Lubomir Ivanov

Formal verification of a microprocessor control

The complexity of the instruction set of modern processors often leads to faults in the microinstruction sequencing, and timing errors, which are difficult to detect with conventional simulation methods. Formal verification offers a powerful alternative for dealing with these problems. In this paper we present a mathematical model of the microcode of a transputer-like microprocessor, and demonstrate how to test for the satisfaction of desired properties and the absence of improper microinstruction sequencing. The verification is based on a recently introduced technique using the inductively defined notion of series parallel posets, which offers low time and space complexity.

Specification and formal verification of interconnect bus protocols

In this paper, we apply a formal verification framework based on partial orders to verify the timing behaviors of communication/interconnect protocols such as Handshaking and PCI. Our methodology aims to reduce the high complexity of the algorithms incorporated in first-generation verification tools.

Modeling and verification of a pipelined CPU

In this paper, we present a formal model of a pipelined version of the DLX processor, and verify the correct operation of the pipeline using a formal verification approach based series-parallel posets. We illustrate how the method can be used to detect pipeline hazards and other problems. The full verification was carried out automatically with the help of a verification tool, based on algorithms with low time- and space complexity.

Using Lexical Stress in Authorship Attribution of Historical Texts

This paper presents some early results from a comprehensive project, whose goal is to investigate the use of intonation and lexical stress in authorship attribution. We demonstrate how lexical stress patterns extracted from written text can be used to train a variety of machine learning algorithms to perform attribution of texts of unknown or disputed authorship. Specifically, we apply our methodology to a collection of 18

Examining the Thomas Paine Corpus: Automated Computer Authorship Attribution Methodology Applied to Thomas Paine’s Writings

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century American and British political writings, and demonstrate how combining lexical stress with other lexical features can significantly improve the attribution results.

Automatic generation of Chu space model expressions for verification

The paper describes the use of alliteration, by itself or in combination with other features, in training machine learning algorithms to perform attribution of texts of unknown/disputed authorship. The methodology is applied to a corpus of 18th century political writings, and used to improve the attribution accuracy.

SPPV: a new formal verification environment

Thomas Paine was one of the most widely read and influential writers in the era of Democratic Revolutions in the eighteenth and early nineteenth centuries. He was a philosopher and a political leader who affected the course of the great revolutions in America and France, and whose writings still have relevance in modern politics. It is important to clarify the body of work that Paine produced. There has been speculation as to what actually were his writings, what has been left out of collections, and what has been mistakenly added to his works. For example, Philip Foner in his once authoritative Complete Writings of Thomas Paine, includes “An Occasional Letter on the Female Sex” and remarks, “Although there is evidence to prove that this article … was not written by Paine … it has been included in the present edition” because it may represent the sentiments of Paine.1 “African Slavery in America” was left out of Eric Foner’s Thomas Paine: Collected Writings, indicating some doubt to the attribution to Paine.2 Until an accurate collected works can be established, the scholarship on Paine will remain incomplete, and the public and academia will continue to misattribute quotes and opinions to Paine without historical support. The goal of our text analysis project is to address this deficiency.