Presented by: Ashgan Fararooy Referenced Papers and Related Work on:

Possible Related Papers  Automatic Inference of Structural Changes for Matching Across Program Versions  An Approach to Software Evolution Based on Semantic Change  Understanding source code evolution using abstract syntax tree matching  Recomposition - Coordinating a Web of Software Dependencies  Identifying the Semantic and Textual Differences Between Two Versions of The Program  Visualizing and Querying Software Structures

Miryung Kim, David Notkin, Dan Grossman

Abstract  Goal: Mapping code elements in one version of a program to corresponding code elements in another version  A fundamental building block for many software engineering tools  Tools that match code elements or identify structural changes (refactorings and API changes): Version merging tools Regression testing tools Profile propagation tools

Abstract  Two important limitations of such tools Having difficulty disambiguating among many potential matches or refactoring candidates Hard to analyze their outcome due to an unstructured representation of results  Proposed approach to overcome these limitations: Represent structural changes as a set of high-level change rules Automatically infer likely change rules and determines method-level matches based on the rules

Motivation  Interest in mining software repositories is demanding more effective and systematic matching techniques  The unstructured, usually lengthy, list of matches or refactorings may prevent the result of existing tools from being broadly used in mining software repository research

Background  To match code elements, the differences between two programs must be identified  Computing semantic differences is undecidable  Tools typically approximate matching via syntactic similarity  Existing refactoring reconstruction tools look for code changes that match a predefined set of refactoring patterns  Problem: either too many refactoring candidates or no candidates

Change Rules  Question: “Given two versions of a program, what changes occurred with respect to a particular vocabulary of changes?”  A change vocabulary characterizes the applications for which the matching results can be used  For example, “diff” defines a change vocabulary in terms of delete, add, and move line

Change Rules  The paper introduces a change vocabulary with the goal of representing groups of related homogeneous changes precisely  The core of their change vocabulary is a change rule consisting of a quantifier and a scope to which a low-level transformation applies  “For all x in (scope − exceptions),t(x),” where t is a transformation, scope is a set of code elements, and exceptions is a subset of scope  Their change vocabulary describes structural changes at or above the level of a method header

Change Rules Transformation Samples:

Change Rules Change Rule Samples:  All methods whose class name either includes Plot or JThermometer changed their package name from chart to chart.plot:

Change Rules Change Rule Samples:  All methods that match the chart.*Plot.get*Range() pattern take an additional ValueAxis argument, except the getVerticalRange method in the MarkerPlot class:

Rule-based Matching  The paper defines a matching between two versions of a program by a set of change rules  The scope of one rule may overlap with the scope of another rule as some methods undergo more than one transformation  The inference algorithm ensures that it infers a set of rules such that the application order of rules does not matter  The methods that are not matched by any rules are deleted or added methods

Applications of Change Rules  Bug Finding  Assisted Documentation  API Evolution Analysis  API Update  Identifying Related Changes

Evaluation & Conclusion  By applying their tool to several open source projects, the authors show that it identifies matches that are difficult to find using other approaches  They also show their approach produces more concise results than other approaches  They claim their approach is the first to automatically infer structural changes and represent them concisely as a set of rules

Rebecca E. Grinter

Abstract  Revisiting the concept of "recomposition”: All the work that development organizations do to make sure that their product fits together and into a broader environment of other technologies  Technologies, such as Configuration Management (CM) systems, can ameliorate some of a software development team’s need to engage in recomposition  Technological solutions do not scale to address other kinds of recomposition needs

Summary  The paper focuses on various organizational responses to the need for recomposition  Describes how those responses are manifested in the day-to-day communications and responsibilities of individuals throughout the organization  Highlights how changes in an organization complicate recomposition

Conclusion The paper concludes with a discussion of three features of software development work that are revealed by recomposition: The affects of environmental disturbances on development work The types of dependencies that require recomposition The images of organizations required to manage the recomposition