1 Data compression is a topic of much importance and many applications. Methods of data compression have been studied for almost four decades. This thesis has provided an overview of data compression methods of general utility. A framework for evaluation the performance is constructed and applied to these data compression techniques.from the experimental results accomplished in chapter 8, we introduce the following conclusions:• The family of PPM especially PPMD proved to be the best performer based on the amount of compression ratio and the absolute worst when the speed is considered.• The dictionary algorithms especially LZW achieve the best performer based on the speed and the compression ratio is not the best.<br The data compressing system based on BWT is attracting attention for its simplicity; also, the compression ratio achieved is close to the applications of the PPM family. The negative point of using BWT is its speed, but it is better than that of PPM family. The statistical coders proved to be the worst performer based on both compression ratio and speed comparing to the previous techniques. Nevertheless, they open the door to a great revolution in the data compression field as they are considered as the backbone of all advanced techniques Based on the complexity of the algorithm and the required size of memory needed to implement the algorithm, Huffman coding occupies the first rank. PPM family is the worst. BWI is attracting attention for its simple algorithm and medium memory requirement. Finally, the dictionary techniques are simple to some extent but need large memory size.•The modifications that added to LZ77 algorithms, which are referred to as LZARI, and LZHUF improve the amount of compression ratio and decrease the speed.• Using the principle of exclusion improves the amount of compression ratio in PPMC family.• Using unbounded length contexts for PPM which is referred to as PPM* improves the performance of PPMC family.• The effects of the cascading obtained by using MTF and RLE algorithms with BWT algorithm improve the performance. In addition, the modifications that are added to these algorithms provide higher performance.Consequently, it is strongly recommended for users to use PPM family especially PPMD for compressing their files if the compression ratio is the main object, regardless the time. In addition, it is better to use the dictionary techniques especially LZW if the time is the main object. If they want to achieve the balance of both the compression ratio and speed, BWT system fulfils this requirement.8.2 Suggestions for Future WorkIn this section, we will introduce further enhancement to be added to the proposed work.• As indicated in the previous chapter, extending the present work to include non-textual data such as graphics, digitally sampled sound/speech and movies would benefit those individuals whose compression needs go beyond simple text. Given the graphical output from many programs, this need is probably going to increase. Therefore, a thesis that demonstrates the usefulness of these algorithms in the non-textual realm would be very useful.• Another thesis to consider in this area would be the development of a new compression technique. As has been done in the past, this new compression technique would most likely be a modification to an existing algorithm. Given the performance of the present–day algorithms, however, a new algorithm that tweaks an existing algorithm could expect a modest performance increase at best. The development of a totally new compression algorithm would also be a major undertaking for a thesis topic.• Another extension to the thesis is to exploit the neural network in developing efficient data compression techniques for textual and non-textual files.• Finally, an obvious extension to this thesis would be to implement a larger body of algorithms and to take algorithms in larger combinations. Another extension using the present body as a starting point would be to implement some of the optimizations presented in the different works.