Source Code Optimization Techniques for Data Flow Dominated Embedded Software

Author(s):  
Heiko Falk ◽  
Peter Marwedel
2014 ◽  
Vol 599-601 ◽  
pp. 1346-1349
Author(s):  
Hai Lin ◽  
Bao Liang Mu

In this paper, we propose a new method for code optimization. This new method is based on backward data flow analysis, and the optimization is done on the source code level. First we design a tiny language to experiment with. Then, using data flow analysis, we set up some simultaneous equations and collect the liveness information for all program points. This is the basis for the optimization. Using this technique, some code can be safely eliminated without affecting the semantics of the code segment.


Author(s):  
Masahide Nakamur ◽  
Hiroshi Igaki ◽  
Takahiro Kimura ◽  
Kenichi Matsumoto

In order to support legacy migration to the service-oriented architecture (SOA), this paper presents a pragmatic method that derives candidates of services from procedural programs. In the SOA, every service is supposed to be a process (procedure) with (1) open interface, (2) self-containedness, and (3) coarse granularity for business. Such services are identified from the source code and its data flow diagram (DFD), by analyzing data and control dependencies among processes. Specifically, first the DFD must be obtained with reverse-engineering techniques. For each layer of the DFD, every data flow is classified into three categories. Using the data category and control among procedures, four types of dependency are categorized. Finally, six rules are applied that aggregate mutually dependent processes and extract them as a service. A case study with a liquor shop inventory control system extracts service candidates with various granularities.


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