ORCID Profile
0000-0002-7263-821X
Current Organisation
UNSW Sydney
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Publisher: Springer International Publishing
Date: 2016
Publisher: Association for Computing Machinery (ACM)
Date: 25-06-2016
DOI: 10.1145/2903138
Abstract: Pattern mining, that is, the automated discovery of patterns from data, is a mathematically complex and computationally demanding problem that is generally not manageable by humans. In this article, we focus on small datasets and study whether it is possible to mine patterns with the help of the crowd by means of a set of controlled experiments on a common crowdsourcing platform. We specifically concentrate on mining model patterns from a dataset of real mashup models taken from Yahoo! Pipes and cover the entire pattern mining process, including pattern identification and quality assessment. The results of our experiments show that a sensible design of crowdsourcing tasks indeed may enable the crowd to identify patterns from small datasets (40 models). The results, however, also show that the design of tasks for the assessment of the quality of patterns to decide which patterns to retain for further processing and use is much harder (our experiments fail to elicit assessments from the crowd that are similar to those by an expert). The problem is relevant in general to model-driven development (e.g., UML, business processes, scientific workflows), in that reusable model patterns encode valuable modeling and domain knowledge, such as best practices, organizational conventions, or technical choices, that modelers can benefit from when designing their own models.
Publisher: Springer International Publishing
Date: 2021
Publisher: IEEE
Date: 12-2007
Publisher: Springer Berlin Heidelberg
Date: 2011
Publisher: IEEE
Date: 25-10-2021
Publisher: Springer International Publishing
Date: 2020
Publisher: Springer International Publishing
Date: 2014
Publisher: IEEE
Date: 10-2020
Publisher: Springer Berlin Heidelberg
Date: 2010
Publisher: ACM
Date: 16-04-2012
Publisher: ACM
Date: 11-10-2021
Publisher: Springer International Publishing
Date: 2020
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 07-2010
DOI: 10.1109/MIC.2010.59
Publisher: Springer International Publishing
Date: 2019
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2016
DOI: 10.1109/MIC.2016.22
Publisher: Springer International Publishing
Date: 2016
Publisher: IGI Global
Date: 2012
DOI: 10.4018/978-1-61350-432-1.CH022
Abstract: Assessing whether a company’s business practices conform to laws and regulations and follow standards and SLAs, i.e., compliance management, is a complex and costly task. Few software tools aiding compliance management exist yet, they typically do not address the needs of who is actually in charge of assessing and understanding compliance. We advocate the use of a compliance governance dashboard and suitable root cause analysis techniques that are specifically tailored to the needs of compliance experts and auditors. The design and implementation of these instruments are challenging for at least three reasons: (1) it is fundamental to identify the right level of abstraction for the information to be shown (2) it is not trivial to visualize different analysis perspectives and (3) it is difficult to manage and analyze the large amount of involved concepts, instruments, and data. This chapter shows how to address these issues, which concepts and models underlie the problem, and, eventually, how IT can effectively support compliance analysis in Service-Oriented Architectures (SOAs).
Publisher: IEEE
Date: 07-2020
Publisher: Elsevier BV
Date: 04-2016
Publisher: Springer Science and Business Media LLC
Date: 31-01-2020
Publisher: Springer Berlin Heidelberg
Date: 2010
Publisher: Springer Science and Business Media LLC
Date: 02-02-2013
Publisher: Springer Berlin Heidelberg
Date: 2011
Publisher: IEEE
Date: 10-2020
Publisher: Springer New York
Date: 04-09-2013
Publisher: Centro Latino Americano de Estudios en Informatica
Date: 31-07-2021
Abstract: Application Programming Interface (API) is a core technology that facilitates developers’ productivity by enabling the reuse of software components. Understanding APIs and gaining knowledge about their usage are therefore fundamental needs for developers. Here, API documentation plays a pivotal role in enabling developers to take full advantage of the benefits brought by APIs. The quality of API documentation has therefore become an important concern given the celerity and dynamics at which APIs are now being made available to users. This article aims at exploring existing research in the area of API documentation in order to identify the associated quality dimensions addressed by the literature. The research is carried out as a systematic mapping study where 103 research papers selected from the literature were reviewed and a total of 5 core quality dimensions were identified and analyzed. By focusing on the two most relevant quality dimensions (understandability and completeness), this article presents an approach to enable API users to explore, discover and learn about APIs through API topic issues discussed in Stack Overflow (SO). We demonstrate the feasibility of our approach through Scout-bot, our tool for exploration and discovery of API topic issues.
Publisher: Springer International Publishing
Date: 2019
Publisher: Springer International Publishing
Date: 2019
No related grants have been discovered for Carlos Rodriguez.