Return of CFA: call-site sensitivity can be superior to object sensitivity even for object-oriented programs

In this paper, we challenge the commonly-accepted wisdom in static analysis that object sensitivity is superior to call-site sensitivity for object-oriented programs. In static analysis of object-oriented programs, object sensitivity has been established as the dominant flavor of context sensitivity thanks to its outstanding precision. On the other hand, call-site sensitivity has been regarded as unsuitable and its use in practice has been constantly discouraged for object-oriented programs. In this paper, however, we claim that call-site sensitivity is generally a superior context abstraction because it is practically possible to transform object sensitivity into more precise call-site sensitivity. Our key insight is that the previously known superiority of object sensitivity holds only in the traditional k -limited setting, where the analysis is enforced to keep the most recent k context elements. However, it no longer holds in a recently-proposed, more general setting with context tunneling. With context tunneling, where the analysis is free to choose an arbitrary k -length subsequence of context strings, we show that call-site sensitivity can simulate object sensitivity almost completely, but not vice versa. To support the claim, we present a technique, called Obj2CFA, for transforming arbitrary context-tunneled object sensitivity into more precise, context-tunneled call-site-sensitivity. We implemented Obj2CFA in Doop and used it to derive a new call-site-sensitive analysis from a state-of-the-art object-sensitive pointer analysis. Experimental results confirm that the resulting call-site sensitivity outperforms object sensitivity in precision and scalability for real-world Java programs. Remarkably, our results show that even 1-call-site sensitivity can be more precise than the conventional 3-object-sensitive analysis.

Highly sensitive analysis of trace elements in aqueous solutions using surface-enhanced and discharge-assisted laser-induced breakdown spectroscopy

By combining surface-enhanced and discharge-assisted laser-induced breakdown spectroscopy (LIBS), the study successfully realized the quantitative analysis of trace heavy metal Cr, Cu, and Pb in aqueous solutions. We used an...

Additive particles, prosodic structure and focus sensitivity in Hungarian

The main aim of this article is to investigate the prosody-information structure interface in the analysis of the Hungarian additive particle is ‘also, too’. We present a prosodic study of narratives, collected through guided elicitation, and provide a prosodic basis for a focus-based analysis of is. Standard formal semantic approaches to the interpretation of additive particles regard additive particles as focus sensitive, hence the associate of the particle is focal and the focus interpretation (in terms of alternatives) is a significant part in its semantics. This view is considered crosslinguistically valid, although the discussion mostly concerns English. In Hungarian, the focus sensitivity of the additive particle is not directly transparent and needs more elaboration. In the relevant literature, the issue of focus marking with respect to the additive particle is has been insufficiently studied or merely stipulated. In this article, we argue for the importance of a more elaborate study of the prosody-information structure interface in the analysis of Hungarian additive particles. Accordingly, we provide data and its analysis to support our core argument and claims. Our study contributes to the overall understanding and analysis of is and to the general claims about focus marking and focus types in Hungarian. We aim to complement the standard semantic analyses by providing a prosodic analysis supporting the focus-sensitive analysis of is instead of merely stipulating an association with focus. On a more general level, we show that the various readings of additive particles can be explained by taking the prosodic patterns of the relevant constructions into account.