GreenSource: A large-scale collection of android code, tests and energy metrics

This paper presents the GreenSource infrastructure: a large body of open source code, executable Android applications, and curated dataset containing energy code metrics. The dataset contains energy metrics obtained by both static analysing the applications' source code and by executing them with available test inputs. To automate the execution of the applications we developed the AnaDroid tool which instruments its code, compiles and executes it with test inputs in any Android device, while collecting energy metrics. GreenSource includes all Android applications included in the MUSE Java source code repository, while AnaDroid implements all Android's energy greedy features described in the literature, GreenSource aims at characterizing energy consumption in the Android ecosystem, providing both Android developers and researchers a setting to reason about energy efficient Android software development.INCT-EN - Instituto Nacional de Ciência e Tecnologia para Excitotoxicidade e Neuroproteção (UID/EEA/50014/2019)This work is financed by National Funds through the Portuguese funding agency, FCT - Fundação para a Ciencia e a Tecnologia within project: ˆ UID/EEA/50014/2019. Second author is also sponsored by FCT grant SFRH/BD/132485/2017. This work is financed by the ERDF – European Regional Development Fund through the Operational Programme for Competitiveness and Internationalisation – COMPETE 2020 Programme and by National Funds through the Portuguese funding agency, FCT, within project POCI-01-0145-FEDER016718

On the multiplicity of umbilic points

We introduce an invariant of umbilic points on surfaces in the Euclidean or Minkowski 3-space that counts the maximum number of stable umbilic points they can split up under deformations of the surfaces. We call that number the multiplicity of the umbilic point and establish its properties

Statically analyzing the energy efficiency of software product lines

Optimizing software to become (more) energy efficient is an important concern for the software industry. Although several techniques have been proposed to measure energy consumption within software engineering, little work has specifically addressed Software Product Lines (SPLs). SPLs are a widely used software development approach, where the core concept is to study the systematic development of products that can be deployed in a variable way, e.g., to include different features for different clients. The traditional approach for measuring energy consumption in SPLs is to generate and individually measure all products, which, given their large number, is impractical. We present a technique, implemented in a tool, to statically estimate the worst-case energy consumption for SPLs. The goal is to reason about energy consumption in all products of a SPL, without having to individually analyze each product. Our technique combines static analysis and worst-case prediction with energy consumption analysis, in order to analyze products in a feature-sensitive manner: a feature that is used in several products is analyzed only once, while the energy consumption is estimated once per product. This paper describes not only our previous work on worst-case prediction, for comprehensibility, but also a significant extension of such work. This extension has been realized in two different axis: firstly, we incorporated in our methodology a simulated annealing algorithm to improve our worst-case energy consumption estimation. Secondly, we evaluated our new approach in four real-world SPLs, containing a total of 99 software products. Our new results show that our technique is able to estimate the worst-case energy consumption with a mean error percentage of 17.3% and standard deviation of 11.2%.This paper acknowledges the support of the Erasmus+ Key Action 2 (Strategic partnership for higher education) project No. 2020-1-PT01-KA203-078646: SusTrainable-Promoting Sustainability as a Fundamental Driver in Software Development Training and Education

Optimal Location of Electronic Toll Gantries: The Case of a Portuguese Freeway

AbstractThis paper presents a decision supporting tool for the location of electronic toll gantries in freeways, regarding the maximization of the toll revenue. The adopted case study consists in one of the most important Portuguese freeways, with 180km of extension and a recently introduced electronic toll collection system. In the first stage of the modeling procedure, we applied a categorical binary model to set drivers’ route choice between the tolled freeway segments and the fastest non-tolled alternative paths, based on traffic data collected before and after the introduction of the toll fees. Then, we developed an optimization model to assign a limited or unlimited number of toll gantries to the freeway segments considering the generalized costs of the trips performed using the freeway and the alternative routes. The results showed that charging for all of the freeway segments may not be the best solution to increase road pricing revenue

Towards energy-aware coding practices for Android

This paper studies how the use of different coding practices when developing Android applications influence energy consumption. We consider two common Java/Android programming practices, namely string operations and (non) cached image loading, and we show the energy profile of different coding practices for doing them. With string operations, we compare the performance of the usage of the standard String class to the usage of the StringBuilder class, while with our second practice we evaluate the benefits of image caching with asynchronous loading. We externally measure energy consumption of the example applications using the Trepn profiler application by Qualcomm. Our preliminary results show that selected coding practices do significantly affect energy consumption, in the particular cases of our practice selection, this difference varies between 20% and 50%.This work is funded by the Slovak Research and Development Agency under the contract No. SK-PT2015-0037 and by the Portugal-Slovakia Cooperation FCT Project (Ref. 441), and by the ERDF – European Regional Development Fund through the Operational Programme for Competitiveness and Internationalisation - COMPETE 2020 Programme and by National Funds through the Portuguese funding agency, FCT – Fundacão para a Ciência e a Tecnologia within project POCI-01-0145- FEDER-016718

Greenspecting Android virtual keyboards

During this still increasing mobile devices proliferation age, much of human-computer interaction involves text input, and the task of typing text is provided via virtual keyboards. In a mobile setting, energy consumption is a key concern for both hardware manufacturers and software developers. Virtual keyboards are software applications, and thus, inefficient applications have a negative impact on the overall energy consumption of the underlying device. Energy consumption analysis and optimization of mobile software is a recent and active area of research. Surprisingly, there is no study analyzing the energy efficiency of the most used software keyboards and evaluating the performance advantage of its features. In this paper, we studied the energy performance of five of the most used virtual keyboards in the Android ecosystem. We measure and analyze the energy consumption in different keyboard scenarios, namely with or without using word prediction. This work presents the results of two studies: one where we instructed the keyboards to simulate the writing of a predefined input text, and another where we performed an empirical study with real users writing the same text. Our studies show that there exist relevant performance differences among the most used keyboards of the considered ecosystem, and it is possible to save nearly 18% of energy by replacing the most used keyboard in Android by the most efficient one. We also showed that is possible to save both energy and time by disabling keyboard intrinsic features and that the use of word suggestions not always compensate for energy and time.- (undefined

Long- term effects of fire and three fire-fighting chemicals on a soil-plant system.

The impacts of fire and fire-fighting chemicals (FFC) on soil properties and the soil-plant system were evaluated five years after treatment application. Unburnt soils (US) were compared with burnt soils treated with water alone (BS) or with foaming agent (BS+Fo), Firesorb polymer (BS+Fi), or ammonium polyphosphate (BS+Ap). Soils (0-2 cm depth) and foliar material (Ulex micranthus, Pterospartum tridentatum, Erica umbellata and Pinus pinaster) were analysed for total-C, total-N, δ 15N, nutrients (soil-available; plant-total), pH and inorganic-N (soils) and vegetation cover and height. No long-term effects of FFC on soil properties were found except for pH (BS+Fo > BS+Ap), inorganic-N and P (BS+Ap > other treatments). BS+Ap plants usually showed higher values of δ 15N, N, P and Na, but less K. Soil coverage by Pterospartum and Ulex was higher in BS+Ap than in other treatments, while the opposite was observed for Erica; shrubs were always taller in BS+Ap. After 3 years of growth, the size of pine seedlings followed the order BS+Ap > US > other treatments. Foliar N and P, scrub regeneration and growth of pines showed the long-term fertilizing effect of ammonium polyphosphate, although the second highest pine mortality was found in the BS+Ap treatment. The foaming agent did not affect vegetation cover, and Firesorb had no noticeable effect on shrubs but the highest pine mortality.Peer reviewe