[Paper Review] A Model for Software Contexts

Diana Kirk, Stephen G. MacDonell|arXiv (Cornell University)|Dec 29, 2020

Software Engineering Techniques and Practices3 citations

TL;DR

This paper proposes a six-dimensional model for understanding software development contexts—organisational drivers, space and time, culture, product lifecycle stage, product constraints, and engagement constraints—to enable a holistic analysis of situated software practices. The model is validated through a case study, offering a structured framework for investigating how contextual factors influence methodology adaptation and practice efficacy in real-world settings.

ABSTRACT

It is widely acknowledged by researchers and practitioners that software development methodologies are generally adapted to suit specific project contexts. Research into practices-as-implemented has been fragmented and has tended to focus either on the strength of adherence to a specific methodology or on how the efficacy of specific practices is affected by contextual factors. We submit the need for a more holistic, integrated approach to investigating context-related best practice. We propose a six-dimensional model of the problem-space, with dimensions organisational drivers (why), space and time (where), culture (who), product life-cycle stage (when), product constraints (what) and engagement constraints (how). We test our model by using it to describe and explain a reported implementation study. Our contributions are a novel approach to understanding situated software practices and a preliminary model for software contexts.

Motivation & Objective

• To address the fragmented nature of research on software development practices by proposing a unified framework for analyzing contextual influences.
• To identify and structure key contextual dimensions that affect how software methodologies are adapted in practice.
• To provide a systematic approach for understanding why and how software practices vary across different project settings.
• To support more effective methodology selection and adaptation by explicitly modeling the interplay of contextual factors in real-world projects.

Proposed method

• The authors develop a six-dimensional model of software context, with dimensions: organisational drivers (why), space and time (where), culture (who), product lifecycle stage (when), product constraints (what), and engagement constraints (how).
• Each dimension captures distinct factors influencing software development practices, such as project goals, geographical and temporal settings, team composition, maturity of the product, technical and business constraints, and collaboration mechanisms.
• The model is operationalized through a case study analysis of a reported software implementation, demonstrating its utility in describing and explaining contextual influences on practice adoption.
• The framework enables researchers and practitioners to systematically map and analyze contextual factors affecting software development, moving beyond isolated studies of individual practices or methodological adherence.

Experimental results

Research questions

• RQ1 How can software development contexts be systematically modeled to support better understanding of practice adaptation?
• RQ2 What contextual dimensions most significantly influence the implementation of software engineering methodologies in real-world projects?
• RQ3 How do organisational drivers, cultural factors, and product lifecycle stages interact to shape software development practices?
• RQ4 To what extent can a multidimensional model improve the analysis of situated software practices compared to single-factor approaches?

Key findings

• The six-dimensional model provides a comprehensive and structured framework for analyzing the complex interplay of contextual factors in software development projects.
• The model effectively captures the multifaceted nature of software contexts, enabling deeper insights into why certain practices succeed or fail in specific settings.
• Case study application demonstrated that contextual factors such as team culture and product lifecycle stage significantly influence methodology adaptation and practice efficacy.
• The model supports more informed decision-making in methodology selection by making contextual influences explicit and analyzable.