Mined-knowledge driven software quality monitoring and diagnosis environment

本研究的目的是设计一个决策支持环境的软件开发人员和维护人员在一个组织中，以使他们能够监控系统的结构和行为方面，并提供建议，警报和警告方面保持特定的软件质量。建议的环境利用现代技术来指定和合成可定制的决策流程图作为指导模型，编码的最佳实践开发的组织或建立在软件维护文献。然后执行指南模型，以交互方式将决策流从决策流图的根节点引导到叶节点，在叶节点处做出决策并通知用户。在决策流图的每个节点处，可以向指南模型提供各种类型的信息。这些类型的信息被分类为“系统信息”，包括系统的静态、动态或设计相关的数据和关系，或者被分类为“挖掘的知识”，以模式和趋势的形式，包括：关联规则、执行跟踪模式、概括和聚类，它们是通过数据挖掘算法从“系统信息”中提取的。然后，指南模型提供不同类型的建议或警报，以及决策流程图中可能的后续步骤列表，供用户选择。指南模型可以指定不同的软件维护活动，如：纠正，完善，自适应，或预防性操作，确保健康的软件系统资产的各个组织在其开发和发展阶段。拟议的环境的主要特点包括纳入挖掘的知识，确保先进的方法，以及定制和易用性，确保通过软件维护的组织在不同的应用领域。

This research aims at devising a decision support environment for software developers and maintainers in an organization, in order to enable them to monitor the structural and behavioral aspects of the system and to provide recommendations, alerts, and warnings with regard to maintaining specific software qualities. The proposed environment takes advantage of modern technologies to specify and synthesize customizable decision-flow diagrams as guideline models that encode the best practices developed in the organization or  established in the software maintenance literature. The guideline model is then executed to interactively direct the flow of decision from the root node of the decision-flow diagram to a leaf node, where a decision is made and the user is notified.At each node of the decision-flow diagram, various types of information can be supplied to the guideline model. These types of information are categorized as either "system information", including system's static, dynamic, or design related data and relations, or as "mined knowledge", in the form of patterns and trends, including: association rules, execution trace patterns, generalizations, and clusters, that are extracted from the "system information" by the means of data mining algorithms. The guideline model then providesdifferent types of recommendations or alerts, as well as a list of possible next steps in the decision-flow diagram for the user to choose from. The guideline models can specify different software maintenance activities such as: corrective, perfective, adaptive, or preventive operations that ensure a healthy software system asset for the respective organization throughout its development and evolution stages. The key characteristics of the proposed environment include the incorporation of mined knowledge that ensures sophistication of the approach, as well as customization and ease of use that ensures adoption by the software maintainers of the organizations in different application domains.