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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. [ABSTRACT FROM AUTHOR]

A known problem in large software companies is to balance the prioritization of short-term and long-term business goals. As an example, architecture suboptimality (Architectural Technical Debt), incurred to deliver fast, might hinder future feature development. However, some technical debt generates more interest to be paid than other. We conducted a multi-phase, multiple-case embedded case study comprehending 9 sites at 6 large international software companies. We have investigated which architectural technical debt items generate more interest , how the interest occurs during software development and which costly extra-activities are triggered as a result. We presented a taxonomy of the most dangerous items identified during the qualitative investigation and a model of their effects that can be used for prioritization, for further investigation and as a quality model for extracting more precise and context-specific metrics. We found that some architectural technical debt items are contagious, causing the interest to be not only fixed, but potentially compound, which leads to the hidden growth of interest (possibly exponential). We found important factors to be monitored to refactor the debt before it becomes too costly. Instances of these phenomena need to be identified and stopped before the development reaches a crises. [ABSTRACT FROM AUTHOR]