Data Analysis for Software Process Improvement: A Systematic Literature Review

  • Jezreel MejíaEmail author
  • Freddy Íñiguez
  • Mirna Muñoz
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 569)


Current information systems demand high quality software products that guarantee a safety and a reliable use for our day-to-day life. A common understanding between software organizations and practitioners is that software product quality largely depends on the software process quality. A Software Process Improvement (SPI) initiative consists of a set of practices and activities that are designed to improve software organizations processes through the evaluation of their current practices and the way software products and services are developed. However, the big amount of information that is generated from the software organization practices has complicated the knowledge extraction, and therefore, the SPI initiatives. A possible technique to make a good knowledge management is data analysis. This paper presents the results of a systematic literature review to establish the state-of-the-art of data analysis for software process improvement. The findings also encourage to the creation of a BigData-based data analysis model in a future work for this research.


Knowledge management Information management Data analysis Software product quality Software process quality Software engineering 


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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Jezreel Mejía
    • 1
    Email author
  • Freddy Íñiguez
    • 1
  • Mirna Muñoz
    • 1
  1. 1.Center for Research in MathematicsZacatecasMexico

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