Structered Information States

Update semantics models the increase of information as the elimination of epistemic possibilities in an information state. (Stalnaker 1979, Veltman 1996) Partition semantics of questions models a question as an equivalence relation over the epistemic possibilities in an information state. Each alternative class corresponds to one of the exhaustive answers to the question. (Groenendijk & Stokhof 1984) The combination, an update semantics for questions (USQ) models a query as a change to the information-structure of an information state. (Jager 1996) Each information state is structured by one or more issues: salient questions in need of an answer

Methodology

* Perhaps the overriding question of this research iswhether domain analysis can help in the reverse engineering process at all. Our case studies indicate thatthis is so, but more work needs to be done. * Corollary to this is the question of how best to makeuse of the domain knowledge obtained. For example, even if we imagine existing, complete, well-organizeddescriptions for each of the domains related to an application program, it is not clear how best to com-bine them to understand a program. Which one should we start with? How do we coordinate a search for mul-tiple expected constructs derived from several domains? * A subsidiary methodological issue concerns knowledge of the domain learned while examining a pro-gram. We would like domain descriptions to grow and become more complete over time, but domain descrip-tions need to be definitive, and the reverse engineer need not be a knowledge engineer nor have sufficientexpertise to judge the accuracy, relevance, and placement of the new information in the domain description. Tools * They not only include a lot of information, but theinformation is highly interrelated. The question the

Summer USENIX Conference,

Ficus is a flexible replication facility with optimistic concurrency control designed to span a wide range of scales and network environments. Optimistic concurrency control provides rapid local access and high availability of files for update in the face of disconnection, at the cost of occasional conflicts that are only discovered when the system is reconnected. Ficus reliably detects all possible conflicts. Many conflicts can be automatically resolved by recognizing the file type and understanding the file's semantics. This paper describes experiences with conflicts and automatic conflict resolution in Ficus. It presents data on the frequency and character of conflicts in our environment. This paper also describes how semantically knowledgeable resolvers are designed and implemented, and discusses our experiences with their strengths and limitations. We conclude from our experience that optimistic concurrency works well in at least one realistic environment, conflicts are rare, and a large proportion of those conflicts that do occur can be automatically solved without human intervention

URN urn:nbn:de:kobv:517-opus-37387

zur Erlangung des akademischen Grades ”doctor rerum naturalium“ (Dr. rer. nat.) in der Wissenschaftsdisziplin Astrophysik eingereicht an de