Success and Failure in Software Engineering: a Followup Systematic Literature Review

TL;DR

This paper presents an in-depth systematic literature review on success and failure in software engineering, identifying key factors, clusters, and a new quality model to better understand and predict project outcomes.

Contribution

It offers a comprehensive grounded-theory of success and failure factors, with validated clusters and a novel quality model incorporating organizational structure aspects.

Findings

Harvested over 500 success and failure factors

Identified 14 validated factor clusters for risk analysis

Proposed a new quality model including organizational structures

Abstract

Success and failure in software engineering are still among the least understood phenomena in the discipline. In a recent special journal issue on the topic, Mantyla et al. started discussing these topics from different angles; the authors focused their contributions on offering a general overview of both topics without deeper detail. Recognising the importance and impact of the topic, we have executed a followup, more in-depth systematic literature review with additional analyses beyond what was previously provided. These new analyses offer: (a) a grounded-theory of success and failure factors, harvesting over 500+ factors from the literature; (b) 14 manually-validated clusters of factors that provide relevant areas for success- and failure-specific measurement and risk-analysis; (c) a quality model composed of previously unmeasured organizational structure quantities which are germane to software product, process, and community quality. We show that the topics of success and failure deserve further study as well as further automated tool support, e.g., monitoring tools and metrics able to track the factors and patterns emerging from our study. This paper provides managers with risks as well as a more fine-grained analysis of the parameters that can be appraised to anticipate the risks.