Transforming Source Code to Mathematical Relations for Performance Evaluation
Abstract
Assessing software quality attributes (such as performance, reliability, and security) from source code is of the utmost importance. The performance of a software system can be improved by its parallel and distributed execution. The aim of the parallel and distributed execution is to speed up by providing the maximum possible concurrency in executing the distributed segments. It is a well known fact that distributing a program cannot be always caused speeding up the execution of it; in some cases, this distribution can have negative effects on the running time of the program. Therefore, before distributing a source code, it should be specified whether its distribution could cause maximum possible concurrency or not. The existing methods and tools cannot achieve this aim from the source code. In this paper, we propose a mathematical relationship for object oriented programs that statically analyze the program by verifying the type of synchronous and asynchronous calls inside the source code. Then, we model the invocations of the software methods by Discrete Time Markov Chains (DTMC). Using the properties of DTMC and the proposed mathematical relationship, we will determine whether or not the source code can be distributed on homogeneous processors. The experimental results showed that we can specify whether the program is distributable or not, before deploying it on the distributed systems.
Keywords
Distributed Software Systems, Source Code, Speed-up, Discrete Time Markov Chains
Full Text:
PDFDOI: http://dx.doi.org/10.17951/ai.2015.15.2.7-13
Date of publication: 2015-09-01 00:00:00
Date of submission: 2016-04-28 09:13:31
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