1. Knowledge-oriented Maintenance at the University of Ottawa Timothy C Lethbridge KOM 2004 - Banff

2. The Knowledge-Based Reverse Engineering Group at the University of Ottawa Formed by Tim Lethbridge in 1994 Original focus was strictly knowledge-based work We still do some of that But our focus has broadened to “tools for helping people deal with complexity”

3. Project 1: Bullding a Knowledge Base to help software engineering of ObjecTime History We had built a series of knowledge management systems (CODE2, CODE4) in the 1989-1994 period We were working with Nortel to help them grapple with the complexity in their software design tools We built a KB interactively with their developers The process helped iron out key concepts Later, this tool span off as a separate company —Incorporated into Rational, and later into IBM Reference My PhD thesis: http://www.site.uottawa.ca/~tcl/thesis_html/thesis_ToC.html

4. Project 2: A lightweight knowledge base for maintainers Contained An ontology of concepts relating to a large telecom system at Mitel Basic definitions and cross references Uses Available for exploration to help new hires learn the system Hooked to ‘intelligent search’ system to help search for concepts in source code Hooked to browsing system: When browsing code, maintainers could follow links from words in comments

5. Project 2 - continued Experience building the KB: Done quickly with very little work Step 1: Scan source code comments and key documents for words and phrases Step 2: Use a multi-phase ranking/voting UI to have project team members prioritize, organize and categorize concepts Deployed: In TkSee at Mitel - used by 15-20 maintainers

6. Project 2 - continued References: Sayyad-Shirabad, J., Lethbridge, T.C. and Lyon, S, (1997, May), "A Little Knowledge Can Go a Long Way Towards Program Understanding", 5th International Workshop on Program Comprehension, Dearborn, MI, pp. 111-117 Liu, H., and Lethbridge, T.C. (2002), “Intelligent Search Methods for Software Maintenance”, Information Systems Frontiers, 4, 4, pp. 409-423.

7. Project 3: Mining a maintenance records to find relevant software entities Premise When maintaining software, maintainers are often not aware of the files, classes, methods that need to be modified We want to create an advisor that will study what you are modifying, and suggest other things that might need modifying This can be done by systematic impact analysis, but we want to try an alternative approach

8. Project 3 - continued Approach Extract all the software entities that have been modified together over several years in the system —Found in the change management system Extract a wide variety of attributes of all software entities Apply machine learning to derive a model that predicts, for any pair, whether when modifying one element, you should look at the other Results After a major PhD project, we have very good prediction tools

9. Project 3 - continued References Sayyad Shirabad, S, Lethbridge, T.C. and Matwin, S. (2004) “Mining Software the Repository of a Legacy Telephony System”, MSR 2004: International Workshop on Mining Software Repositories, in conjunction with ICSE 2004, Edinburgh Scotland, May, IEE Press Sayyad Shirabad, J., Lethbridge, T.C. Matwin, S. (2003) “Applying Data Mining to Software Maintenance Records”, proc CASCON 2003, Toronto, October, IBM, in ACM Digital Library, pp. 136- 148. Sayyad Shirabad, J, Lethbridge, T.C., Matwin, S., (2003) “Mining the Maintenance History of a Legacy Software System”, International Conference on Software Maintenance (ICSM), Amsterdam, IEEE Computer Society, pp. 95-104. Jelber Sayyad’s PhD thesis: http://www.site.uottawa.ca/~tcl/gradtheses/jsayyad/

10. Project 4 - Proposed work to remodel the UML 2 spec and metamodel in a KB Premise The UML 2.0 Spec is confusing and inconsistent Software engineers could make better use of models of they could have a more consistent and better specified modelling language and tools UML and modelling is a knowledge-rich area, ready for knowledge management Status We are initiating this work with IBM

11. What knowledge is most important to a maintainer Simple, navigable facts about their system But more than just code knowledge —Knowledge about: -The domain -The requirements -The conceptual framework -The terminology used Simplicity is key

12. How can this knowledge be best captured, and from where? Simple tools Extract terminology from documentation and the system Have software engineers rank and organize it They can do 5000 concepts in a day! We did it!

13. How can we make best use of this knowledge? In a code exploration tool

14. This presentation will be at: http://www.site.uottawa.ca/~tcl/presentations/kom- banff-lethbridge.ppt Thank-you!