Towards the statistical construction of hybrid development methods

TL;DR

This paper proposes a statistical approach to systematically construct hybrid software development methods based on large-scale survey data, identifying core practices and providing a framework for method design.

Contribution

It introduces a data-driven procedure for constructing hybrid development methods, grounded in empirical survey data and practice characterization.

Findings

Eight core methods and practices form the basis of modern software development.

An 85% agreement threshold helps characterize hybrid methods by their practices.

A step-by-step construction procedure for hybrid methods is developed.

Abstract

Hardly any software development process is used as prescribed by authors or standards. Regardless of company size or industry sector, a majority of project teams and companies use hybrid development methods (short: hybrid methods) that combine different development methods and practices. Even though such hybrid methods are highly individualized, a common understanding of how to systematically construct synergetic practices is missing. In this article, we make a first step towards a statistical construction procedure for hybrid methods. Grounded in 1467 data points from a large-scale practitioner survey, we study the question: What are hybrid methods made of and how can they be systematically constructed? Our findings show that only eight methods and few practices build the core of modern software development. Using an 85% agreement level in the participants' selections, we provide examples illustrating how hybrid methods can be characterized by the practices they are made of. Furthermore, using this characterization, we develop an initial construction procedure, which allows for defining a method frame and enriching it incrementally to devise a hybrid method using ranked sets of practice.