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Details

  • Name

    Filipe Alexandre Pais
  • Cluster

    Computer Science
  • Role

    Senior Researcher
  • Since

    01st December 2018
Publications

2019

Live software development

Authors
Aguiar, A; Restivo, A; Correia, FF; Ferreira, HS; Dias, JP;

Publication
Proceedings of the 3rd International Companion Conference on Art, Science, and Engineering of Programming - Programming '19

Abstract

2019

Trusted Data Transformation with Blockchain Technology in Open Data

Authors
Tavares, B; Correia, FF; Restivo, A;

Publication
Distributed Computing and Artificial Intelligence, 16th International Conference, DCAI 2019, Avila, Spain, 26-28 June, 2019, Special Sessions

Abstract
Trusted open data can be used for auditing, accountability, business development, or as an anti-corruption mechanism. Metadata information can address provenance concerns, and trust issues can somehow be mitigated by digital signatures. Those approaches can trace the data origin, but usually lack information about the transformation process. Creating trust in an open data service through technology can reduce the need for third-party certifications, and creating a distributed consensus mechanism capable of validating all the transformations can guarantee that the datasets are reliable and easy to use. This work aims to leverage blockchain technologies to track open data transformations, allowing consumers to verify the data using a distributed ledger, and providing a mechanism capable of publishing trusted transformed data without relying on third-party certifications. To validate the proposed approach, use cases for data transformation will be used. The consensus protocol must be capable of validating the transformations according to a predefined algorithm, the provider must be capable of publishing verifiable transformed data, and the consumer should be able to check if a dataset originated by a transformation is legit. © 2020, Springer Nature Switzerland AG.

2019

Towards an artifact to support agile teams in software analytics activities

Authors
Choma, J; Guerra, E; da Silva, TS; Zaina, LAM; Correia, FF;

Publication
The 31st International Conference on Software Engineering and Knowledge Engineering, SEKE 2019, Hotel Tivoli, Lisbon, Portugal, July 10-12, 2019.

Abstract
Software analytics supports data-driven decision making, which allows software practitioners to leverage valuable insights from software data to improve their processes and many quality aspects of the software. In this paper, we present an artifact designed from a set of patterns to support agile teams to plan and manage software analysis activities, named Software Analytics Canvas. Further, we report the study undertaken to evaluate the ease of use and the utility of our canvas from the practitioners' viewpoint, and a participatory design session carried out to collect information about possible artifact improvements. In general, subjects found the artifact useful, but some of them reported difficulties in learning and understanding how to use it. In the participatory design, they pointed out improvement points and a new layout for the canvas components. The results of both studies helped us refine the proposed artifact, improving both the terms used in each element and the layout of the blocks to make more sense for its users.