求助:翻译
这是一个项目的软件开发文档的一部分,请大家帮我翻译一下,尽量完整一些: Connection to Organizational Process Improvement: Process Capability DataBase (PCDB) and the Office of Cost Estimation (OCE)
1. Division policies require submission of historical project data; these are mandated to be yearly at a minimum, or coincident with major project events. From Tactical Systems VP: “…the frequency shall be consistent with major contracted deliveries to the customer…”
2. Project PCDB submissions are made to the OCE, which ensures correct inputs, and provides assistance with developing submissions.
3. The submissions consist of project descriptive information, product descriptions (e.g., SLOC counts in the case of software), and effort data from the cost accounting systems which is laid out against a standard Work Breakdown Structure for ease of use.
a) Expanded organizational collection of engineering metrics (e.g., defects, requirements, performance measures, …) from projects introduced in 2002 for process improvement purposes. (Projects have collected these “forever.”)
4. Projects and Proposals have a responsibility to utilize relevant historical PCDB & OCE data in developing estimates. The data forms quantifiable backup data for proposal estimation. This benefits both customer and contactor.
Final Thoughts on Success
1. Multi-faceted attention to customers/users/ stakeholders requirements and needs
2. Evolutionary software development process
a) Excellent match for aggressive schedule and ever-evolving requirements, ports, embeddings, …
b) Some early steps streamlined based on cost/benefit trade-offs
3. Rigorous 2-level software CM processes
4. Continuous attention to handling and understanding defects (at many levels)
5. Long-time collection and analysis of defect metrics (among many others)
a) for identification of problem areas before they become severe
b) for understanding causes of problems
c) for understanding and presenting accurate status on quality
d) for contributing to calibrating TRW organizational process capability baselines and predictive models
e) to capitalize on project experience for prediction purposes