Large software systems undergo significant evolution during their lifespan, yet often individual changes are not well documented. In this work, we seek to automatically classify large changes into various categories of maintenance tasks — corrective, adaptive, perfective, feature addition, and non-functional improvement — using machine learning techniques. In a previous paper, we found that man...

In trials witnesses often slant their testimony in order to advance their own interests. To obtain truthful testimony, the law relies on cross-examination under threat of prosecution for perjury. We show that perjury law is an imperfect truth-revealing mechanism. More importantly, we develop a perfect truth-revealing mechanism. Under this mechanism the witness is sanctioned if a court eventuall...

The question is: how has the system responded to the rigid rules and controls that have been imposed from the top? Did it improve the system, or did it produce gaming and compliance roleplaying? Have system leaders just blindly gone along with this whole "blame culture" that has been nurtured by Queen's Park to deflect blame from the inner circle of connected operators? Are there any leaders wh...

Expertise of annotators has a major role in crowdsourcing based opinion aggregation models. In such frameworks, accuracy and biasness of annotators are occasionally taken as important features and based on them priority of the annotators are assigned. But instead of relying on a single feature, multiple features can be considered and separate rankings can be produced to judge the annotators pro...

Collecting human judgments for music similarity evaluation has always been a difficult and time consuming task. This paper explores the viability of Amazon Mechanical Turk (MTurk) for collecting human judgments for audio music similarity evaluation tasks. We compared the similarity judgments collected from Evalutron6000 (E6K) and MTurk using the Music Information Retrieval Evaluation eXchange 2...

Computerized generation of humor is a notoriously difficult AI problem. We develop an algorithm called Libitum that helps humans generate humor in a Mad Lib R ©, which is a popular fill-in-the-blank game. The algorithm is based on a machine learned classifier that determines whether a potential fill-in word is funny in the context of the Mad Lib story. We use Amazon Mechanical Turk to create gr...

Distributed database systems require a commit process to preserve the ACID property of transactions executed on a number of system sites. With the appearance of main memory database system, the database processing time has been reduced in the order of magnitude, since the database access does not incur any disk access at all. However, when it comes to distributed main memory database systems, t...