I did not borrow any of the usual techniques from the literature, e.g. Donald Knuths "Dancing Links." Instead I rolled my own from scratch as a personal challenge. As such, its performance can only be blamed on yours truly. Still, I feel it is quite fast. On a 333 MHz Pentium II Linux box it solves typical medium force puzzles in approximately 800 microseconds or about 1,200 puzzles per second, give or take. On an Athlon XP 3000 it solves about 6,600 puzzles per sec. (Solving time is dependent upon degree of difficulty, so YMMV.)
Description of Algorithm:
The puzzle algorithm initially assumes every unsolved cell can assume every possible value. It then uses the placement of the givens to refine the choices available to each cell. I call this the markup phase.
After markup completes, the algorithm then looks for singleton cells with values that, due to constraints imposed by the row, column, or 3x3 region, may only assume one possible value. Once these cells are assigned values, the algorithm returns to the markup phase to apply these changes to the remaining candidate solutions. The markup/singleton phases alternate until either no more changes occur, or the puzzle is solved. I call the markup/singleton elimination loop the Simple Solver because in a large percentage of cases it solves the puzzle.
If the simple solver portion of the algorithm doesnt produce a solution, then more advanced deductive rules are applied.
Ive implemented two additional rules as part of the deductive puzzle solver. The first is subset elimination wherein a row/column/region is scanned for X number of cells with X number of matching candidate solutions. If such subsets (or tuples) are found in the row, column, or region, then the candidates values from the subset may be eliminated from all other unsolved cells within the row, column, or region, respectively.
The next deductive rule examines each region looking for candidate values that exclusively align themselves along a single row or column, i.e. a vector. If such candidate values are found, then they may be eliminated from the cells outside of the region that are part of the aligned row or column.
Note that each of the advanced deductive rules calls all preceeding rules, in order, if that advanced rule has effected a change in puzzle markup.
Finally, if no solution is found after iteratively applying all deductive rules, then we begin trial-and-error using recursion for backtracking. A working copy is created from our puzzle, and using this copy the first cell with the smallest number of candidate solutions is chosen. One of the solutions values is assigned to that cell, and the solver algorithm is called using this working copy as its starting point. Eventually, either a solution, or an impasse is reached.
If we reach an impasse, the recursion unwinds and the next trial solution is attempted. If a solution is found (at any point) the values for the solution are added to a list. Again, so long as we are examining all possibilities, the recursion unwinds so that the next trial may be attempted. It is in this manner that we enumerate puzzles with multiple solutions.
Note that it is certainly possible to add to the list of applied deductive rules. The techniques known as "X-Wing" and "Swordfish" come to mind. On the other hand, adding these additional rules will, in all likelihood, slow the solver down by adding to the computational burden while producing very few results. Ive seen the law of diminishing returns even in some of the existing rules, e.g. in subset elimination I only look at two and three valued subsets because taking it any further than that degraded performance.
Enhancements:
- Code optimization has resulted in a 30% increase in speed.