The paper presents a framework for automatic inferring knowledge about reasons for the appearance of anti-patterns in the program source code during its development. Experiments carried out on histories of development of few open-source java projects shown that we can efficiently detect temporal patterns, which are indicators of likely appearance of future anti-pattern. The approach presented in this paper uses expert knowledge (formal description of anti-patterns) to automatically produce extra knowledge (with machine learning algorithm) about the evolution of bad structures in the program source code. The research can be used to build scalable and adaptive tools, which warns development teams about the fact that system architecture is drifting in the wrong direction, before this is reported by typical static source code analysis tools.