scholarly journals CP-DSL: Supporting Configuration and Parametrization of Ocean Models with UVic (2.9) and MITgcm (67w)

2021 ◽  
Author(s):  
Reiner Jung ◽  
Sven Gundlach ◽  
Wilhelm Hasselbring

Abstract. Ocean models are long-living software systems facing challenges with increasing complexity, architecture erosion, and managing legacy code. These challenges increase maintenance costs in development and use, which reduces the time and resources available for research. Software engineering addresses these challenges by separation of concerns and modularization. One particular approach is to separate concerns by tailor-made notations, i.e. Domain-Specific Languages (DSLs). Using DSLs, the model developer can focus on one concern at a time without the need to consider other concerns of a software system simultaneously. In ocean and climate models, DSL tooling, like PSyclone and Dusk/Dawn, is used for instance to separate scientific and technical code. CP-DSL complements this approach with a focus on configuration and parametrization, which play an important role in ocean models, especially in parameter optimization and scenario-based simulations. CP-DSL is designed to be model agnostic and provides a unified interface to different ocean models. Furthermore, the DSL can be integrated into tools and processes used by domain experts. In this paper we report on the DSL design, implementation, and the evaluation with scientists and research software engineers. The implementation of CP-DSL is available as open source software and a replication package for configuration and parameterization of UVic and MITgcm is provided.

Author(s):  
Maria Ulan ◽  
Welf Löwe ◽  
Morgan Ericsson ◽  
Anna Wingkvist

AbstractA quality model is a conceptual decomposition of an abstract notion of quality into relevant, possibly conflicting characteristics and further into measurable metrics. For quality assessment and decision making, metrics values are aggregated to characteristics and ultimately to quality scores. Aggregation has often been problematic as quality models do not provide the semantics of aggregation. This makes it hard to formally reason about metrics, characteristics, and quality. We argue that aggregation needs to be interpretable and mathematically well defined in order to assess, to compare, and to improve quality. To address this challenge, we propose a probabilistic approach to aggregation and define quality scores based on joint distributions of absolute metrics values. To evaluate the proposed approach and its implementation under realistic conditions, we conduct empirical studies on bug prediction of ca. 5000 software classes, maintainability of ca. 15000 open-source software systems, and on the information quality of ca. 100000 real-world technical documents. We found that our approach is feasible, accurate, and scalable in performance.


2021 ◽  
Vol 11 (12) ◽  
pp. 5476
Author(s):  
Ana Pajić Simović ◽  
Slađan Babarogić ◽  
Ognjen Pantelić ◽  
Stefan Krstović

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.


2021 ◽  
Vol 11 (12) ◽  
pp. 5690
Author(s):  
Mamdouh Alenezi

The evolution of software is necessary for the success of software systems. Studying the evolution of software and understanding it is a vocal topic of study in software engineering. One of the primary concepts of software evolution is that the internal quality of a software system declines when it evolves. In this paper, the method of evolution of the internal quality of object-oriented open-source software systems has been examined by applying a software metric approach. More specifically, we analyze how software systems evolve over versions regarding size and the relationship between size and different internal quality metrics. The results and observations of this research include: (i) there is a significant difference between different systems concerning the LOC variable (ii) there is a significant correlation between all pairwise comparisons of internal quality metrics, and (iii) the effect of complexity and inheritance on the LOC was positive and significant, while the effect of Coupling and Cohesion was not significant.


2010 ◽  
Vol 20-23 ◽  
pp. 992-997 ◽  
Author(s):  
Qing Wu ◽  
Shi Ying ◽  
You Cong Ni ◽  
Hua Cui

Service-oriented software systems are inherently complex and have to cope with an increasing number of exceptional conditions in order to meet the system’s dynamic requirements. This work proposes an architecture framework which has exception handling capability. This framework ensures the credibility of service-oriented software, during the architectural stage, by adding exception handling-related architecture elements and modeling exception handling process. It allows a clear separation of concerns between the business function and the exception handling unit, using reflection mechanism. It plays an important guiding role for achieving reliable service-oriented system.


2020 ◽  
pp. 53-108
Author(s):  
Christian Schlegel ◽  
Alex Lotz ◽  
Matthias Lutz ◽  
Dennis Stampfer

AbstractSuccessful engineering principles for building software systems rely on the separation of concerns for mastering complexity. However, just working on different concerns of a system in a collaborative way is not good enough for economically feasible tailored solutions. A successful approach for this is the composition of complex systems out of commodity building blocks. These come as is and can be represented as blocks with ports via data sheets. Data sheets are models and allow a proper selection and configuration as well as the prediction of the behavior of a building block in a specific context. This chapter explains how model-driven approaches can be used to support separation of roles and composition for robotics software systems. The models, open-source tools, open-source robotics software components and fully deployable robotics software systems shape a robotics software ecosystem.


2020 ◽  
Author(s):  
Bradley M. Conrad ◽  
Matthew R. Johnson

Abstract. Gas flaring is an important source of atmospheric soot/black carbon, especially in sensitive Arctic regions. However, emissions have traditionally been challenging to measure and remain poorly characterized, confounding international reporting requirements and adding uncertainty to climate models. The sky-LOSA optical measurement technique has emerged as a powerful means to quantify flare black carbon emissions in the field, but broader adoption has been hampered by the complexity of its deployment, where decisions during setup in the field can have profound, non-linear impacts on achievable measurement uncertainties. To address this challenge, this paper presents a prescriptive measurement protocol and associated open-source software tool that simplifies acquisition of sky-LOSA data in the field. Leveraging a comprehensive Monte Carlo-based General Uncertainty Analysis (GUA) to predict measurement uncertainties over the entire breadth of possible measurement conditions, general heuristics are identified to guide a sky-LOSA user toward optimal data collection. These are further extended in the open-source software utility, SetupSkyLOSA, which interprets the GUA results to provide detailed guidance for any specific combination of location, date/time, and flare, plume, and ambient conditions. Finally, a case study of a sky-LOSA measurement at an oil and gas facility in Mexico is used to demonstrate the utility of the software tool, where potentially small region(s) of optimal instrument setup are easily and quickly identified. It is hoped that this work will help increase the accessibility of the sky-LOSA technique and ultimately the availability of field measurement data for flare black carbon emissions.


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