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Process correlation analysis model for process improvement identification.

Su-jin Choi1, Dae-Kyoo Kim2, Sooyong Park1

  • 1Sogang University, Seoul, Republic of Korea.

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Summary
This summary is machine-generated.

This study introduces a new model to identify correlations between software process elements, enhancing improvement plans. By analyzing process assessment data, this model boosts the efficiency of software process improvement initiatives.

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Area of Science:

  • Software Engineering
  • Information Systems

Background:

  • Software process improvement (SPI) aims to enhance software development.
  • Process assessments identify strengths and weaknesses, guiding improvement plans.
  • Established models like CMMI provide a framework for SPI.

Purpose of the Study:

  • To address the inefficiency in current software process improvement plans.
  • To develop a model for identifying correlations among process elements.
  • To improve the efficiency of software process improvement by considering element correlations.

Main Methods:

  • Developed a process correlation analysis model based on CMMI.
  • Integrated empirical data from improvement practices into the model.
  • Utilized process assessment results as input for the model.

Main Results:

  • The model effectively identifies correlations between software process elements.
  • Overlooked correlations in process elements can diminish improvement plan efficiency.
  • The proposed model offers a systematic approach to uncovering these correlations.

Conclusions:

  • The developed model aids in identifying crucial process element correlations.
  • Considering these correlations enhances the efficiency of software process improvement plans.
  • The model provides a valuable tool for practitioners and researchers in software engineering.