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A new conditional invariant detection framework (CIDF)

机译:新的条件不变检测框架(CIDF)

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摘要

Software engineering included some different process such as designing, implementing and modifying of software. All these processes are done to have fast developed software as well as reach a high quality, efficient and maintainable software. Invariants help programmer and tester to do most steps of software engineering more easily. Invariants are mostly always true but of course with a specific confidence. Since some invariants are produced in some conditions of program execution and not always, conditional invariants can show the behavior of program so much better. For producing this kind of invariants, it might use some technique of data mining such as association rule mining or using decision tree to obtain rules. So the paper will introduce a new perspective to dynamic invariant detection. Also the feasibility of conditional invariant detection is examined and a framework to extract them is proposed.
机译:软件工程包括一些不同的过程,例如软件的设计,实现和修改。所有这些过程都是为了拥有快速开发的软件以及高质量,高效且可维护的软件。不变式帮助程序员和测试人员更轻松地完成软件工程的大多数步骤。不变量通常总是正确的,但当然具有特定的信心。由于某些不变量是在程序执行的某些条件下产生的,而并非总是如此,因此条件不变量可以更好地显示程序的行为。为了产生这种不变量,它可能使用一些数据挖掘技术,例如关联规则挖掘或使用决策树来获取规则。因此,本文将为动态不变检测引入一个新的视角。还检查了条件不变检测的可行性,并提出了提取它们的框架。

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