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The Software Complexity Estimation Method in Algorithm Level by Analysis of Source code  

Lim, Woong (Dept. of Computer Engineering, Kwangwoon University)
Nam, Jung-Hak (Dept. of Computer Engineering, Kwangwoon University)
Sim, Dong-Gyu (Dept. of Computer Engineering, Kwangwoon University)
Cho, Dae-Sung (Samsung Electronics)
Choi, Woong-Il (Samsung Electronics)
Publication Information
Journal of the Institute of Electronics Engineers of Korea SP / v.47, no.5, 2010 , pp. 153-164 More about this Journal
Abstract
A program consumes energy by executing its instructions. The amount of cosumed power is mainly proportional to algorithm complexity and it can be calculated by using complexity information. Generally, the complexity of a S/W is estimated by the microprocessor simulator. But, the simulation takes long time why the simulator is a software modeled the hardware and it only provides the information about computational complexity quantitatively. In this paper, we propose a complexity estimation method of analysis of S/W on source code level and produce the complexity metric mathematically. The function-wise complexity metrics give the detailed information about the calculation-concentrated location in function. The performance of the proposed method is compared with the result of the gate-level microprocessor simulator 'SimpleScalar'. The used softwares for performance test are $4{\times}4$ integer transform, intra-prediction and motion estimation in the latest video codec, H.264/AVC. The number of executed instructions are used to estimate quantitatively and it appears about 11.6%, 9.6% and 3.5% of error respectively in contradistinction to the result of SimpleScalar.
Keywords
complexity estimation; software optimization; power consumption;
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