Investigating a Semantic Metrics Suite for Object-Oriented Design

1. Investigating a Semantic Metrics Suite for Object-Oriented Design Dr. Letha Etzkorn (PI) Ms. Cara Stein Dr. Glenn Cox Dr. Sampson Gholston Dr. Dawn Utley Dr. Phil Farrington The University of Alabama in Huntsville

2. A Semantic Metrics Suite for Object-Oriented Design Standard software metrics have some problems! • They are implementation dependent since they are calculated strictly from the code • They count code items; sometimes it is arguable whether the items counted accurately reflect the qualities the metrics are supposed to measure • Does # of lines of code always reflect complexity? The University of Alabama in Huntsville

3. A Semantic Metrics Suite for Object-Oriented Design Segment #1 and Segment #2 do the same thing but have very different LOC metrics: Code Segment #1: test[--cnt]-> test = val1[input_count++].counter + val2[tmp_count--]->mycount; Code Segment #2: temp = val1[input_count].counter + val2[tmp_count]->mycount; input_count++; tmp_count--; --cnt; test[cnt]->test = temp; The University of Alabama in Huntsville

4. A Semantic Metrics Suite for Object-Oriented Design Object-Oriented software metrics have some similar problems: • Including constructor or destructor functions in the calculation of the Lack of Cohesion in Methods metric can cause the metric to fail The University of Alabama in Huntsville

5. A Semantic Metrics Suite for Object-Oriented Design • These problems with software metrics all result due to the metrics being calculated on syntactic aspects of the code. • The solution is to define metrics based on semantic aspects of code (“what the code means”, the code design versus the code implementation) • Program Understanding!!! The University of Alabama in Huntsville

6. A Semantic Metrics Suite for Object-Oriented Design Program Understanding • Includes any activity that uses dynamic or static methods to reveal program properties The University of Alabama in Huntsville

7. A Semantic Metrics Suite for Object-Oriented Design Three kinds of program understanding approaches • Algorithmic approaches • Annotate programs with formal specifications • Knowledge-based Approaches • Knowledge-base is mapped to program concepts • Graph parsing approaches • Program turned into a flow graph, then matched to a knowledge-base of flow graphs The University of Alabama in Huntsville

8. A Semantic Metrics Suite for Object-Oriented Design Two kinds of knowledge-based program understanding approaches • Look at code only • Kozaczynski, Ning and Engberts; Harandi and Ning • Informal tokens only • Biggerstaff, Mitbander and Webster; Etzkorn and Davis The University of Alabama in Huntsville

9. A Semantic Metrics Suite for Object-Oriented Design Etzkorn Informal Tokens approach: • Used natural language processing and information extraction techniques • Used informal tokens: comments and identifier names • Used a knowledge-base consisting of a hierarchical semantic network • Originally implemented in the PATRicia system (Program Analysis Tool for Reuse) The University of Alabama in Huntsville

10. A Semantic Metrics Suite for Object-Oriented Design Original purpose of the PATRicia system was to identify reusable components in existing object-oriented software. Included two parts: • Was the code useful in an area of interest? • Was the code “good enough” to use? The University of Alabama in Huntsville

11. A Semantic Metrics Suite for Object-Oriented Design To answer: Was the code useful in an area of interest? • Developed the Etzkorn Informal tokens program understanding approach To answer: Was the code “good enough” to use? • Used Object-Oriented software metrics The University of Alabama in Huntsville

12. A Semantic Metrics Suite for Object-Oriented Design The PATRicia system produced: • 2 reports from informal tokens section • A list of areas, with definitions, covered by a class or class hierarchy • A description of the operation of a class in natural language • 1 report from metrics section • Values of various OO metrics for classes and class hierarchies The University of Alabama in Huntsville

13. A Semantic Metrics Suite for Object-Oriented Design Description of Operation Report: Class wxbItem: -- minimizes a window. HINT: A button that can be described by a color descriptor and a left descriptor can minimize a window. -- focuses an <object> HINT: It is possible to focus an area. -- tracks a mouse. HINT: It is possible to track a mouse that can own a button. The University of Alabama in Huntsville

14. A Semantic Metrics Suite for Object-Oriented Design The effectiveness of the PATRicia system informal tokens approach has been demonstrated for: • GUI packages • Mathematical software Using information extraction-based metrics for: • Recall • Precision • overgeneration The University of Alabama in Huntsville

15. A Semantic Metrics Suite for Object-Oriented Design • Currently have published 17 refereed articles from research related to the PATRicia system • Knowledge-based journals and conferences • Natural language journals • Software metrics/software engineering journals The University of Alabama in Huntsville

16. A Semantic Metrics Suite for Object-Oriented Design Using the PATRicia system, we: • Noticed various problems with traditional software metrics • Came to realize that knowledge-based program understanding could be used to develop new metrics independent of the syntax of the code The University of Alabama in Huntsville

17. A Semantic Metrics Suite for Object-Oriented Design The knowledge-base in the PATRicia system is: • A weighted, hierarchical semantic network • At the lowest level, based on conceptual graphs The University of Alabama in Huntsville

18. A Semantic Metrics Suite for Object-Oriented Design What is a conceptual graph? • A knowledge representation technique • Often used in natural language understanding, especially in natural language generation The University of Alabama in Huntsville

19. A Semantic Metrics Suite for Object-Oriented Design A conceptual graph example: CAT SIT MAT STAT LOC The University of Alabama in Huntsville

20. A Semantic Metrics Suite for Object-Oriented Design Conceptual graphs, concepts in conceptual graphs infer CURSOR INSERT TEXT LOC OBJ infer Interface layer—consists of keywords tagged with the part of speech (noun, adjective, verb, etc.) The University of Alabama in Huntsville

21. A Semantic Metrics Suite for Object-Oriented Design • The various semantic metrics in the semantic metrics suite are defined in terms of a conceptual graph-based knowledge-base. • The PATRicia system knowledge-base is conceptual graph-based; however, it includes an inferencing scheme that is outside the conceptual graph definition. The University of Alabama in Huntsville

22. A Semantic Metrics Suite for Object-Oriented Design • Semantic complexity metrics measure the domain complexity rather than the implementation complexity: • Semantic Class Definition Entropy (SCDE) • Class Domain Complexity (CDC) • Relative Class Domain Complexity (RCDC) • Key Class Identification (KCI) • Class Interface Complexity The University of Alabama in Huntsville

23. A Semantic Metrics Suite for Object-Oriented Design Class Domain Complexity (CDC): • CDC = Σi=1m |concept + conceptual relations| X weight • 1 + number of conceptual relations linking the current concept to another concept recognized by the class. Concepts linking to concepts in another class are not included in the count. Only outgoing conceptual relations are included in the count (to prevent counting the same conceptual relation twice) The University of Alabama in Huntsville

24. A Semantic Metrics Suite for Object-Oriented Design • Semantic Class Definition Entropy: • Based on information theory. Entropy is the measure of the amount of information. • Validated and Published in “A Semantic Entropy Metric,” Etzkorn, L., Gholston, S., Hughes. W., The Journal of Software Maintenance and Evolution, Vol. 14, 2002, pp. 293-310 The University of Alabama in Huntsville

25. A Semantic Metrics Suite for Object-Oriented Design • Semantic Class Definition Entropy (cont’d): • Amount of information in an alphabetic string • Ii = -log2 Pi • Probability of the I most frequently occurring domain related concepts or keywords • Pi = fi /N1 • fi = number of occurrences of I most frequently occurring domain related concepts or keywords • N1 = total number of non-unique domain related concepts or keywords The University of Alabama in Huntsville

26. A Semantic Metrics Suite for Object-Oriented Design • Semantic Class Definition Entropy (cont’d): • Average amount of information contributed by each domain-related concept or keyword in a class definition • H = - Σi=1n1 (Pi log2 Pi) • n1 = total number of unique domain-related concepts or keywords belonging to a class • Pi = fi /N1 The University of Alabama in Huntsville

27. A Semantic Metrics Suite for Object-Oriented Design • Semantic Class Definition Entropy (SCDE): • SCDE = - Σi=1n1 (fi /N1 log2 fi /N1 ) • n1 = total number of unique domain-related concepts or keywords belonging to a class • fi = number of occurrences of I most frequently occurring domain related concepts or keywords • N1 = total number of non-unique domain related concepts or keywords The University of Alabama in Huntsville

28. A Semantic Metrics Suite for Object-Oriented Design • Proposed Semantic Metrics were published in: • Etzkorn, Letha and Delugach, Harry, "Towards a Semantic Metrics Suite for Object-Oriented Design," Proceedings of the 34th International Conference on Technology of Object-Oriented Languages and Systems, TOOLS 34 (TOOLS USA), July 30-August 4, 2000, IEEE Computer Society Press, Los Alamitos, CA, 2000, pp. 71-80. • In this paper, the semantic metrics were validated theoretically using: • Weyucker’s criteria for metric definitions • Briand and Melo’s criteria for cohesion metrics The University of Alabama in Huntsville

29. A Semantic Metrics Suite for Object-Oriented Design • Under the NASA grant, currently extending the informal tokens portion of the PATRicia system to analyze Semantic Metrics • New tool is called SemMet The University of Alabama in Huntsville

30. A Semantic Metrics Suite for Object-Oriented Design • PATRicia system informal tokens analysis (and now SemMet) written in: • C++ • CLIPS expert system shell • Various lex parsers The University of Alabama in Huntsville

31. A Semantic Metrics Suite for Object-Oriented Design Plan to validate SemMet-based semantic metrics: • GUI/mathematical packages data • MDP data (from Mike Chapman) • Advanced Engineering Environment from MSFC The University of Alabama in Huntsville

32. A Semantic Metrics Suite for Object-Oriented Design QUESTIONS? The University of Alabama in Huntsville