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Data flow-based testing uses data flow analysis as source of information to derive testing requirements.
The static method mainly includes control flow analysis, data flow analysis, structural analysis, etc.
Bidirectional data flow analysis has become the standard technique for solving bit-vector-based code motion problems in the presence of critical edges.
Through the system function data flow analysis, get the logical structure of database system, and on this basis, the physical structure of database to create all kinds of information inquiry, update operation.
On one side, we count on deterministic approaches, among which we cite: data flow analysis [12], symbolic execution [13], dynamic partitioning [14], control flow graphs [15], textual differences in the code [16], model-based testing [17], and TC selection based on a similarity functions [11].
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However, their approach does not incorporate data-flow analysis.
For their determination we introduce a static data-flow analysis called "to be recorded" analysis.
We build a data-flow analysis based on constraint graphs, whose nodes are program points and whose arcs propagate information according to the semantics of each bytecode instruction.
While a static clock and data-flow analysis may be able to detect the dependencies to desynchronize such programs [17], adding an explicit notion of independence makes it possible for compilers to create desynchronized code without sophisticated and expensive analyses.
Specifically, we apply data-flow analysis to extract the semantic flow of the registers as well as the semantic components of the control flow graph, which are then synthesized into a novel representation called the semantic flow graph (SFG).
The experimental results on the MTTS specification show that the exhaustive model-checking approach scales reasonably well and is efficient at finding errors in specifications that were not previously detected with the data-flow analysis (DFA) capabilities of Plural.
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