33000310
When do changes induce fixes?
2817846
Extracting structural information from bug reports
In software engineering experiments, the description of bug reports is typically treated as natural language text, although it often contains stack traces, source code, and patches. Neglecting such structural elements is a loss of valuable information; structure usually leads to a better performance of machine learning approaches. In this paper, we present a tool called infoZilla that detects structural elements from bug reports with near perfect accuracy and allows us to extract them. We anticipate that infoZilla can be used to leverage data from bug reports at a different granularity level that can facilitate interesting research in the future.
7939700
Mining additions of method calls in ArgoUML
In this paper we refine the classical co-change to the addition of method calls. We use this concept to find usage patterns and to identify cross-cutting concerns for ArgoUML.
8450751
How documentation evolves over time
Good source code documentation, especially of programming interfaces, is essential for using and maintaining software components. In this paper, we present the Quasoledo tool that automatically measures the quality of documentation with respect to completeness, quantity, and readability. We applied our set of metrics to the Eclipse project, and benchmarked against the well-documented Java class library. The result of Quasoledo is a map of documentation quality in Eclipse, showing the best documentation for its core components. Additionally, we looked at the evolution of Eclipse and identified batch updates that caused jumps in documentation quality. For Eclipse, only 32.6% of all changes touched documentation.
14788283
Automatic Identification of Bug-Introducing Changes
Bug-fixes are widely used for predicting bugs or finding risky parts of software. However, a bug-fix does not contain information about the change that initially introduced a bug. Such bug-introducing changes can help identify important properties of software bugs such as correlated factors or causalities. For example, they reveal which developers or what kinds of source code changes introduce more bugs. In contrast to bug-fixes that are relatively easy to obtain, the extraction of bug-introducing changes is challenging. In this paper, we present algorithms to automatically and accurately identify bug-introducing changes. We remove false positives and false negatives by using annotation graphs, by ignoring non-semantic source code changes, and outlier fixes. Additionally, we validated that the fixes we used are true fixes by a manual inspection. Altogether, our algorithms can remove about 38%~51% of false positives and 14%~15% of false negatives compared to the previous algorithm. Finally, we show applications of bug-introducing changes that demonstrate their value for research
12356102
Object-Oriented Symbolic Derivation and Automatic Programming of Finite Elements in Mechanics
Abstract.Symbolic approaches to assist in the development of finite element formulations have been used since the late 1970s. Today, symbolic mathematical software such as Mathematica, Maple, etc., has proved to be helpful when testing formulations. In earlier work, the authors introduced a new way of integrating naturally symbolic concepts in numerical finite element codes, taking advantage of an objectoriented code organization. In this paper, we wish to prove on practical examples that the proposed approach is very attractive and promising today, leading to an alternative way of conceiving finite element codes. After presenting a state-of- the-art of symbolic approaches for finite element developments, we first give a practical application of symbolic developments (for discontinuous space-time formulations), and then examples of Computer Aided Software Engineering tools that can be introduced into such a finite element environment.
34244433
Amica: einfache, uniforme Nutzung heterogener, verteilter, dynamischer Ressourcen