Quantitative Productivity Analysis of a Domain-Specific Modeling Language

2015 ◽  
pp. 313-344
Author(s):  
Joe Hoffert ◽  
Douglas C. Schmidt ◽  
Aniruddha Gokhale
Keyword(s):  
Ease Of Use ◽  
Alternative Methods ◽  
Modeling Language ◽  
Modeling Languages ◽  
Productivity Analysis ◽  
Model Driven ◽  
Domain Specific ◽  
Productivity Gain ◽  
Domain Specific Modeling ◽  
Specific Modeling

Model-Driven Engineering (MDE), in general, and Domain-Specific Modeling Languages (DSMLs), in particular, are increasingly used to manage the complexity of developing applications in various domains. Although many DSML benefits are qualitative (e.g., ease of use, familiarity of domain concepts), there is a need to quantitatively demonstrate the benefits of DSMLs (e.g., quantify when DSMLs provide savings in development time) to simplify comparison and evaluation. This chapter describes how the authors conducted quantitative productivity analysis for a DSML (i.e., the Distributed Quality-of-Service [QoS] Modeling Language [DQML]). The analysis shows (1) the significant quantitative productivity gain achieved when using a DSML to develop configuration models compared with not using a DSML, (2) the significant quantitative productivity gain achieved when using a DSML interpreter to automatically generate implementation artifacts as compared to alternative methods when configuring application entities, and (3) the viability of quantitative productivity metrics for DSMLs.

Productivity Analysis of the Distributed QoS Modeling Language

2011 ◽  
pp. 156-176
Author(s):  
Joe Hoffert ◽  
Douglas C. Schmidt ◽  
Aniruddha Gokhale
Keyword(s):  
Ease Of Use ◽  
Alternative Methods ◽  
Modeling Language ◽  
Modeling Languages ◽  
Productivity Analysis ◽  
Model Driven ◽  
Domain Specific ◽  
Productivity Gain ◽  
Domain Specific Modeling

Model-driven engineering (MDE), in general, and Domain-Specific Modeling Languages (DSMLs), in particular, are increasingly used to manage the complexity of developing applications in various domains. Although many DSML benefits are qualitative (e.g., ease of use, familiarity of domain concepts), there is a need to quantitatively demonstrate the benefits of DSMLs (e.g., quantify when DSMLs provide savings in development time) to simplify comparison and evaluation. This chapter describes how the authors conducted productivity analysis for the Distributed Quality-of-Service (QoS) Modeling Language (DQML). Their analysis shows (1) the significant productivity gain using DQML compared with alternative methods when configuring application entities and (2) the viability of quantitative productivity metrics for DSMLs.

scholarly journals Supporting the platform extensibility for the model-driven development of agent systems by the interoperability between domain-specific modeling languages of multi-agent systems

2017 ◽  
Vol 14 (3) ◽  
pp. 875-912 ◽  
Author(s):  
Geylani Kardas ◽  
Emine Bircan ◽  
Moharram Challenger
Keyword(s):  
Conventional Approach ◽  
Modeling Languages ◽  
Multi Agent Systems ◽  
Model Driven Development ◽  
Agent Systems ◽  
Model Driven ◽  
Domain Specific ◽  
Domain Specific Modeling ◽  
Multi Agent ◽  
Specific Modeling

The conventional approach currently followed in the development of domain-specific modeling languages (DSMLs) for multi-agent systems (MASs) requires the definition and implementation of new model-to-model and model-totext transformations from scratch in order to make the DSMLs functional for each different agent execution platforms. In this paper, we present an alternative approach which considers the construction of the interoperability between MAS DSMLs for a more efficient way of platform support extension. The feasibility of using this new interoperability approach instead of the conventional approach is exhibited by discussing and evaluating the model-driven engineering required for the application of both approaches. Use of the approaches is also exemplified with a case study which covers the model-driven development of an agent-based stock exchange system. In comparison to the conventional approach, evaluation results show that the interoperability approach requires both less development time and effort considering design and implementation of all required transformations.

scholarly journals Towards a Domain-Specific Modeling Language for Extracting Event Logs from ERP Systems

2021 ◽  
Vol 11 (12) ◽  
pp. 5476
Author(s):  
Ana Pajić Simović ◽  
Slađan Babarogić ◽  
Ognjen Pantelić ◽  
Stefan Krstović
Keyword(s):  
Process Mining ◽  
Modeling Language ◽  
Sufficient Information ◽  
Event Data ◽  
Erp Systems ◽  
Domain Experts ◽  
Domain Specific ◽  
Event Logs ◽  
Domain Specific Modeling ◽  
Specific Modeling

Enterprise resource planning (ERP) systems are often seen as viable sources of data for process mining analysis. To perform most of the existing process mining techniques, it is necessary to obtain a valid event log that is fully compliant with the eXtensible Event Stream (XES) standard. In ERP systems, such event logs are not available as the concept of business activity is missing. Extracting event data from an ERP database is not a trivial task and requires in-depth knowledge of the business processes and underlying data structure. Therefore, domain experts require proper techniques and tools for extracting event data from ERP databases. In this paper, we present the full specification of a domain-specific modeling language for facilitating the extraction of appropriate event data from transactional databases by domain experts. The modeling language has been developed to support complex ambiguous cases when using ERP systems. We demonstrate its applicability using a case study with real data and show that the language includes constructs that enable a domain expert to easily model data of interest in the log extraction step. The language provides sufficient information to extract and transform data from transactional ERP databases to the XES format.

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