Posted Jun 9, 2016 by Greg Wilson in Research
Michael Eichberg, Ben Hermann, Mira Mezini, and Leonid Glanz: "Hidden Truths in Dead Software Paths". ESEC/FSE’15, August 2015, http://dx.doi.org/10.1145/2786805.2786865 http://www.thewhitespace.de/publications/ehmg15-deadpath.pdf .
Approaches and techniques for statically finding a multitude of issues in source code have been developed in the past. A core property of these approaches is that they are usually targeted towards finding only a very specific kind of issue and that the effort to develop such an analysis is significant. This strictly limits the number of kinds of issues that can be detected.
In this paper, we discuss a generic approach based on the detection of infeasible paths in code that can discover a wide range of code smells ranging from useless code that hinders comprehension to real bugs. Code issues are identified by calculating the difference between the control-flow graph that contains all technically possible edges and the corresponding graph recorded while performing a more precise analysis using abstract interpretation.
We have evaluated the approach using the Java Development Kit as well as the Qualitas Corpus (a curated collection of over 100 Java Applications) and were able to find thousands of issues across a wide range of categories.
If engineering is indeed "applied science", then this paper is a great example of software engineering. In it, the authors show that it’s possible to identify a wide range of problems in code by comparing the actual control flow graph (which is the set of all possible paths through the program) with the abstract interpretation flow graph (which is the set of all paths once possible data values are taken into account). To make this more concrete, the control flow graph (CFG) for:
01: x = 0 02: if x > 0: 03: x = 1
includes the statement on line 3, but the abstract interpretation flow graph (AIFG) doesn’t, because there’s no way it could ever be executed given the possible value(s) of
x . Code paths that are in the CFG but not in the AIFG signal dead code, which in turn usually signals logic errors, such as use of
and instead of
or in a logical test. The results are impressive; in particular, the authors found that a lot of code in widely-used libraries is littered with unnecessary
null checks, and that even experienced developers don’t seem to understand Boolean operators as well as they should.
Best of all, their tool is available for download under a BSD license. Most developers probably won’t have encountered the science behind it in their training—abstract interpretation is a fairly advanced topic—but they’ll appreciate the usefulness of the end product.