Project ID:
RFP-2007-012
Title:
Improvement of Source Code Analysis Metrics
Summary:
The existing set of tools and metrics for measuring various aspects of source code quality often take conflicting views, and produce results that are difficult to compare or quantify in a meaningful way. For example, as we seek to understand and improve modularity, how can we assess and compare the quality and power of the metrics that measure modularity? The question is, can we develop Source Code analysis metrics and tools that are well-understood, easy to compare, and increase our confidence in the resulting measures of, e.g., modularity, security, API quality, testability?
Full Description:
There are several existing metrics and tools that attempt to answer the questions, "How modular is my source code?" or "How testable is my source code?" However, there is little concurrence across different tools on how one should most appropriately measure, e.g., modularity, security, testability.
For example, what does a "modularity index of 0.8" really mean? And how can one compare results from one metric/tool, to another?
We encourage research into the area of metric evaluation and understanding.
Questions of interest might include:
- Can we develop metrics for which we have a deep understanding, that yield useful, comparable results, across a broad range of source code?
- Can we quantify modularity, define a set of metrics, and as they evaluate a piece of code, have a better understanding of what the results mean/imply?
- How should we measure API consistency and testability?
- How should the metrics change with scaling (number of lines of code)?
- Can we develop reliable metrics that, for example, evaluate code-size and similarity of topic across code-sections, which have reduced dependency on human input? (There is a separate RFP with more emphasis related to this (automation) topic).
Constraints and other information:
IPR will stay with the University. Cisco expects customary scholarly dissemination of results, and hopes that promising results would be made available to the community without limiting licenses, royalties, or other encumbrances.
Proposal submission:
Cisco is not currently accepting proposals for this RFP.
Questions? Contact: research@cisco.com
