1 / 49

Program Slicing for Refactoring

Program Slicing for Refactoring. Advanced SW Tools Seminar. Jan 2005 Yossi Peery. Agenda. Slicing Overview Slicing Algorithms Slicing with Inference Rules Refactoring Overview Slice Extraction Refactoring Example NATE – Slicing Based Refactoring Tool. Starter.

werner
Télécharger la présentation

Program Slicing for Refactoring

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Program Slicing for Refactoring Advanced SW Tools Seminar Jan 2005 Yossi Peery

  2. Agenda • Slicing Overview • Slicing Algorithms • Slicing with Inference Rules • Refactoring Overview • Slice Extraction Refactoring • Example • NATE – Slicing Based Refactoring Tool Yossi Peery Advanced SW Tools Seminar

  3. Starter Yossi Peery Advanced SW Tools Seminar

  4. Program Slicing History • Mark Weiser, 1981 • Experimented with programmers to show that slices are: “The mental abstraction people make when they are debugging a program” [Weiser] • Used Data Flow Equations • Ottenstein & Ottenstein – PDG, 1984 • Horowitz, Reps & Binkly – SDG, 1990 Yossi Peery Advanced SW Tools Seminar

  5. What is a Slice? • All the statements of a program that may affect the values of some variables in a set V at some point of interest p. • Slicing Criterion: C = (p , V) Yossi Peery Advanced SW Tools Seminar

  6. Slice Example A slice for the criterion (10 , {product}) Yossi Peery Advanced SW Tools Seminar

  7. What is it good for? • Debugging • Program Comprehension • Reverse Engineering • Program Testing • Measuring Program Metrics Coverage, Overlap, Clustering • Refactoring Yossi Peery Advanced SW Tools Seminar

  8. Slicing Properties • Static Slicing • Statically available information only • No assumptions made on input • Computed slice can never be accurate (minimal slice) • Problem is undecidable – reduction to the halting problem • Current static methods can only compute approximations • Result may not be usefull Yossi Peery Advanced SW Tools Seminar

  9. Slicing Properties • Dynamic Slicing • Computed on a given input • actual instead of might • Useful for applications that provide are input driven (debugging, testing) Criterion: (n=-3, 5, {sign}) Yossi Peery Advanced SW Tools Seminar

  10. Slicing Properties • Amorphous & Semantic Slicing • Allows any semantic preserving transformations • Used for program comprehension and reverse engineering Instead of: We write if (n >= 0) if (n < 0) ; sign := -1 else sign := -1 Yossi Peery Advanced SW Tools Seminar

  11. Slicing Properties • Backward Slicing • Original Slicing Method • Backward Traversal of Program Flow • Slicing starts from point p (C = (p , V)) • Examines statements that are executed before p (in run-time) • Keep statements that affect value of V at p, or execution of p. • Not only statements that appear before p Yossi Peery Advanced SW Tools Seminar

  12. Slicing Properties • Forward Slicing • Forward Traversal of Program Flow • Slicing starts from p (C = (p , V)) • Examine all statements that are executed after p • Keep statements that are affected by the values of V at p or by the execution of p • Shows downstream code that depend on a specific variable or statement • Can show the code affected by a modification to a single statement Yossi Peery Advanced SW Tools Seminar

  13. Slicing Properties • Intraprocedural Slicing • Computes slice within one procedure • Assumes worse case for function calls • Interprocedural Slicing • Compute slice over an entire program • Two ways for crossing procedure boundary • Up – going from sliced procedure into calling procedure • Down – going from sliced procedure into called procedure • Must Be Context Sensitive Yossi Peery Advanced SW Tools Seminar

  14. Slicing Algorithm • CFG – Control Flow Graph • Each program statement is a node • A directed edge will connect between any 2 nodes that represent statements with a possible control flow between them. • Special nodes: Start, Stop • Definitions - There is a directed path from I to j - Set of nodes that are influenced by i - all of the variables that are defined (modified) at statement i. - all of the variables that are referenced (used) at statement i. Yossi Peery Advanced SW Tools Seminar

  15. Slicing Algorithms Yossi Peery Advanced SW Tools Seminar

  16. Slicing Algorithms • Data Flow Equations (Weiser) • Iterative Process (Over CFG) • Compute consecutive sets of “relevant” variables for each node in the CFG using data dependencies • Control dependences are not computed explicitly • Variables of control predicates (if, while) are “indirectly relevant” if any one of the statements in their body is relevant • Start with slicing criterion: C = (p, V) • Continue until a fixed point is reached – last iteration didn’t find new relevant statements Yossi Peery Advanced SW Tools Seminar

  17. Slicing Algorithms Iteration 0: Iteration k+1: Yossi Peery Advanced SW Tools Seminar

  18. Slicing Algorithm Yossi Peery Advanced SW Tools Seminar

  19. Slicing Algorithms • Issues with algorithm • Output statements are not included in slice Solution: print(x) ≡ out = out + x , out V • Interprocedural Slicing • Solution proposed by Weiser • Can go up or down procedure calls • Actual parameters of function call are changed to call parameters (or the opposite) • Variables not in scope are removed • Is not “context sensitive” – too inaccurate Yossi Peery Advanced SW Tools Seminar

  20. Slicing Algorithms • PDG – Program Dependance Graphs • Each node represents a statement (like CFG) • Directed Edges represent: • Control Dependence (Bold Lines) – between a predicate and the statements it controls • Data Dependence (Regular Lines) – between statements modifying a variable and those that may reference it • Special “Entry” node is connected to all nodes that are not control dependant Yossi Peery Advanced SW Tools Seminar

  21. Slicing Algorithms Yossi Peery Advanced SW Tools Seminar

  22. Slicing Algorithm • Slicing with PDG • Slicing criterion is less general: C = ( p, Def(p) ∩ Ref(p) ) • Graph is computed for a single procedure • Slicing becomes a reachability problem A slice consits of all the nodes that have a directed path to the node in the slicing criterion are in the • Linear in time, after graph is calculated • Issues • Method isn’t interprocedural Yossi Peery Advanced SW Tools Seminar

  23. Slicing Algorithms • SDG – System Dependence Graph • New nodes: Call Site, Procedure Entry, Actual-in-argument, Actual-out-argument, Formal-in-parameter, Formal-out-parameter • New edges: • Call Edge – connect “call site” and “procedure entry” • Parameter-In Edge – connect “Actual-in” with “Formal-in” • Parameter-Out-Edge – connect “Actual-out” with “Formal-out” Yossi Peery Advanced SW Tools Seminar

  24. Slicing Algorithm Yossi Peery Advanced SW Tools Seminar

  25. Yossi Peery Advanced SW Tools Seminar

  26. Context Sensitivity Can not be solved by data flow equations The <add> procedure, included through the <multiply> procedure will include the call site <add(sum,i)> and consequently <sum:=0> Solved by SDG New summary edges (dotted) represent transitive dependences between “actual-in” and “actual-out” nodes. Slice is calculated in 2 passes (instead of 1): Follow all edges except “parameter-out” Follow all edges except “parameter-in” Slicing Algorithms Yossi Peery Advanced SW Tools Seminar

  27. Yossi Peery Advanced SW Tools Seminar

  28. Slicing Algorithm • SDG - Issues • Slicing remains a reachability problem • SDG of a program is complex and costly to build (time, space) • After computation, many different slices can be found using the same graph • Is not efficient for developing code • OO concepts and unstructured control flow (jump statements, exceptions) further complicate the graph Yossi Peery Advanced SW Tools Seminar

  29. Slicing with Inference Rules • Concept • Use inference rules when traversing backwards the flow of the program to determine relevant statements • Rules are applied on a specific configuration of <S,Γ,R> S – Statement or sequence of statements that have been analyized Γ – Current slicing context R – Set of statements that are relevant (so far) • Similar in nature to data flow equations method Yossi Peery Advanced SW Tools Seminar

  30. Slicing with Inference Rules • Context: • Inference Rule: • Initial Configuration: • Our Example • Final Configuration: Yossi Peery Advanced SW Tools Seminar

  31. Slicing with Inference Rules • Rule Example • Inference rules are defined so that, at each step, there is at most one rule that matches the configuration Yossi Peery Advanced SW Tools Seminar

  32. Slicing with Inference Rules • Features • Supports interprocedural slicing • Context Sensitive • Can be extended to support other language features such as: • Complex expressions • Array access • Variable declarations • Structured Jumps (break, continue) • Object-oriented slicing (scoping, polymorphism) • Aliasing Yossi Peery Advanced SW Tools Seminar

  33. Refactoring Overview • Gradually improving design of existing code • Source code transformations that, • Preserve behavior of original system • Manually or Automated • Introduced by William Opdyke, 1992 • Formally defined the reasonable behavior preservation degree expected from a refactoring tool • Formally Disciplined by Martin Fowler 2000 • Formal description of a refactoring • Catalog of refactoring techniques Yossi Peery Advanced SW Tools Seminar

  34. Refactoring Overview • Over 70 refactoring techniques can be found at: www.refactoring.com/catalog/index.html • Refactoring categories: Composing Methods, Moving features between Objects, Organizing Data, Making Method Calls Simpler • Some refactorings: Rename Method, Extract Method, Move Method, Replace Conditional with Polymorphism Yossi Peery Advanced SW Tools Seminar

  35. Refactoring Overview Yossi Peery Advanced SW Tools Seminar

  36. Slice Extraction Refactoring Yossi Peery Advanced SW Tools Seminar

  37. Slice Extraction Refactoring Yossi Peery Advanced SW Tools Seminar

  38. Slice Extraction Refactoring • Idea introduced by K. Maruyama, 2001 • Is not limited to consecutive statements (like extract method) • Allows the untangling of a single concern from a complex method • Extracted slice can be refactored to • New Method • New Object • New Aspect Yossi Peery Advanced SW Tools Seminar

  39. Slice Extraction Refactoring • Slice Extraction Refactoring Concerns • Not all of the statements in the slice can be deleted • Deleted statements are determined by re-slicing for variables in statements that were not sliced: • Preconditions & Limitations • Clean compilation • Return statement • Global-scoped variables • Input/Output statements Yossi Peery Advanced SW Tools Seminar

  40. Example – original code Yossi Peery Advanced SW Tools Seminar

  41. Example – Extract as Method Yossi Peery Advanced SW Tools Seminar

  42. Example – Extract as Object Yossi Peery Advanced SW Tools Seminar

  43. Example – Extract as Aspect Yossi Peery Advanced SW Tools Seminar

  44. Example – Extract as Aspect Yossi Peery Advanced SW Tools Seminar

  45. NATE – Slicing based Refactoring Tool • Oxford University – Programming Tools Group http://web.comlab.ox.ac.uk/oucl/research/areas/progtools/projects/nate/nate.html • Slicing based refactoring techniques for the Java programming language • Currently supports a small subset of Java (March 2004) • Extract Slice as Method Refactoring • An Eclipse Plug-in Yossi Peery Advanced SW Tools Seminar

  46. NATE – Slicing based Refactoring Tool • How is it used? • Programmer selects: • slicing criterion • Name for new extracted method • Tool performs: • Compute Slice • Check refactoring preconditions • If extraction is possible – perform transformation • Show original and transformed code in a preview dialog to the user for confirmation • User can cancel any operation Yossi Peery Advanced SW Tools Seminar

  47. NATE – Slicing based Refactoring Tool • Implementation • Uses JDT plug-in for access to the AST • Slicing is done with inference rules • The AST node of a statement is associated with a related inference rule • Intensive use of visitor pattern to visit the AST and its related rules • Each AST node can be marked as relevant or not Yossi Peery Advanced SW Tools Seminar

  48. Yossi Peery Advanced SW Tools Seminar

  49. Refernces • “Untangling: A Slice Extraction Refactoring - Ran Ettinger and Mathieu Verbaere (March 2004) • “Program Slicing for Refactoring” - Mathieu Verbaere (September 2003) • “Automated Tools for Refactoring” - Ran Ettinger (June 2003) • “Program Slicing” - Mark Weiser (1981) Yossi Peery Advanced SW Tools Seminar

More Related