Verified Transformations and Hoare Logic: Beautiful Proofs for Ugly Assembly Language

Digital Processing of STEM Images

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100097752 ◽

1981 ◽

Vol 39 ◽

pp. 236-237

Author(s):

A. V. Crewe ◽

M. Ohtsuki

Keyword(s):

High Resolution ◽

Low Dose ◽

Assembly Language ◽

Processing System ◽

Principal Component ◽

Digital Processing ◽

Image Analysis System ◽

Black And White ◽

Analysis System ◽

Dose Imaging

We have assembled an image processing system for use with our high resolution STEM for the particular purpose of working with low dose images of biological specimens. The system is quite flexible, however, and can be used for a wide variety of images.The original images are stored on magnetic tape at the microscope using the digitized signals from the detectors. For low dose imaging, these are “first scan” exposures using an automatic montage system. One Nova minicomputer and one tape drive are dedicated to this task.The principal component of the image analysis system is a Lexidata 3400 frame store memory. This memory is arranged in a 640 x 512 x 16 bit configuration. Images are displayed simultaneously on two high resolution monitors, one color and one black and white. Interaction with the memory is obtained using a Nova 4 (32K) computer and a trackball and switch unit provided by Lexidata.The language used is BASIC and uses a variety of assembly language Calls, some provided by Lexidata, but the majority written by students (D. Kopf and N. Townes).

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Good programming in assembly language

IEE Proceedings E Computers and Digital Techniques ◽

10.1049/ip-e.1980.0049 ◽

1980 ◽

Vol 127 (6) ◽

pp. 241 ◽

Cited By ~ 1

Author(s):

J. Mills

Keyword(s):

Assembly Language

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Teaching assembly-language programming: a high-level approach

Software & Microsystems ◽

10.1049/sm.1983.0015 ◽

1983 ◽

Vol 2 (2) ◽

pp. 40 ◽

Cited By ~ 4

Author(s):

D. Crookes

Keyword(s):

Assembly Language ◽

Assembly Language Programming ◽

High Level

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Synthesizing Conjunctive & Disjunctive Linear Invariants by K-means++ and SVM

The International Arab Journal of Information Technology ◽

10.34028/iajit/17/6/3 ◽

2020 ◽

Vol 17 (6) ◽

pp. 847-856

Author(s):

Shengbing Ren ◽

Xiang Zhang

Keyword(s):

Software Verification ◽

State Of The Art ◽

Positive Sample ◽

Machine Learning Algorithms ◽

Support Vector ◽

Hoare Logic ◽

Excellent Performance ◽

Automated Software ◽

Inductive Invariants ◽

Linear Invariants

The problem of synthesizing adequate inductive invariants lies at the heart of automated software verification. The state-of-the-art machine learning algorithms for synthesizing invariants have gradually shown its excellent performance. However, synthesizing disjunctive invariants is a difficult task. In this paper, we propose a method k++ Support Vector Machine (SVM) integrating k-means++ and SVM to synthesize conjunctive and disjunctive invariants. At first, given a program, we start with executing the program to collect program states. Next, k++SVM adopts k-means++ to cluster the positive samples and then applies SVM to distinguish each positive sample cluster from all negative samples to synthesize the candidate invariants. Finally, a set of theories founded on Hoare logic are adopted to check whether the candidate invariants are true invariants. If the candidate invariants fail the check, we should sample more states and repeat our algorithm. The experimental results show that k++SVM is compatible with the algorithms for Intersection Of Half-space (IOH) and more efficient than the tool of Interproc. Furthermore, it is shown that our method can synthesize conjunctive and disjunctive invariants automatically

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