Aligning Development Tools with the Way Programmers Think About Code - PowerPoint PPT Presentation

Aligning Development Tools with the Way Programmers Think About Code Changes Marat Boshernitsan et al. Presented By: James Mendek Carleton University - COMP 5900 pmendek@gmail.com October 13, 2015 James Mendek (CU) iXj: Source Transformations in Java October 13, 2015 1 / 17

Problem Definition Conceptually simple source code changes often require numerous edits that are similar but not identical, leading to errors and omissions. Most existing automated refactoring tools are counter-intuitive and difficult to use, failing to align with developers’ mental models of programming structures, or integrate well with development environments. James Mendek (CU) iXj: Source Transformations in Java October 13, 2015 2 / 17

Existing Solutions Type Examples Issues Text Tools Regular Expressions Language agnostic but dif- SED + AWK ficult to read and under- stand, or extend beyond trivial refactoring IDE Tools Find and Replace, Ignores code structure. Refactoring Features Cannot create custom transformations AST Visualization A*, TAWK, Strat- Structure based, but too ego/XT low level Edit-By-Example EBE, TELS, LAPIS, Structure captured from ex- VISUAL AWK amples, but example collec- tion effort negates automa- tion James Mendek (CU) iXj: Source Transformations in Java October 13, 2015 3 / 17

Example Solutions Figure 2 : TXL - Use an extended Figure 1 : Text substitution with sed syntax of the underlying programming treats source code as flat, structureless language to specify structured text. transformations thus improving its readability and maintainability. However, tool is complex and highly specialized James Mendek (CU) iXj: Source Transformations in Java October 13, 2015 4 / 17

Contributions of Paper 1 A program manipulation paradigm that allows modifying source code with interactively-constructed visual program transformations, bridging the gap between manipulation of source code structure and lightweight refactoring 2 Design of a visual transformation language and of the accompanying user-interaction model that combines edit-by-example, iterative refinement, and immediate feedback 3 Extending the traditional evaluative use of the Cognitive Dimensions framework to earlier design phases 4 The integration of a prototype visual transformation tool into a professional IDE (Eclipse) James Mendek (CU) iXj: Source Transformations in Java October 13, 2015 5 / 17

Research Methodology Goal is easy source code transformation generation. Target audience is experienced java developers. Three iterations of prototype design and verification based on compliance with CD framework Empiracal Study with 5 java developers Pre-study interview iXJ training session Small code editing task (controlling for transformation type) Post-study interview based on CD questionnaire tailored to programmers Assessment of study results based on same framework. James Mendek (CU) iXj: Source Transformations in Java October 13, 2015 6 / 17

Cognitive Dimensions of Notations I Offers non-indepent techniques for interface evaluation and design improvement through building a cognitive profile of a system. 6 dimensions are essential: 1 High Visibility : One must be able to observe both the pattern and the transformation through a visual representation understandable by the programmer. 2 Moderate diffuseness : The notation for specifying transformations should be easy to learn for newcomers, but not so verbose that even simple transformations need long descriptions. 3 Low error-proneness : One must be prevented from making errors wherever possible, but if an error occurs it should be easy to find and fix. James Mendek (CU) iXj: Source Transformations in Java October 13, 2015 7 / 17

Cognitive Dimensions of Notations II 4 Closeness of mapping : One must be able to intuitively map a structural tranformation to his/her conceptual understanding of a program structure. 5 Progressive Evaluation : One must be able to check the results of a transformation-in-progress by examining its effect on the entire body of source code before “committing” the transformation. 6 No premature commitment : It should be possible to manipulate patterns and transformations in any order. Any transformation must be easily reversible after it is applied James Mendek (CU) iXj: Source Transformations in Java October 13, 2015 8 / 17

Example iXj Mockups Figure 3 : Transformation rewrites Figure 4 : Mockup 2 includes calls to the removeElement() method context-sensitive interface that assists in java.util.Vector as a combination of the user with transformation patterns, calls to remove() and indexOf(). thus supposedly reducing error Presents issues with diffuseness, proneness viscosity, error-proneness, and closeness of mapping James Mendek (CU) iXj: Source Transformations in Java October 13, 2015 9 / 17

Example iXj Mockups Figure 5 : Non-sql based pattern Figure 6 : Final mockup combines description beginning to more resemble textual and visual elements. Pattern java source code, but still awkward. boxes resemble java syntax with intuitive wildcards, while transforming actions in gray (click image for demo) James Mendek (CU) iXj: Source Transformations in Java October 13, 2015 10 / 17

Example iXj Transformation (From Left to Right) James Mendek (CU) iXj: Source Transformations in Java October 13, 2015 11 / 17

iXj Notable Properties From example construction enables programmers to start with a simple transformation that applies to one location in the source code and generalize it to apply to similar code fragments. Iterative Refinement from immediate feedback of the UI means that at any point in the transformation construction process the programmer knows what source code is affected and how it will be modified. Encourages playing. Transformation pending avoids intermediate inconsistent code states by allowing previews before application. James Mendek (CU) iXj: Source Transformations in Java October 13, 2015 12 / 17

Time Metrics All this really shows is that tool fluency improved over increased exposure to the tool, which might suggest it is easy to learn. Figure 7 : Time in seconds spent by users on each of the transformation tasks. “Init” is the time spent on the initial attempt. “Fix” is the time for a subsequent correction. “Total” is total time spent for a transformation. James Mendek (CU) iXj: Source Transformations in Java October 13, 2015 13 / 17

User Performance Review Pros Users reported high visibility, low resistance to change, minimal premature commitment and moderate diffuseness allowing for easy readability of transformations. Users thankful for lack of tree structure and for flexibility of pending transformations to assist with workflow organization. Cons Users sometimes didn’t know they had introduced an error and that their final transformation was incorrect. Users reported difficulty knowing when a pattern is sufficiently generic, or how to write patterns that match targetted code fragments. Users also repeatedly clicked the wrong icon for a task, or failed to click outside of a text field to set the input. James Mendek (CU) iXj: Source Transformations in Java October 13, 2015 14 / 17

Author Observations Proposed Solutions Implement an approximate pattern-matching algorithm that will indicate which variations of the pattern structure exist in the program and which parts of the transformation can be wildcarded to affect more code fragments. Possible performance issues in a large code base? Tool Evaluation Issues Transformation tasks were too simple, small in scope, and were hand selected, limiting user tool exposure. Results cannot attest to the scalability of the visual approach to transformation tasks. James Mendek (CU) iXj: Source Transformations in Java October 13, 2015 15 / 17

Discussion Questions 1 Are there any types of tranformation that iXj cannot perform? 2 What are some ways to address the tool’s issues with insufficient wildcarding of transformation patterns? 3 How can the papers evaluation of iXj’s utility over other tools be made more convincing? 4 Do the benefits of iXj eclipse integration outweigh the limitations? Why or why not? 5 Are there any reasons to doubt the tool’s portability to languages beyond Java? 6 How can the tool’s UI be improved? Are there any important design criteria or functionality not addressed by the Cognitive Dimensions Framework? James Mendek (CU) iXj: Source Transformations in Java October 13, 2015 16 / 17

iXj Limitations James Mendek (CU) iXj: Source Transformations in Java October 13, 2015 17 / 17