Software Process Data Capture, Visualization and Analysis

软件过程研究涉及软件系统的系统管理和自动化开发与维护问题。软件过程研究中的主要挑战包括理解和描述现有过程，开发和指定新过程，以及将现有过程演变为新过程。本项目研究了软件过程研究的两个领域的技术，它们从根本上有助于回答这些挑战：(1)捕获特征过程数据；(2)分析过程数据以详细识别问题。有了这样的结果，软件工程师可以获得对现有过程的基于统计的理解，揭示系统问题，指出可能的过程改进领域，并计算过程变更的影响。调查的起点是基于事件的软件过程模型。事件用于根据可识别的、瞬时的过程里程碑来描述过程的动态行为，例如调用开发工具或决定要执行的下一个活动。一种新颖的混合方法集成了自动和手动数据收集技术，记录关于基于计算机的事件（例如，工具调用）和非基于计算机的事件（例如，决策制定）的信息，在这些类别内和跨这些类别的相关事件。定义并计算适合于揭示异常软件过程行为的度量。一个灵活的测试平台，用于存储和检索各种分析工具的过程数据，作为相关性分析的基础。通过在工业中使用的几个实际软件过程的捕获和分析中采用技术来验证结果。

Software process research is concerned with the problem of systematically managing and automating the development and maintenance of software systems. Key challenges in software process research include understanding and describing existing processes, developing and specifying new processes, and evolving existing processes toward new processes. This project investigates techniques in two areas of software process research that fundamentally contribute to answering these challenges: (1) capture of characteristic process data and (2) analysis of process data for purposes of detailed problem identification. With such results, software engineers can gain a statistically-based understanding of an existing process, uncover systemic problems indicating areas for possible process improvement, and calculate the effects of changes to processes. The starting point for the investigation is an event-based model of software processes. An event is used to characterize the dynamic behavior of a process in terms of identifiable, instantaneous process milestones, such as invoking a development tool or deciding upon the next activity to be performed. A novel, hybrid approach integrating automated and manual data collection techniques records information about both computer-based events (e.g., tool invocation) and non-computer-based events (e.g., decision making), relating events within and across these categories. Metrics appropriate for revealing anomalous software process behavior are defined and calculated. A flexible testbed for storage and retrieval of process data with a variety of analysis tools is used as a basis for correlation analysis. Results are validated by employing the techniques in the capture and analysis of several real-world software processes used in industry.