Code Delay in Legacy Software Systems: Measurement, Models, and Statistical Strategies

遗留软件系统中的代码延迟：测量、模型和统计策略

• 批准号: 9529926
• 负责人: Alan Karr
• 金额: $ 24.79万
• 依托单位: National Institute of Statistical Sciences
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 1996
• 资助国家: 美国
• 起止时间: 1996-04-15 至 2000-03-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9529926&HistoricalAwards=false
• 关键词: Code; Delay; Legacy; Software; Systems

This research program is directed toward key problems regarding a massive, but largely unappreciated problem -- decay of computer software. Three key problems to be investigated include describing code decay, identifying factors that cause code decay, and evaluating effects of reductions in code decay. The research team, which represents a partnership between AT&T and the National Institute of Statistical Sciences, will develop indices (measures) of code decay that reflect key behavioral and managerial characteristics in the software development process. Changes in controllable (for example, organizational) factors will change the indices, which in turn impact key responses: cost, time and quality. By incorporating adequate behavioral and organizational factors, as well as code characteristics, we will develop techniques to identify relevant factors and evaluate their effects on code decay. The research team is cross-disciplinary, including experts in software engineering, behavioral issues, organizational theory, management and statistics. Statistics -- especially measurement, modeling, prediction, and experimentation -- serves as the `glue` and enabling technology for progress on problems of code decay, and as the means to apply paradigms from the traditional sciences to software engineering. Statistic strategies will be developed and used to model and control the effects of design decisions, software architecture and organizational factors. The products will be the basis for management tools for achieving reductions in cost and development interval, increases in software quality and enhanced capability to predict cost, interval and quality.

该研究计划针对一个巨大但基本上未被重视的关键问题——计算机软件的衰退。 要研究的三个关键问题包括描述代码衰减、识别导致代码衰减的因素以及评估代码衰减减少的效果。 该研究团队代表 AT&T 和国家统计科学研究所之间的合作伙伴关系，将开发反映软件开发过程中关键行为和管理特征的代码衰退指数（衡量标准）。 可控（例如组织）因素的变化将改变指数，进而影响关键响应：成本、时间和质量。 通过结合足够的行为和组织因素以及代码特征，我们将开发技术来识别相关因素并评估它们对代码衰减的影响。 研究团队是跨学科的，包括软件工程、行为问题、组织理论、管理和统计学方面的专家。 统计——尤其是测量、建模、预测和实验——充当“粘合剂”和推动代码衰退问题取得进展的技术，并将传统科学的范式应用到软件工程中。 将开发统计策略并用于建模和控制设计决策、软件架构和组织因素的影响。 这些产品将成为管理工具的基础，以实现降低成本和开发周期、提高软件质量以及增强预测成本、周期和质量的能力。