Software source code authorship analysis has become an important area in recent years with promising applications in both the legal sector (such as proof of ownership and software forensics) and the education sector (such as plagiarism detection and assessing style). Authorship analysis encompasses the sub-areas of author discrimination, author characterization, and similarity detection (also referred to as plagiarism detection). While a large number of metrics have been proposed for this task, many borrowed or adapted from the area of computational linguistics, there is a difficulty with capturing certain types of information in terms of quantitative measurement. Here it is proposed that existing numerical metrics should be supplemented with fuzzy-logic linguistic variables to capture more subjective elements of authorship, such as the degree to which comments match the actual source code's behavior. These variables avoid the need for complex and subjective rules, replacing these with...

Software reusability is an important and difficult problem in general, and this is in particular true for graph algorithms. The usual way to address reusability of graph algorithms is to provide a standard--setting library of data structures (incl. various kinds of graphs), on which graph algorithms may be implemented. In this working paper, we discuss the disadvantages to this approach, and we propose a couple of domain design patterns to overcome these disadvantages. To apply design patterns, we shift the focus from data structures as the primary units of reuse to algorithms themselves. So far, our concept is highly immature, and so is this paper. In fact, this paper merely reflects the state of our discussion and is intended to serve as a base for further dicussions. We are currently implementing a case study (maximum flow problem) in C++ to evaluate our ideas empirically. 1 Introduction Efficiency vs. reusability. Besides mere correctness, there are several design criteria for go...