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S
Goulão, M., N. Fonte, M. Wermelinger, and F. B. Abreu, "Software Evolution Prediction Using Seasonal Time Analysis: a Comparative Study", 16th European Conference on Software Maintenance and Reengineering (CSMR 2012), Szeged, Hungary, IEEE Computer Society, 30 Mar., 2012. Abstract

http://doi.ieeecomputersociety.org/10.1109/CSMR.2012.30

goulao2012csmr.pdf

Prediction models of software change requests are useful for supporting rational and timely resource
allocation to the evolution process. In this paper we use a time series forecasting model to predict software
maintenance and evolution requests in an open source software project (Eclipse), as an example of projects with seasonal release cycles. We build an ARIMA model based on data collected from Eclipse’s change request tracking system since the project’s start. A change request may refer to defects found in the software, but also to suggested improvements in the system under scrutiny. Our model includes the identification of seasonal patterns and tendencies, and is validated through the forecast of the change requests evolution for the next 12 months. The usage of seasonal information significantly improves the estimation ability of this model, when compared to other ARIMA models found in the literature, and does so for a much longer estimation period. Being able to accurately forecast the change requests’ evolution over a fairly long time period is an important ability for enabling adequate process control in maintenance activities, and facilitates
effort estimation and timely resources allocation. The approach presented in this paper is suitable for projects with a relatively long history, as the model building process relies on historic data.

H
Ameller, D., X. Franch, C. Gómez, J. Araújo, R. B. Svensson, S. Biffl, J. Cabot, V. Cortellessa, M. Daneva, D. M. Fernández, A. Moreira, H. Muccini, A. Vallecillo, M. Wimmer, V. Amaral, H. Brunelière, L. Burgueño, M. Goulão, B. Schätz, and S. Teufl, "Handling Non-Functional Requirements in Model-Driven Development: An Ongoing Industrial Survey", 23rd International Conference on Requirements Engineering (RE'15) - RE: Next!, Ottawa, Canada, IEEE Computer Society, 24-28 August, 2015.
F
Goulão, M., and F. B. Abreu, "Formalizing Metrics for COTS", International Workshop on Models and Processess for the Evaluation of COTS Components (MPEC 2004) at ICSE 2004, Edimburgh, Scotland, IEE, pp. 37-40, 2004. Abstract

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D
Gabriel, P., M. Goulão, and V. Amaral, "Do Software Languages Engineers Evaluate their Languages?", XIII Congreso Iberoamericano en "Software Engineering" (CIbSE'2010), ISBN: 978-9978-325-10-0, Cuenca, Ecuador, Universidad del Azuay, pp. 149-162, 2010. Abstractgabrielgoulaoamaralcibse2010.pdf

Domain Speci c Languages (DSLs) can contribute to increment productivity, while reducing the required maintenance and programming expertise. We hypothesize that Software Languages Engineering (SLE) developers consistently skip, or relax, Language Evaluation. Based on the experience of engineering other types of software products, we assume that this may potentially lead to the deployment of inadequate languages. The fact that the languages already deal with concepts from the problem domain, and not the solution domain, is not enough to validate several issues at stake, such as its expressiveness, usability,
eff ectiveness, maintainability, or even the domain expert's productivity while using them. We present a systematic review on articles published in top ranked venues, from 2001 to 2008, which report DSLs' construction, to characterize the common practice. This work con rms our initial hypothesis and lays the ground for the discussion on how to include a systematic approach to DSL evaluation in the SLE process.

C
Fernandes, A. I., M. Goulão, and Armanda Rodrigues, "A Comparison of Maps Application Programming Interfaces", 16th AGILE Conference on Geographic Information Science, AGILE 2013, Leuven, Belgium, May 14-17, 2013. Abstractagile2013fernandesetalcameraready.pdf

The development of web applications that manipulate geo-referenced information is often supported by Application Programming Interfaces (APIs), allowing a fast development cycle for high quality applications. APIs can be used by programmers with different expertise levels and choosing an adequate API may
have a dramatic impact on the productivity achieved by those programmers. Our goal is to compare maps APIs with respect to their usability. We compare three different APIs: the Google Maps JavaScript API, the ArcGIS API for JavaScript, and the OpenLayers JavaScript Mapping Library. Our comparison is supported by
a set of software metrics and is performed in two orthogonal ways: the comparison of three implementations of the same system prototype, each using one of the APIs under scrutiny; the comparison of the APIs specifications. The main results of the study are related to the size of the APIs, with the Google API being significantly smaller than the others.