Parallel Models in Software Life Cycle

  • Aditya P. Mathur


Demand for high quality software has led to the infusion of several innovative techniques for use in different phases of the software life cycle. The knowledge based techniques proposed by Yau and Liu (1986), Yau and Tsai (1987) and high quality testing proposed by DeMillo (Aeree, DeMillo, Budd, and Sayward, 1979) are just two examples of such innovation. One of the major impediments to the use of these techniques is their high computational requirements. A trivial solution to this problem is the use of parallel computers. However, arbitrary use of parallel computers may lead to poor utilization efficiency of the machine.

In this paper we proposed and analyze parallel models for implementation of the two techniques cited above. These models are algorithm guided and, therefore, could be ported to any of the several architectures. For mutation based testing, we have presented three models that differ from each other in their complexity and potential for providing speedups on MIMD architectures. For knowledge based maintenance, we present one model that can be implemented on an MIMD machine.


Parallel Model Execution Sequence Split Point Host Processor Split Phase 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Plenum Press, New York 1990

Authors and Affiliations

  • Aditya P. Mathur
    • 1
  1. 1.Software Engineering Research Center Department of Computer SciencePurdue UniversityW. LafayetteUSA

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