A low-resource environment has limitations in terms of resources, such as limited network availability and low-powered computing devices. In such environments, it is arguably more difficult to set up new software systems, maintain existing software, and migrate between software systems. This paper presents a survey of software systems for low-resource environments to highlight the challenges (social and technical) and concepts. A qualitative methodology is employed, consisting of an extensive literature review and comparative analysis of selected software systems. The literature covers academic and non-academic sources, focusing on identifying software solutions that address specific challenges in low-resource environments. The selected software systems are categorized based on their ability to overcome challenges such as limited technical skills, device constraints, and socio-cultural issues. The study reveals that despite noteworthy progress, unresolved challenges persist, necessitating further attention to enable the optimal performance of software systems in low-resource environments.

Large student numbers often drive teaching staff to consider greater degrees of automation of assessment activities. In introductory Computer Science classes - where submitted programs need to repeatedly be compiled, executed and tested -automation is an obvious route to investigate. This paper reports on an experimental automation system for assessing programming assignments, and its integration with the open source Sakai learning management system. While the system has been an administrative success, feedback from students has identified numerous areas for improvement at the interface of the student and the automatic marker. Furthermore, the use of automation has highlighted the need for teaching software development methodology from an early stage.

NDLTD, the Networked Digital Library of Theses and Dissertations, supports and encourages the production and archiving of electronic theses and dissertations (ETDs). While many current NDLTD member institutions and consortia have individual collections accessible online, there has until recently been no single mechanism to aggregate all ETDs to provide NDLTD‐wide services (e.g. searching). With the emergence of the Open Archives Initiative (OAI), that has changed. The OAI’s Protocol for Metadata Harvesting is a robust interoperability solution that defines a standard method of exchanging metadata. While working with the OAI to develop and test the metadata harvesting standard, we have set up and actively maintain a central NDLTD metadata collection and multiple user portals. We discuss in this article our experiences in building this distributed digital library based upon the work of the OAI.