Presented by Rebekah Leslie.

The existing implementation of DDT uses a depth-first search algorithm to drive the exploration of new paths for testing. This algorithm provides full coverage of the program under test, but is limited by the fact that the number of paths increases exponentially with the size of the program. By employing the control-flow graph information of the program under test, we can direct the testing process towards program paths that contain unvisited points and therefore obtain full branch coverage in a smaller number of tests than would be required by the original depth-first search algorithm. We will present two uses of control-flow graph information in DDT. The first use is a refinement of depth-first search where control-flow graph information is used to prune the search space to eliminate unnecessary tests. The second use is in the context of a prioritized work-queue that forms the basis for a variety of sophisticated search algorithms that exploit different heuristics.

Presented by Aaron Tomb.

Many tools exist to automate the search for defects in software source code. However, many of these tools have not been widely applied, partly because they tend to work least well in the most common case: on large software systems that have only partial specifications describing correct behavior --- often a collection of independent assertions sprinkled throughout the program.

Recent research has suggested that a large class of software bugs fall into the category of inconsistencies, or cases where two pieces of program code make incompatible assumptions. Existing approaches to inconsistency detection have used intentionally unsound techniques aimed at bug-finding rather than verification. In this dissertation, we describe an inconsistency detection analysis that subsumes previous work and is instead based on the foundation of the weakest precondition calculus.

We have applied our analysis to a large body of widely-used open-source software, and found a number of bugs.

Come join us for Pythonic talks!

This month, we're proud to present talks covering both advanced and beginner-friendly topics.

Thanks to our speakers Emily Cain and Allan Feldman!

Emily Cain Purrsistent Debugging

One of the most important skills for a software developer is debugging. How do we approach debugging? What tools do we learn? What skills are involved, and what habits do we pick up as we learn them? How do we teach and communicate about these skills?

In this talk, programmer, writer, and technology educator Emily Cain will explore these issues. Beginners will learn about key tools like PDB and the browser's debugger, as well as learning to inspect code and function outputs to look for patterns. Meanwhile, more advanced coders will learn techniques for understanding and discussing these skills, and gain a better perspective on how to help their more junior colleagues advance beyond the "Googling StackOverflow" stage of debugging. And everyone will get to look at adorable pictures of a particularly dedicated cat as she "debugs" her way into an infinite supply of snacks.

Allan Feldman Reference cycles: what are they, how to detect them, and how to fix them

Let's talk about garbage! Ever had a long-running Python process whose memory usage seemed to grow over time? In this talk, Allan Feldman, Senior Software Engineer at New Relic, dives into Python internals to show how reference cycles can happen, how to find them in your code, and how to fix a cycle once found. You'll never look at garbage the same way again!

We'll also open things up for some 3-5 minute Lightning Talks afterward. Are you working on something cool or did you discover a new tool or package? Get up and talk about it!

Submit proposals for talks here: http://bit.ly/portland-python-proposals

All speakers and attendees must follow our code of conduct: http://www.meetup.com/pdxpython/pages/Code_of_Conduct/

Join us after the meetup at Bailey's taproom at 213 SW Broadway to continue the discussion over a beverage.