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

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
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
1996
资助国家:
美国
项目状态:
已结题
起止时间:
1996-04-15 至 2000-03-31

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中文摘要
翻译
这个研究计划是针对一个大规模的关键问题,但在很大程度上不受重视的问题-计算机软件的衰变。 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,并评估减少代码衰减的效果。 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,将开发代码衰减的指数(度量),以反映软件开发过程中的关键行为和管理特征。 可控(例如组织)因素的变化将改变指数,而指数又会影响关键的反应:成本、时间和质量。 通过结合适当的行为和组织因素,以及代码特征,我们将开发技术来识别相关因素,并评估其对代码衰减的影响。 该研究团队是跨学科的,包括软件工程,行为问题,组织理论,管理和统计方面的专家。 统计学--特别是测量、建模、预测和实验--作为“粘合剂”和使能技术,促进代码衰退问题的进展,并作为将传统科学的范例应用于软件工程的手段。 统计策略将被开发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,以减少成本和开发间隔,提高软件质量,并增强预测成本、间隔和质量的能力。
英文摘要
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.
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