NOn-Technical Debt in Large-Scale Agile Software Development (NODLA)

Since the inception of the Agile Manifesto in 2001, the software industry hailed agile as a paradigmatic shift in the development of software systems. Initially, agile methods were typically deployed in smaller projects with few project team members. Recently, agile methods applicability created interest in larger projects, referred to as large-scale Agile Software Development (ASD). Large-scale ASD is gaining adoption by using a range of frameworks such as the Scaled Agile Framework (SAFe), Large-Scale Scrum (LeSS), and the Spotify model, along with the popular Agile methods such as Scrum and Kanban. However, ASD in large-scale projects is challenging, and one reason is inter-team coordination and communication as well as developers’ morale. When teams fail to collaborate, the negative effects hinder agility in the medium and long term. In other words, the organization and the system accumulate debt. Debt is a metaphor used to communicate the consequences of poor software development practices to various stakeholders.

Incurring technical debt (i.e., design debt, code debt) and non-technical debt (i.e., process, social and people debt) may bring short-term benefits to a project, but such benefits are often achieved at the cost of extra work in the future. It is an evident fact that “agile development appears to be more prone to technical debt accumulation compared to traditional software development approaches, due to its delivery-oriented focus” . This becomes more complex when it comes to large-scale ASD projects, as it is too easy to lose track of delayed tasks or to misunderstand their impact. Such challenges are becoming more complex during and post COVID19 pandemic. Currently, there is a limited insight on how to identify and efficiently handle various types’ of debt in large-scale ASD projects.

NODLA aim to investigate Non-Technical Debt (NTD) with the purpose of understanding causes leading to the accumulation of NTD, impacts of NTD, and mitigation strategies in the context of large-scale ASD from professionals and researchers perspectives. The project has three main goals: propose a taxonomy and a descriptive model for NTD; investigate how developers’ morale is influence by NTD, and develop strategies to balance NTD in large-scale ASD.

This is a joint research project between the Department of Computer Science (CS) at Karlstad University and three industrial partners naming TietoEvry AB, Skandia AB and AFRY AB. This project investigates the burning questions which industrial partners are facing in the context of large-scale ASD. The results of the project are envisaged in integrating into the products and solution portfolios of our industry partners to impact industry standards and best practices immediately. Further, NODLE will improve the existing large-scale ASD frameworks to a large extend.


Dr. Muhammad Ovais Ahmad (Principal investigator), Department of CS, Karlstad University, Sweden.

Dr. Tomas Gustavsson, Department of Industrial Engineering and Management, Karlstad University, Sweden.