Jenny Morales (Autonomous University of Chile), Cristian Rusu (Pontifical Catholic University of Chile), Federico Botella (Miguel Hernández University of Elche) and Daniela Quiñones (Pontifical Catholic University of Chile).
Abstract. Programmers use various software development artifacts in their work, such as programming environments, design documents, and programming codes. These software artifacts can be studied and improved based on usability and User eXperience (UX) factors. In this paper, we consider programmers to be a specific case of users and analyze different elements that influence their experience in this specific context. We conducted a systematic literature review of papers published over the last ten years related to 1) the definition of the Programmer eXperience (PX); 2) the PX, UX, and usability factors regarding the programming environments, design documents, and programming codes; and 3) sets of heuristics to evaluate the software development artifacts mentioned before. We analyzed 73 articles, and the results obtained show that: 1) the important elements that influence the PX are the motivation of programmers and the choice of tools they use in their work, such as programming environments; 2) most of the identified studies (59%) aimed to evaluate the influence of the PX, UX, and usability on programming environments; 3) the majority of the studies (70%) used methods such as usability tests and/or heuristic evaluation methods; and 4) four sets of heuristics are used to evaluate software development artifacts in relation to programming environments, programming languages, and application programming interfaces. The results suggest that further research in this area is necessary to better understand and evaluate the concept of the PX.
Keywords. Heuristic evaluation; Programmer eXperience; Systematic literature review; User eXperience; Usability
Scientific articles
N. Allouch, Luis A. Guardiola, & A. Meca (2024). Measuring productivity in networks: A game-theoretic approach. Socio-Economic Planning Sciences, 91, 101783.
N. Allouch (University of Kent – School of Economics), Luis A. Guardiola (Departamento de Métodos Cuantitativos para la Economía y Empresa, Universidad de Murcia), Ana Meca (I.U. Centro de Investigación Operativa, Universidad Miguel Hernández de Elche) Abstract: Measuring individual productivity (or equivalently distributing the overall productivity) in a network structure of workers displaying peer effects has been [...]