Using correctness, consistency, and completeness patterns for automated scenarios verification

Sarmiento, Edgar; Leite, Julio César Sampaio do Prado; Almentero, Eduardo

doi:10.1109/repa.2015.7407737

Cited by 4 publications

(2 citation statements)

References 5 publications

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“…Scenarios should be written carefully in order to satisfy the quality attributes. Nevertheless, it is challenging to achieve this goal [12]. Scenarios have been historically described by only one person, the requirements engineer who elicited the knowledge, organized it and produced a homogenous specification [7].…”

Section: Introductionmentioning

confidence: 99%

Semantic Support for Scenarios to Improve Communication in Agribusiness

Antonelli

Torres

Hozikian

et al. 2019

Collaborative Networks and Digital Transformation

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Organizations produce and exchange a huge amount of critical information, which main purpose is to obtain acceptable results. Hence, the trend is by considering integrated systems that can be easily adapted to several domains, especially when they need to exchange information. In this context, the agribusiness sector is a good example where massive data is generated, which implies the need for information sharing and collaboration, where the great challenged is support and understand the colliding context. However, every software system relies on its context, with its own rules, dynamism, and languages. Hence, it implies a significant effort to have a complete understanding of the composed domain. For this purpose, scenarios are well-known tools to describe dynamic domains and are commonly described under textbased context. When different stakeholders build Scenarios, it is essential to review them in order to unify their description. Thus, Scenarios under this unified perspective will better support the analysis and identification of relationship between two or more domains. This analysis is the key to design mechanisms to exchange information. Therefore, in the light of this, this paper proposes a semantic definition of Scenarios and a set of queries to identify issues in the Scenarios and improve their quality. In addition to this, a wiki platform to implement the semantic support and the queries is also provided.

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Section: Introductionmentioning

confidence: 99%

Semantic Support for Scenarios to Improve Communication in Agribusiness

Antonelli

Torres

Hozikian

et al. 2019

Collaborative Networks and Digital Transformation

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“…However, energy planning activities and processes are inherently complex. Many inconsistency problems and constraint violations invariably arise in system development and implementation process, in particular where knowledge modelling is incrementally undertaken (Sarmiento et al 2015;Beydoun et al 1998). According to Balint et al (2011), some of the common problems that may arise in the energy planning system such as a lack of a single problem statement, administrative and scientific complexity, conflicting data values, conflicting objectives, political complexity, a dynamic and a changing context, and multiplicity of actors involved.…”

Section: Introductionmentioning

confidence: 99%

Uncovering Complexity in the Jakarta Energy Planning Process using Agent-Oriented Analysis

Anggoro¹,

Sandu²,

Beydoun³

2018

Australasian Conference on Information Systems 2018

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The Jakarta Energy Planning Process (JEPP) is expected to be a successful template for other provinces in Indonesia. However, JEPP consists of a complex set of interrelated activities. These activities are fraught with difficulties and errors, including incorrectness, inconsistency, incompleteness, and redundancy in the process under which the Jakarta energy planning is undertaken. This paper aims to identify complexity issues in JEPP with the aim to alleviate these complexities using Agent-Oriented Analysis (AOA). This research uses the Design Science Research (DSR) method and towards the analysis employs seven Agent-Based Modellings (ABMs), including goal model, role model, organisation model, interaction model, environment model, agent model, and scenario model. The research consists of five stages: the synthesis of a preliminary knowledge analysis framework, the identification of complexity issues, recommendation synthesis, and finally the development of the complete knowledge analysis framework. While the analysis undertaken in this paper focuses on Jakarta, the developed knowledge analysis framework should be useful for energy planners in other regions, and research communities in general who are involved in such endeavours in developing complex planning processes.

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