Abstract
Farm management information system (FMIS) is an important element of precision agriculture to support the decision making process in the agricultural business. Developing FMIS is not trivial and requires the proper design and implementation models for supporting the understandability, enhancing communication and analysis of the design decisions, and the communication among stakeholders. To cope with these challenges, a Domain-specific language (DSL) framework for the design and development of precision-agriculture FMISs is proposed and evaluated. The DSL framework is developed based on a domain-driven design approach in which a feature diagram is provided that represents the common and variant features of the precision agriculture domain. The key requirements for the DSL framework are discussed, the scope of the DSL is defined, and the set of DSLs for supporting FMISs is presented. A controlled experiment demonstrates that the proposed DSL framework is easy to learn and to use, and is effective in developing high-quality system models for precision agriculture.
Highlights
Precision agriculture is a farming management concept that applies advanced information technology and the corresponding principles to increase production and economic returns, often intending to reduce the impact on the environment (Rains and Thomas 2009)
The analysis focuses on farm management information systems for precision agriculture
The participants were asked about their opinion on the ease of learning and using the domain-specific language (DSL)
Summary
Precision agriculture is a farming management concept that applies advanced information technology and the corresponding principles to increase production and economic returns, often intending to reduce the impact on the environment (Rains and Thomas 2009). General-purpose programming languages (GPLs) that are agnostic to a particular domain are being used to develop programs for agriculture. These GPLs often fail to express the specific concerns of the agriculture domain, have a steep learning curve, and are difficult to master in a short time. Domain-specific languages (DSLs) (Kleppe 2009; Stahl and Voelter 2006; Voelter 2013; Tekinerdogan and Demirli 2013) have been developed in several scientific fields to facilitate the construction of models at a level closer to the conceptual model, thereby making model implementation more accessible to domain experts and declarative, rather than imperative (Challenger et al 2015; Fall and Fall 2001; Fowler 2010; Mernik et al 2005; Nascimento 2012; Oliviera et al Oliveira et al 2009; Tekinerdogan and Arkin 2019)
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