A grounded theory of selecting lean and agile practices for software development

Abstract

The practices of lean and agile methods are important to manage and guide projects development in different situations. However, selecting the appropriate practices of lean and agile methods is a daunting task, owing to the availability of hundreds of practices. This wide variety of available practices bewilders potential users, in terms of the best practices that may yield satisfactory solution when applied to the project development. Lean and agile practices selection model is necessary to guide both academic and industrial experts to choose the appropriate practices for a specific project development. Thus, this study aimed to develop lean and agile practices selection (LAPS) model that presents a clear picture of how developers can use LAPS model to select and adopt different practices from various lean and agile methods. Qualitative research method (e.g., grounded theory) was used to interview 18 software developers across 13 countries. The validated qualitative analysis results showed that the proposed LAPS model consists of two main components, which are (1) lean and agile practices that include 41 best practices related to lean and agile methods and (2) factors that affect the process of lean and agile practices selection including five main factors and 17 subfactors associated with the five main factors. The two case studies conducted assured the validity and applicability of the lean and agile practices selection model.

Combining Phenomenology and Grounded Theory in Software Engineering: An Experience

“…Grounded theory was firstly applied in SE research for investigating the use of Computer-aided Software Engineering (CASE) (Orlikowski, 1993). Other SE research that adopted grounded theory include topics concerning requirements engineering, distributed development and agile development (Badreddin, 2013;Alqudah et al, 2019;Alqudah et al, 2023). Some experience of using grounded theory in SE research have also been reported (Razali et al, 2020).…”