Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Feature scattering is long said to be an undesirable characteristic in source code. Since scattered features introduce extensions across the code base, their maintenance requires analyzing and changing different locations in code, possibly causing ripple effects. Despite this fact, scattering often occurs in practice, either due to limitations in existing programming languages (e.g., imposition of a dominant decomposition) or time-pressure issues. In the latter case, scattering provides a simple way to support new capabilities, avoiding the upfront investment of creating modules and interfaces (when possible). Hence,  argue that scattering is not necessarily bad, provided it is kept within certain limits, or thresholds. Extracting thresholds, hover, is not a trivial task. For instance, research shows that some source-code-metric distributions are heavy-tailed, usually following por-law models. In the face of heavy-tailed distributions, reporting metrics in terms of averages and standard deviations is unreliable, although commonly done so. Thus, prior to extracting reliable thresholds for feature scattering, one must understand the shape of feature-scattering distribution. In this direction,  analyze the scattering degree of five C-pre-processor-based software families and verify whether their empirical cumulative feature-scattering distributions follow por laws. Our results show that feature scattering in the studied subject systems have characteristics of heavy-tailed distributions, with a good-fit with por laws. Hence,  raise awareness that feature scattering thresholds based on central measures may not be reliable in practice.
['Rodrigo Queiroz', 'Leonardo Teixeira Passos', 'Marco Tulio Valente', 'Sven Apel', 'Krzysztof Czarnecki']
I am writing a research paper on a idea Does feature scattering follow power-law distributions?: an investigation of five pre-processor-based systems
[{"from": "human", "value": "I am writing a research paper on a idea Does feature scattering follow power-law distributions?: an investigation of five pre-processor-based systems"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Feature scattering is long said to be an undesirable characteristic in source code. Since scattered features introduce extensions across the code base, their maintenance requires analyzing and changing different locations in code, possibly causing ripple effects. Despite this fact, scattering often occurs in practice, either due to limitations in existing programming languages (e.g., imposition of a dominant decomposition) or time-pressure issues. In the latter case, scattering provides a simple way to support new capabilities, avoiding the upfront investment of creating modules and interfaces (when possible). Hence,  argue that scattering is not necessarily bad, provided it is kept within certain limits, or thresholds. Extracting thresholds, hover, is not a trivial task. For instance, research shows that some source-code-metric distributions are heavy-tailed, usually following por-law models. In the face of heavy-tailed distributions, reporting metrics in terms of averages and standard deviations is unreliable, although commonly done so. Thus, prior to extracting reliable thresholds for feature scattering, one must understand the shape of feature-scattering distribution. In this direction,  analyze the scattering degree of five C-pre-processor-based software families and verify whether their empirical cumulative feature-scattering distributions follow por laws. Our results show that feature scattering in the studied subject systems have characteristics of heavy-tailed distributions, with a good-fit with por laws. Hence,  raise awareness that feature scattering thresholds based on central measures may not be reliable in practice."}]