By David Lo
An rising subject in software program engineering and information mining, specification mining tackles software program upkeep and reliability concerns that fee economies billions of greenbacks every year. the 1st unified reference at the topic, Mining software program requisites: Methodologies and functions describes fresh ways for mining standards of software program structures. specialists within the box illustrate tips to follow state of the art information mining and laptop studying innovations to deal with software program engineering concerns.
In the 1st set of chapters, the publication introduces a few reviews on mining finite nation machines that hire innovations, similar to grammar inference, partial order mining, resource code version checking, summary interpretation, and extra. the remainder chapters current learn on mining temporal rules/patterns, protecting concepts that come with path-aware static application analyses, light-weight rule/pattern mining, statistical research, and different attention-grabbing techniques. through the e-book, the authors talk about how you can hire dynamic research, static research, and mixtures of either to mine software program specifications.
According to the USA nationwide Institute of criteria and expertise in 2002, software program insects have fee the U.S. economic climate 59.5 billion cash a 12 months. This quantity exhibits how specification mining will help locate insects and increase software figuring out, thereby decreasing pointless monetary losses. The ebook encourages the adoption of specification mining suggestions and the assimilation of those strategies in common built-in improvement environments (IDEs).
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Additional resources for Mining software specifications : methodologies and applications
The collected traces are later filtered to distill the method calls that are relevant to the scenario and remove irrelevant ones. Based on this set of scenarios, their approach infers implied scenarios that are not present in the original set. The final set of scenarios is output and presented to the user. In , Lo and Maoz extend the initial work on mining Live Sequence Charts published in . The work introduces the concept of triggers and effects. The task is: Given a trigger, mine all significant effects.
When the monitored component executes similar tasks, we obtain similar traces, namely, traces that share the same sequence of method invocation, and Mining Finite-State Automata with Annotations 37 differ only for the values of the parameters and return values. 2 are similar. To produce models that capture the general nature of the interactions, gkTail identifies and merges sets of similar traces, and produces traces where each method is associated with a set of parameter values. The set of values associated with a method in the merged traces corresponds to the parameter values associated to the same method in the original traces.
Grama, and S. Jagannathan. Path-sensitive inference of function precedence protocols. In Proceedings of ACM/IEEE International Conference on Software Engineering, pages 240–250, 2007. K. Ramanathan, A. Grama, and S. Jagannathan. Static specification inference using predicate mining. In Proceedings of ACM Conference on Programming Language Design and Implementation, pages 123–134, 2007. K. Ramanathan, K. Sen, A. Grama, and S. Jagannathan. Protocol inference using static path profiles. In Proceedings of International Symposium on Static Analysis, pages 78–92, 2008.