People can exhibit their status by the consumption of particular goods or experiential purchases; this is known as “conspicuous consumption”; the practice is widespread and explains the market characteristics of a whole class of goods, Veblen goods, demand for which increase in tandem with their price. The value of such positional goods lies in their distribution among the population—the rarer they are, the more desirable they become. At the same time, higher income, often associated with higher status, has been studied in its relation to unethical behavior. Here we present research that shows how a particular Veblen good, illicit behavior, and wealth, combine to produce the display of illegality as a status symbol. We gathered evidence at a large, country-level, scale of a particular form of consumption of an illictly acquired good for status purposes. We show that in Greece, a developed middle-income country, where authorities cannot issue custom vanity license plates, people acquire distinguishing plate numbers that act as vanity plate surrogates. We found that such license plates are more common in cars with bigger engines and in luxury brands, and are therefore associated with higher value vehicles. This cannot be explained under the lawful procedures for allocating license plates and must therefore be the result of illegal activities, such as graft. This suggests a pattern of “conspicuous corruption”, where individuals break the law and use their gains as status symbols, knowing that the symbols hint at rule-breaking, as long as the unlawful practice cannot be incontestably established.

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A model regarding the lifetime of individual source code lines or tokens can estimate maintenance effort, guide preventive maintenance, and, more broadly, identify factors that can improve the efficiency of software development. We present methods and tools that allow tracking of each line’s or token’s birth and death. Through them, we analyze 3.3 billion source code element lifetime events in 89 revision control repositories. Statistical analysis shows that code lines are durable, with a median lifespan of about 2.4 years, and that young lines are more likely to be modified or deleted, following a Weibull distribution with the associated hazard rate decreasing over time. This behavior appears to be independent from specific characteristics of lines or tokens, as we could not determine factors that influence significantly their longevity across projects. The programing language, and developer tenure and experience were not found to be significantly correlated with line or token longevity, while project size and project age showed only a slight correlation.

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We examine the use of the Java exception types in the Android platform’s Application Programming Interface (API) reference documentation and their impact on the stability of Android applications. We develop a method that automatically assesses an API’s quality regarding the exceptions listed in the API’s documentation. We statically analyze ten versions of the Android platform’s API (14–23) and 3,539 Android applications to determine inconsistencies between exceptions that analysis can find in the source code and exceptions that are documented. We cross-check the analysis of the Android platform’s API and applications with crash data from 901,274 application execution failures (crashes). We discover that almost 10% of the undocumented exceptions that static analysis can find in the Android platform’s API source code manifest themselves in crashes. Additionally, we observe that 38% of the undocumented exceptions that developers use in their client applications to handle API methods also manifest themselves in crashes. These findings argue for documenting known might-thrown exceptions that lead to execution failures. However, a randomized controlled trial we run shows that relevant documentation improvements are ineffective and that making such exceptions checked is a more effective way for improving applications’ stability.@en

Motivation: Even though many studies examine the energy efficiency of hardware and embedded systems, those that investigate the energy consumption of software applications are still limited, and mostly focused on mobile applications. As modern applications become even more complex and heterogeneous a need arises for methods that can accurately assess their energy consumption.

Goal: Measure the energy consumption and run-time performance of commonly used programming tasks implemented in different programming languages and executed on a variety of platforms to help developers to choose appropriate implementation platforms.

Method: Obtain measurements to calculate the Energy Delay Product, a weighted function that takes into account a task’s energy consumption and run-time performance. We perform our tests by calculating the Energy Delay Product of 25 programming tasks, found in the Rosetta Code Repository, which are implemented in 14 programming languages and run on three different computer platforms, a server, a laptop, and an embedded system.

Results: Compiled programming languages are outperforming the interpreted ones for most, but not for all tasks. C, C#, and JavaScript are on average the best performing compiled, semi-compiled, and interpreted programming languages for the Energy Delay Product, and Rust appears to be well-placed for i/o-intensive operations, such as file handling. We also find that a good behaviour, energywise, can be the result of clever optimizations and design choices in seemingly unexpected programming languages.@en