As a guest user you are not logged in or recognized by your IP address. You have
access to the Front Matter, Abstracts, Author Index, Subject Index and the full
text of Open Access publications.
Escape analysis is the process of discovering boundaries of dynamically allocated objects in programming languages. For object-oriented languages such as C++ and Java, this analysis leads to an understanding of which program objects interact directly, as well as what objects hold references to other objects. Such information can be used to help verify the correctness of an implementation with respect to its design, or provide information to a run-time system about which objects can be allocated on the stack (because they do not “escape” the method in which they are declared). For existing object-oriented languages, this analysis is typically made difficult by aliasing endemic to the language, and is further complicated by inheritance and polymorphism. In contrast, the occam-π programming language is a process-oriented language, with systems built from layered networks of communicating concurrent processes. The language has a strong relationship with the CSP process algebra, that can be used to reason formally about the correctness of occam-π programs. This paper presents early work on a compositional escape analysis technique for mobiles in the occam-π programming language, in a style not dissimilar to existing CSP analyses. The primary aim is to discover the boundaries of mobiles within the communication graph, and to determine whether or not they escape any particular process or network of processes. The technique is demonstrated by analysing some typical occam-π processes and networks, giving a formal understanding of their mobile escape behaviour.
This website uses cookies
We use cookies to provide you with the best possible experience. They also allow us to analyze user behavior in order to constantly improve the website for you. Info about the privacy policy of IOS Press.
This website uses cookies
We use cookies to provide you with the best possible experience. They also allow us to analyze user behavior in order to constantly improve the website for you. Info about the privacy policy of IOS Press.