11:00 - 11:30

• Morpheus: Variability-Aware Refactoring in the Wild

  Today, many software systems are configurable with conditional compilation. Just like any software system, configurable systems need to be refactored in their evolution, but their inherent variability induces an additional dimension of complexity that is not addressed well by current academic and industrial refactoring engines. To improve the state of the art, we propose a variability-aware refactoring approach that relies on a canonical variability representation and recent work on variability-aware analysis. The goal is to preserve the behavior of all variants of a configurable system, without compromising general applicability and scalability. To demonstrate practicality, we developed Morpheus, a sound, variability-aware refactoring engine for C code with preprocessor directives. We applied Morpheus to three substantial real-world systems (Busy box, Open SSL, and SQ Lite) showing that it scales reasonably well, despite of its heavy reliance on satisfiability solvers. By extending a standard approach of testing refactoring engines with support for variability, we provide evidence for the correctness of the refactorings implemented.

   

  Preprint available:

Joerg Liebig; Andreas Janker; Florian Garbe; Sven Apel; Christian Lengauer

University of Passau, Germany

11:30 - 12:00

• Does Automated Refactoring Obviate Systematic Editing?

  When developers add features and fix bugs, they often make systematic edits—similar edits to multiple locations. Systematic edits may indicate that developers should instead refactor to eliminate redundancy. This paper explores this question by designing and implementing a fully automated refactoring tool called RASE, which performs clone removal. RASE (1) extracts common code guided by a systematic edit, (2) creates new types and methods as needed, (3) parameterizes differences in types, methods, variables, and expressions, and (4) inserts return objects and exit labels based on control and data flow. To our knowledge, this functionality makes RASE the most advanced refactoring tool for automated clone removal. We evaluate RASE with real-world systematic edits and compare to method based clone removal. RASE successfully performs clone removal in 30 of 56 method pairs (n=2) and 20 of 30 method groups (n≥3) with systematic edits. We find that scoping refactoring based on systematic edits (58%), rather than the entire method (33%), increases the applicability of automated clone removal. Automated refactoring is not feasible in the other 42% cases, which indicates that automated refactoring does not obviate the need for systematic editing.

   

  Preprint available:

Na Meng; Lisa Hua; Miryung Kim; Kathryn S. McKinley

The University of Texas at Austin, USA; University of California at Los Angeles, USA; Microsoft Research, USA

12:00 - 12:30

• When and Why Your Code Starts to Smell Bad

  In past and recent years, the issues related to managing technical debt received significant attention by researchers from both industry and academia. There are several factors that contribute to technical debt. One of these is represented by code bad smells, i.e., Symptoms of poor design and implementation choices. While the repercussions of smells on code quality have been empirically assessed, there is still only anecdotal evidence on when and why bad smells are introduced. To fill this gap, we conducted a large empirical study over the change history of 200 open source projects from different software ecosystems and investigated when bad smells are introduced by developers, and the circumstances and reasons behind their introduction. Our study required the development of a strategy to identify smell-introducing commits, the mining of over 0.5M commits, and the manual analysis of 9,164 of them (i.e., Those identified as smell-introducing). Our findings mostly contradict common wisdom stating that smells are being introduced during evolutionary tasks. In the light of our results, we also call for the need to develop a new generation of recommendation systems aimed at properly planning smell refactoring activities.

   

  Preprint available:

 

Michele Tufano; Fabio Palomba; Gabriele Bavota; Rocco Oliveto; Massimiliano Di Penta; Andrea De Lucia; Denys Poshyvanyk

College of William and Mary, USA; University of Salerno, Italy; University of Sannio, Italy; University of Molise, Italy