While many bug prediction algorithms have been developed by academia, they're often only tested and verified in the lab using automated means. We do not have a strong idea about whether such algorithms are useful to guide human developers. We deployed a bug prediction algorithm across Google, and found no identifiable change in developer behavior. Using our experience, we provide several characteristics that bug prediction algorithms need to meet in order to be accepted by human developers and truly change how developers evaluate their code.

The phenomenal growth of social network games in the last five years has left many game designers, game scholars, and long-time game players wondering how these games so effectively engage their audiences. Without a strong understanding of the sources of appeal of social network games, and how they relate to the appeal of past games and other human activities, it has proven difficult to interpret the phenomenon accurately or build upon its successes. In this paper we propose and employ a particular approach to this challenge, analyzing the motivational game design patterns in the popular 'Ville style of game using the lenses of behavioral economics and behavioral psychology, explaining ways these games engage and retain players. We show how such games employ strategies in central, visible ways that are also present (if perhaps harder to perceive) in games with very different mechanics and audiences. Our conclusions point to lessons for game design, game interpretation, and the design of engaging software of any type.

"Player modeling" is a loose concept. It can equally apply to everything from a predictive model of player actions resulting from machine learning to a designer's description of a player's expected reactions in response to some piece of game content. This lack of a precise terminology prevents practitioners from quickly finding introductions to applicable modeling methods or determining viable alternatives to their own techniques. We introduce a vocabulary that distinguishes between the major existing player modeling applications and techniques. Four facets together define the kind for a model: the scope of application, the purpose of use, the domain of modeled details, and the source of a model's derivation or motivation. This vocabulary allows the identification of relevant player modeling methods for particular problems and clarifies the roles that a player model can take.

At the core of video games are complex interactions leading to emergent behaviors. This complexity creates difficulties architecting components, predicting their behaviors and testing the results. The Workshop on Games and Software Engineering (GAS 2011) provides an opportunity for software engineering researchers and practitioners who work with games to come together and discuss how these two areas can be intertwined.

The FixCache algorithm, introduced in 2007, effectively identifies files or methods which are likely to contain bugs by analyzing source control repository history. However, many open questions remain about the behaviour of this algorithm. What is the variation in the hit rate over time? How long do files stay in the cache? Do buggy files tend to stay buggy, or can they be redeemed? This paper analyzes the behaviour of the FixCache algorithm on four open source projects. FixCache hit rate is found to generally increase over time for three of the four projects; file duration in cache follows a Zipf distribution; and topmost bug-fixed files go through periods of greater and lesser stability over a project's history.

Collecting large sets of quantitative video game play data can take many months or years. This delays the progress of interpreting data and drawing interesting conclusions. Mining game data from publicly accessible web services allows us to quickly retrieve quantitative results. This will allow the pace of quantitative research in video games to increase, as well as provide pointers towards maximizing the efficiency of future qualitative study.

Video games are complex, emergent systems that are difficult to design and test. This difficulty invariably leads to failures being present in the game, negatively impacting the play experience of some. We present a taxonomy of possible failures, divided into temporal and non-temporal failures. The taxonomy can guide the thinking of designers and testers alike, helping them expose bugs in the game. This will lead to games being better tested and designed, with fewer failures when released.

Generating correct specifications for real-time event-driven software systems is difficult and time-consuming. Even when such specifications have been created, they are often used to guide development rather than state properties guaranteed by the actual system. We propose a specification generator that reads execution traces and can generate invariants with real-time constraints. That specification can also offer programmers the ability to repair violated invariants at runtime. Creating fault-tolerant systems in this manner would provide software engineers guarantees about the software's high-level operation and its ability to recover from errors.

In software with emergent properties, despite the best efforts to remove faults before execution, there is a high likelihood that faults will occur during runtime. These faults can lead to unacceptable program behavior during execution, even leading to the program terminating unexpectedly. Using a distributed event-driven runtime software-fault monitor to repair faulty states creates an enforceable runtime specification. Using such an architecture can help ensure that emergent systems operate within specification, increasing the reliability of such software.