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SEVERITY BASED CODE OPTIMIZATION : A DATA MINING APPROACH

机译:基于严重度的代码优化:一种数据挖掘方法

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Billions of lines of code are currently running in Legacy systems, mainly running machine critical systems. Large organizations and as well as small organizations extensively rely on IT infrastructure as the backbone. The dependability on legacy Software systems to meet current demanding requirements is a major challenge to any IT profession. One of the top priority of any IT manager is to maintain the existing legacy system and optimize modules where required. Various techniques have been developed to determine the complexity of the modules as well as protocols have developed to assess the severity of a software problem. In this paper, it is proposed to study data mining algorithms in a multiclass scenario based on the severity of the error in the module.
机译:Legacy系统中目前正在运行数十亿行代码,主要是运行机器关键系统。大型组织和小型组织都广泛依赖IT基础架构作为骨干。依靠传统软件系统满足当前苛刻要求的可靠性是任何IT专业人员面临的主要挑战。任何IT经理的首要任务之一就是维护现有的旧系统并在需要时优化模块。已经开发出各种技术来确定模块的复杂性,并且已经开发出协议来评估软件问题的严重性。本文提出了根据模块中错误的严重性来研究多类场景中的数据挖掘算法。

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