Software Process Data Capture, Visualization and Analysis

软件过程数据捕获、可视化和分析

• 批准号: 9302739
• 负责人: Alexander Wolf
• 金额: $ 24.64万
• 依托单位: University of Colorado at Boulder
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 1993
• 资助国家: 美国
• 起止时间: 1993-06-15 至 1997-11-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9302739&HistoricalAwards=false
• 关键词: Software; Process; Data; Capture; Visualization

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.

软件过程研究涉及对软件系统的开发和维护进行系统管理和自动化的问题。软件过程研究中的关键挑战包括理解和描述现有的过程，开发和指定新的过程，以及将现有的过程演变为新的过程。本项目研究软件过程研究的两个领域中的技术，这两个领域从根本上有助于回答这些挑战：(1)捕获特征过程数据和(2)为了详细识别问题的目的而分析过程数据。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，发现指示可能的过程改进领域的系统性问题，并计算过程更改的影响。调查的起点是软件过程的基于事件的模型。事件用于根据可识别的瞬时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。集成自动和手动数据收集技术的新颖混合方法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)的信息，将这些类别内和跨这些类别的事件关联起来。定义并计算了适用于揭示异常软件过程行为的度量。使用灵活的试验台，利用各种分析工具存储和检索过程数据，作为相关性分析的基础。通过对工业中使用的几个真实软件过程的捕获和分析，结果得到了验证。