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Survey of code-size reduction methods
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Source ACM Computing Surveys (CSUR) archive
Volume 35 ,  Issue 3  (September 2003) table of contents
Pages: 223 - 267  
Year of Publication: 2003
ISSN:0360-0300
Authors
Árpád Beszédes  University of Szeged, Szeged, Hungary
Rudolf Ferenc  University of Szeged, Szeged, Hungary
Tibor Gyimóthy  University of Szeged, Szeged, Hungary
André Dolenc  Nokia Mobile Phones, Finland
Konsta Karsisto  Nokia Mobile Phones, Finland
Publisher
ACM  New York, NY, USA
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ABSTRACT

Program code compression is an emerging research activity that is having an impact in several production areas such as networking and embedded systems. This is because the reduced-sized code can have a positive impact on network traffic and embedded system costs such as memory requirements and power consumption. Although code-size reduction is a relatively new research area, numerous publications already exist on it. The methods published usually have different motivations and a variety of application contexts. They may use different principles and their publications often use diverse notations. To our knowledge, there are no publications that present a good overview of this broad range of methods and give a useful assessment. This article surveys twelve methods and several related works appearing in some 50 papers published up to now. We provide extensive assessment criteria for evaluating the methods and offer a basis for comparison. We conclude that it is fairly hard to make any fair comparisons of the methods or draw conclusions about their applicability.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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Araújo, G., Centoducatte, P., Azevedo, R., and Pannain, R. 2000a. Expression tree based algorithms for code compression on embedded RISC architectures. Tech. Rep. IC-00-01, Instituto de Computação---UNICAMP. Jan.
 
3
 
4
 
5
 
6
 
7
8
9
 
10
Bird, P. L. and Mudge, T. N. 1996. An instruction stream compression technique. Tech. Rep. CSE-TR-319-96, EECS Department, University of Michigan. Nov.
 
11
 
12
 
13
Chen, I.-C. K., Bird, P. L., and Mudge, T. N. 1997. The impact of instruction compression on I-cache performance. Tech. Rep. CSE-TR-330-97, EECS Department, University of Michigan.
14
15
16
 
17
Franz, M. 1994. Code-generation on-the-fly: A key to portable software. Ph.D. dissertation, ETH Zürich.
 
18
19
20
21
 
22
Fraser, C. W. and Proebsting, T. A. 1995. Custom instruction sets for code compression. Unpublished manuscript. http://research. microsoft.com/˜toddpro/papers/pldi2.ps.
 
23
 
24
 
25
 
26
Howard, P. G. and Vitter, J. S. 1992. Practical implementations of arithmetic coding. Image Text Compres., 85--112.
 
27
Huffman, D. A. 1952. A method for the construction of minimum redundancy codes. Proc. IERE 40, 1098--1101.
 
28
IBM. 1998. CodePack: PowerPC Code Compression Utility User's Manual Version 3.0. International Business Machines (IBM) Corporation.
 
29
 
30
 
31
 
32
 
33
 
34
Lefurgy, C. R. and Mudge, T. N. 1998. Code compression for DSP. Technical Report CSE-TR-380-98, EECS Department, University of Michigan. Nov.
 
35
 
36
Lefurgy, C. R., Piccininni, E., and Mudge, T. N. 2000. Reducing code size with run-time decompression. In Proceedings of the 6th International Symposium on High-Performance Computer Architecture (HPCA).
 
37
38
39
40
 
41
 
42
Lekatsas, H. and Wolf, W. 1999b. SAMC: A code compression algorithm for embedded processors. IEEE Trans. CAD 18, 12 (Dec.), 1689--1701.
 
43
Lempel, A. and Ziv, J. 1976. On the complexity of finite sequences. IEEE Trans. Inf. Theory 22, 1 (Jan.), 75--81.
44
 
45
 
46
 
47
Muth, R., Debray, S. K., Watterson, S., and Bosschere, K. D. 1998. alto: A link-time optimizer for the DEC Alpha. Tech. Rep. 98-14, Dept. of Computer Science, The University of Arizona. Dec.
 
48
 
49
van de Wiel, R. 2001. The code compaction bibliography. http://www.extra.research.philips.com/ccb/
 
50
van de Wiel, R., Augusteijn, L., Bink, A., and Hoogendijk, P. 2001. Code compaction: Reducing memory cost of embedded software. Philips white paper. See http://www.extra. research.philips.com/
 
51
van de Wiel, R. and Hoogendijk, P. 2001. Belt-tightening in software. Philips Res. Passw. Mag., 16--19.
 
52
Welch, T. A. 1984. A technique for high-performance data compression. Comput. Mag. Comput. Group News IEEE Comput. Group Soc. 17, 6 (June), 8--19.
53
54
55
 
56
Ziv, J. and Lempel, A. 1977. A universal algorithm for sequential data compression. IEEE Trans. Inf. Theory 23, 3 (May), 337--343.

CITED BY  14

Collaborative Colleagues:
Árpád Beszédes: colleagues
Rudolf Ferenc: colleagues
Tibor Gyimóthy: colleagues
André Dolenc: colleagues
Konsta Karsisto: colleagues