Many automated static analysis (ASA)

Capture of surveillance data on mobile devices and rapid transfer of such data from these devices into an electronic database or data management and decision support systems promote timely data analyses and public health response during disease outbreaks. Mobile data capture is used increasingly for malaria surveillance and holds great promise for surveillance of other neglected tropical diseases. We focused on mosquito-borne dengue, with the primary aims of: 1) developing and field-testing a cell phone-based system (called Chaak) for capture of data relating to the surveillance of the mosquito immature stages, and 2) assessing, in the dengue endemic setting of Mérida, México, the cost-effectiveness of this new technology versus paper-based data collection. Chaak includes a desktop component, where a manager selects premises to be surveyed for mosquito immatures, and a cell phone component, where the surveyor receives the assigned tasks and captures the data. Data collected on the cell phone can be transferred to a central database through different modes of transmission, including near-real time where data are transferred immediately (e.g., over the Internet) or by first storing data on the cell phone for future transmission. Spatial data are handled in a novel, semantically driven, geographic information system. Compared with a pen-and-paper-based method, use of Chaak improved the accuracy and increased the speed of data transcription into an electronic database. The cost-effectiveness of using the Chaak system will depend largely on the up-front cost of purchasing cell phones and the recurring cost of data transfer over a cellular network.

No abstract

The impact of design patterns on quality attributes has been extensively evaluated in studies with different perspectives, objectives, metrics, and quality attributes, leading to contradictive and hard to compare results. The authors' objective is to explain these results by considering confounding factors, practices, metrics, or implementation issues that affect quality. Furthermore, there is a lack of research that connects design patterns evaluations to patterns development studies. Accordingly, they also aim at providing an initiate on how patterns structure and implementation can be improved, to promote software quality. To achieve their goals, conducted a systematic literature review by searching the literature for related studies. The study covers the period between years 2000 and 2018. They identified 804 candidate papers. After applying inclusion and exclusion criteria, they were left with 50 primary studies. Their results show that documentation of patterns, size of pattern classes, and the scattering degree of patterns have clear impact on quality. In case studies, researchers used different metrics applied to different modules. Controlled experiments have major design differences. Reaching consensuses on the effect of patterns requires considering influencing factors, using unified metrics, and an agreement on what modules to measure. Studying how to improve patterns modularity is recommended for future research.

No abstract