Comparing Four Approaches for Technical Debt Identification

Background: Software systems accumulate technical debt (TD) when short-term goals in software development are traded for long term goals (e.g., quick-and-dirty implementation to reach a release date vs. a well-refactored implementation that supports the long term health of the project). Some forms of TD accumulate over time in the form of source code that is difficult to work with and exhibits a variety of anomalies. A number of source code analysis techniques and tools have been proposed to potentially identify the code-level debt accumulated in a system. What has not yet been studied is if using multiple tools to detect TD can lead to benefits, i.e. if different tools will flag the same or different source code components. Further, these techniques also lack investigation into the symptoms of TD “interest” that they lead to. To address this latter question, we also investigated whether TD, as identified by the source code analysis techniques, correlates with interest payments in the form of increased defect- and change-proneness. Aims: Comparing the results of different TD identification approaches to understand their commonalities and differences and to evaluate their relationship to indicators of future TD “interest”. Method: We selected four different TD identification techniques (code smells, automatic static analysis (ASA) issues, grime buildup, and modularity violations) and applied them to 13 versions of the Apache Hadoop open source software project. We collected and aggregated statistical measures to investigate whether the different techniques identified TD indicators in the same or different classes and whether those classes in turn exhibited high interest (in the form of a large number of defects and higher change proneness). Results: The outputs of the four approaches have very little overlap and are therefore pointing to different problems in the source code. Dispersed coupling and modularity violations were co-located in classes with higher defect proneness. We also observed a strong relationship between modularity violations and change proneness. Conclusions: Our main contribution is an initial overview of the TD landscape, showing that different TD techniques are loosely coupled and therefore indicate problems in different locations of the source code. Moreover, our proxy interest indicators (change- and defect-proneness) correlate with only a small subset of TD indicators

Scaling Flow Path Processes to Fluvial Landscapes: An Integrated Field and Model Assessment of Temperature and Dissolved Oxygen Dynamics in a River-Floodplain-Aquifer System

Biogeochemical cycling within river ecosystems is strongly influenced by geomorphic and hydrologic dynamics. To scale point observations of temperature and dissolved oxygen (DO) to a hydrologically complex and dynamic three-dimensional river-floodplain-aquifer system, we integrated empirical models of temperature and biotic oxygen utilization with a recently published hydrogeomorphic model. The hydrogeomorphic model simulates channel flow, floodplain inundation, and surface-subsurface water exchange on the 16 km(2) Nyack Floodplain, Middle Fork Flathead River, Montana, USA. Model results were compared to observed data sets of DO to test the hypothesis that complexity in spatiotemporal patterns of biogeochemistry emerges from a comparatively simple representation of biogeochemical processes operating within a multidimensional hydrologic system. The model explained 58% of the variance in 820 DO measurements that spanned the study site longitudinally, laterally, vertically, and across river discharge conditions and seasons. We also used model results to illustrate spatial and temporal trends of temperature and DO dynamics within the shallow alluvial aquifer, which is an extensive hyporheic zone because subsurface alluvial flow paths are recharged primarily by channel water. Our results underscore the importance of geomorphic, hydrologic, and temperature dynamics in driving river ecosystem processes, and they demonstrate how a realistic representation of a river\u27s physical template, combined with simple biogeochemical models, can explain complex patterns of solute availability

Behavioral and neurophysiological correlates of emotional face processing in borderline personality disorder: are there differences between men and women?

Emotional dysregulation is a core feature of borderline personality disorder (BPD);it is, for example, known to influence one's ability to read other people's facial expressions. We investigated behavioral and neurophysiological foundations of emotional face processing in individuals with BPD and in healthy controls, taking participants' sex into account. 62 individuals with BPD (25 men, 37 women) and 49 healthy controls (20 men, 29 women) completed an emotion classification task with faces depicting blends of angry and happy expressions while the electroencephalogram was recorded. The cortical activity (late positive potential, P3/LPP) was evaluated using source modeling. Compared to healthy controls, individuals with BPD responded slower to happy but not to angry faces;further, they showed more anger ratings in happy but not in angry faces, especially in those with high ambiguity. Men had lower anger ratings than women and responded slower to angry but not happy faces. The P3/LPP was larger in healthy controls than in individuals with BPD, and larger in women than in men;moreover, women but not men produced enlarged P3/LPP responses to angry vs. happy faces. Sex did not interact with behavioral or P3/LPP-related differences between healthy controls and individuals with BPD. Together, BPD-related alterations in behavioral and P3/LPP correlates of emotional face processing exist in both men and women, supposedly without sex-related interactions. Results point to a general 'negativity bias' in women. Source modeling is well suited to investigate effects of participant and stimulus characteristics on the P3/LPP generators

Embedding Software Engineering in Mixed Methods: Computationally Enhanced Risk Communication

Mixed methods research ameliorates many convergent research challenges within the contemporary sociotechnical landscape. We suggest the integration of software engineering in mixed methods studies is a critical step to address some of the remaining and persistent challenges. One such research challenge where software engineering is particularly well suited is in hazard preparedness—in particular, the creation of risk communication messages to mitigate or prevent harm. Computationally enhanced risk communication is convergent research that integrates software engineering and social science research for the benefit of protecting humans and infrastructure. To this end, we developed a mixed methods framework for the efficient construction of risk communication messages. We call this the Domain Agnostic Risk Communication (DARC) framework and present it here. The DARC framework formalizes connections between software engineering and social science methods. It incorporates the best available science in risk communication research and a cadre of natural language processing techniques to impart validity, reliability, and precision into resultant messages. The DARC framework is highly modular owing to the incorporation of the software engineering principles of abstraction, extensibility, and encapsulation. While the focus of this position paper is on risk communication, we encourage the incorporation of software engineering into mixed methods research and the incorporation of mixed methods more broadly into software engineering experimentation

Comparing Four Approaches for Technical Debt Identification

Background: Software systems accumulate technical debt (TD) when short-term goals in software development are traded for long term goals (e.g., quick-and-dirty implementation to reach a release date vs. a well-refactored implementation that supports the long term health of the project). Some forms of TD accumulate over time in the form of source code that is difficult to work with and exhibits a variety of anomalies. A number of source code analysis techniques and tools have been proposed to potentially identify the code-level debt accumulated in a system. What has not yet been studied is if using multiple tools to detect TD can lead to benefits, i.e. if different tools will flag the same or different source code components. Further, these techniques also lack investigation into the symptoms of TD "interest" that they lead to. To address this latter question, we also investigated whether TD, as identified by the source code analysis techniques, correlates with interest payments in the form of increased defect- and change-proneness. Aims: Comparing the results of different TD identification approaches to understand their commonalities and differences and to evaluate their relationship to indicators of future TD "interest". Method: We selected four different TD identification techniques (code smells, automatic static analysis (ASA) issues, grime buildup, and modularity violations) and applied them to 13 versions of the Apache Hadoop open source software project. We collected and aggregated statistical measures to investigate whether the different techniques identified TD indicators in the same or different classes and whether those classes in turn exhibited high interest (in the form of a large number of defects and higher change proneness). Results: The outputs of the four approaches have very little overlap and are therefore pointing to different problems in the source code. Dispersed coupling and modularity violations were co-located in classes with higher defect proneness. We also observed a strong relationship between modularity violations and change proneness. Conclusions: Our main contribution is an initial overview of the TD landscape, showing that different TD techniques are loosely coupled and therefore indicate problems in different locations of the source code. Moreover, our proxy interest indicators (change- and defect-proneness) correlate with only a small subset of TD indicator

Obesity and Respiratory Hospitalizations During Influenza Seasons in Ontario, Canada: A Cohort Study

Evidence from the 2009 H1N1 pandemic suggests that severe obesity was a risk factor for serious complications from influenza infection. Our study identifies severe obesity as a risk factor for respiratory hospitalizations during seasonal influenza epidemics

Seasonal Influenza Vaccine Effectiveness among Children Aged 6 to 59 Months in Southern China

In China the protective effect of seasonal influenza vaccine has only been assessed in controlled clinical trials and proven to be highly effective. However, the post-licensure effectiveness of influenza vaccine has not been examined. In our study all influenza cases from the 19 surveillance sites in Guangzhou were laboratory confirmed during 2009 and 2010. Controls were randomly selected from children aged 6 to 59 months in the Children's Expanded Programmed Immunization Administrative Computerized System. 2529 cases and 4539 controls were finally enrolled. After adjusting for gender, age and area of residence, the vaccine effectiveness of full vaccination was 51.79% and 57.78% in the 2009 and 2010 influenza season, respectively. Partial vaccination provided 39.38% and 35.98% protection to children aged 24 to 59 months in 2009 and 2010, respectively, and no protective effect was observed among younger children. Full vaccination is highly protective and partial vaccination is protective for older children. Influenza vaccination in general should be encouraged, and full vaccination should be particularly encouraged because its protective effect is much stronger than that of partial vaccination

Protective essential oil attenuates influenza virus infection: An in vitro study in MDCK cells

<p>Abstract</p> <p>Background</p> <p>Influenza is a significant cause of morbidity and mortality. The recent pandemic of a novel H1N1 influenza virus has stressed the importance of the search for effective treatments for this disease. Essential oils from aromatic plants have been used for a wide variety of applications, such as personal hygiene, therapeutic massage and even medical practice. In this paper, we investigate the potential role of an essential oil in antiviral activity.</p> <p>Methods</p> <p>We studied a commercial essential oil blend, On Guard™, and evaluated its ability in modulating influenza virus, A/PR8/34 (PR8), infection in Madin-Darby canine kidney (MDCK) cells. Influenza virus was first incubated with the essential oil and infectivity in MDCK cells was quantified by fluorescent focus assay (FFA). In order to determine the mechanism of effects of essential oil in viral infection inhibition, we measured hemagglutination (HA) activity, binding and internalization of untreated and oil-treated virus in MDCK cells by flow cytometry and immunofluorescence microscopy. In addition, the effect of oil treatment on viral transcription and translation were assayed by relative end-point RT-PCR and western blot analysis.</p> <p>Results</p> <p>Influenza virus infectivity was suppressed by essential oil treatment in a dose-dependent manner; the number of nascent viral particles released from MDCK cells was reduced by 90% and by 40% when virus was treated with 1:4,000 and 1:6,000 dilutions of the oil, respectively. Oil treatment of the virus also decreased direct infection of the cells as the number of infected MDCK cells decreased by 90% and 45% when virus was treated with 1:2,000 and 1:3,000 dilutions of the oil, respectively. This was not due to a decrease in HA activity, as HA was preserved despite oil treatment. In addition, oil treatment did not affect virus binding or internalization in MDCK cells. These effects did not appear to be due to cytotoxicity of the oil as MDCK cell viability was only seen with concentrations of oil that were 2 to 6 times greater than the doses that inhibited viral infectivity. RT-PCR and western blotting demonstrated that oil treatment of the virus inhibited viral NP and NS1 protein, but not mRNA expression.</p> <p>Conclusions</p> <p>An essential oil blend significantly attenuates influenza virus PR8 infectivity <it>in vitro </it>without affecting viral binding or cellular internalization in MDCK cells. Oil treated virus continued to express viral mRNAs but had minimal expression of viral proteins, suggesting that the antiviral effect may be due to inhibition of viral protein translation.</p