Generating Predicate Callback Summaries for the Android Framework

One of the challenges of analyzing, testing and debugging Android apps is that the potential execution orders of callbacks are missing from the apps' source code. However, bugs, vulnerabilities and refactoring transformations have been found to be related to callback sequences. Existing work on control flow analysis of Android apps have mainly focused on analyzing GUI events. GUI events, although being a key part of determining control flow of Android apps, do not offer a complete picture. Our observation is that orthogonal to GUI events, the Android API calls also play an important role in determining the order of callbacks. In the past, such control flow information has been modeled manually. This paper presents a complementary solution of constructing program paths for Android apps. We proposed a specification technique, called Predicate Callback Summary (PCS), that represents the callback control flow information (including callback sequences as well as the conditions under which the callbacks are invoked) in Android API methods and developed static analysis techniques to automatically compute and apply such summaries to construct apps' callback sequences. Our experiments show that by applying PCSs, we are able to construct Android apps' control flow graphs, including inter-callback relations, and also to detect infeasible paths involving multiple callbacks. Such control flow information can help program analysis and testing tools to report more precise results. Our detailed experimental data is available at: http://goo.gl/NBPrKsComment: 11 page

Analyzing Android applications for specifications and bugs

Android has become one of the leader operating systems for smartphones. Moreover, Android has a big community of developers with over 696500 applications on its market. However, given the complexity of the system, bugs are very common on Android applications--such as security vulnerabilities and energy bugs. Normally Android applications are written using the Java programming language. In contrast to most Java applications, Android applications does not have a single entry point (main function). In addition, these applications can use some system calls and receive events from external entities (such as the user) that affect how their control flows. Therefore, a model of the Android system must be defined in order to understand the behavior of Android applications and define how their control flows. In this thesis, two approaches to define the behavior of Android applications are studied. The first approach is an intra-component analysis that take take in account just the lifecycle of the main components in Android to define control flow of the applications. This approach is evaluated applying a specification miner for energy related specifications on 12 applications from the Android market. We were able to mine 91 specifications on all the applications and 41 of them were validated. For 50% of the applications analyzed, the analysis had less than 40% of false positives specifications. However, for the rest of the applications, the interaction between components was a important factor that increased the false positives. Therefore, the second approach is an inter-component approach that takes in account both, the lifecycle of components and interaction between components to define the control flow of Android applications. We evaluate the approach checking the percentage of code coverage on 8 applications from the Google market. The results are promising with an average coverage of 67%. In addition, we were able to identify bugs related to violations of constraints regarding intecomponent interactions

Simplified Mathematical Modeling on Person-to-Person Disease Transmission: The Coronavirus Case

In this paper, a simplified mathematical model is developed through a system of ordinary differential equations for the transmission of diseases from person to person, conditions for disease control are provided and cases are studied in which it is not possible to apply the Hurwitz criterion, the corresponding qualitative study is carried out to draw conclusions on the future evolution of the disease. Additionally, the ways in which the different diseases are transmitted are analyzed and the possibilities of epidemic development and the conditions that must be created to avoid them are studied A background of the Mathematical Modeling research group is also indicated

Developing Methods to Evaluate Phenotypic Variability in Biological Nitrification Inhibition (BNI) Capacity of \u3cem\u3eBrachiaria\u3c/em\u3e Grasses

As part of the nitrogen (N) cycle in the soil, nitrification is an oxidation process mediated by microorganisms that transform the relatively immobile ammonium (NH4+)to the water soluble nitrate (NO3-), enabling the production of nitrous oxide (N2O, a potent greenhouse gas) by denitrification as a by-product (Canfield et al. 2010). Researchers at CIAT-Colombia in collaboration with JIRCAS-Japan, reported that Brachiaria humidicola forage grasses have the ability to inhibit the nitrification process by exuding chemical compounds from its roots to the soil. A major hydrophobic compound was discovered and named brachial-actone (Subbarao et al. 2009). This capacity of Brachiaria grasses is known as biological nitrification inhibition (BNI) and it could contribute to better N use efficiency in crop-livestock systems by improving recovery of applied N while reducing NO3- leaching and N2O emission. The current methodologies for quantifying the BNI trait need further improvement to facilitate high throughput evaluation to quantify genotypic differences. In this paper, we aim to develop new (or improve the existing) phenotyping methods for this trait. Preliminary results were obtained using three different methods to quantify BNI: (1) a mass spectrometry method to quantify brachialactone; (2) a static chamber method to quantify N2O emission from soils under greenhouse conditions; and (3) an improved molecular method to quantify microbial populations by Real-Time PCR. Using these three methods we expect to score a bi-parental hybrid population (n=134) of two B. humidicola accessions differing in their BNI capacity CIAT26146 (medium to low BNI) x CIAT16888 (high BNI), in an attempt to identify QTLs associated with the BNI trait

Climate-Smart Crop-Livestock Systems for Smallholders in the Tropics: Integration of New Forage Hybrids to Intensify Agriculture and to Mitigate Climate Change through Regulation of Nitrification in Soil

It is widely recognized that less than 50% of applied nitrogen (N) fertilizer is recovered by crops, and based on current fertilizer prices the economic value of this “wasted N” globally is currently estimated as US$81 billion annually. Worse still, this wasted N has major effects on the environment (Subbarao et al. 2012). CIAT researchers and their collaborators in Japan reported a major breakthrough in managing N to benefit both agriculture and the environment (Subbarao et al. 2009). Termed Biological Nitrification Inhibition (BNI), this natural phenomenon has been the subject of long-term collaborative research that revealed the mechanism by which certain plants (and in particular the tropical pasture grass B. humidicola) naturally inhibit the conversion of N in the soil from a stable form to forms subject to leaching loss (NO3) or to the potent greenhouse gas N2O (Subbarao et al. 2012). Brachiaria humidicola which is well adapted to the low-nitrogen soils of South American savannas has shown high BNI-capacity among the tropical grasses tested (Subbarao et al. 2007). The major nitrification inhibitor in Brachiaria forage grasses is brachialactone, a cyclic diterpene (Subbarao et al. 2009). Reduction of N loss from the soil under a B. humidicola pasture has a direct and beneficial environmental effect. We hypothesize that this conservation of soil N will have an additional positive impact on a subsequent crop (e.g. maize). At present, recovery of fertilizer N and the impact on crop yield is not known. The main purpose of our inter-institutional and multi-disciplinary project, targeting small-scale farmers, is to develop the innovative approach of BNI using B. humidicola forage grass hybrids to realize sustainable economic and environmental benefits from integrated crop-livestock production systems

Influenza A Viruses from Wild Birds in Guatemala Belong to the North American Lineage

The role wild bird species play in the transmission and ecology of avian influenza virus (AIV) is well established; however, there are significant gaps in our understanding of the worldwide distribution of these viruses, specifically about the prevalence and/or significance of AIV in Central and South America. As part of an assessment of the ecology of AIV in Guatemala, we conducted active surveillance in wild birds on the Pacific and Atlantic coasts. Cloacal and tracheal swab samples taken from resident and migratory wild birds were collected from February 2007 to January 2010.1913 samples were collected and virus was detected by real time RT-PCR (rRT-PCR) in 28 swab samples from ducks (Anas discors). Virus isolation was attempted for these positive samples, and 15 isolates were obtained from the migratory duck species Blue-winged teal. The subtypes identified included H7N9, H11N2, H3N8, H5N3, H8N4, and H5N4. Phylogenetic analysis of the viral sequences revealed that AIV isolates are highly similar to viruses from the North American lineage suggesting that bird migration dictates the ecology of these viruses in the Guatemalan bird population

A communal catalogue reveals Earth’s multiscale microbial diversity

Our growing awareness of the microbial world’s importance and diversity contrasts starkly with our limited understanding of its fundamental structure. Despite recent advances in DNA sequencing, a lack of standardized protocols and common analytical frameworks impedes comparisons among studies, hindering the development of global inferences about microbial life on Earth. Here we present a meta-analysis of microbial community samples collected by hundreds of researchers for the Earth Microbiome Project. Coordinated protocols and new analytical methods, particularly the use of exact sequences instead of clustered operational taxonomic units, enable bacterial and archaeal ribosomal RNA gene sequences to be followed across multiple studies and allow us to explore patterns of diversity at an unprecedented scale. The result is both a reference database giving global context to DNA sequence data and a framework for incorporating data from future studies, fostering increasingly complete characterization of Earth’s microbial diversity