Efficient static checker for tainted variable attacks

TL;DR: Two static analyses are designed and tested - symbolic region and range analysis - which are combined to remove the majority of guards that prevent out-of-bounds memory accesses and generate code that is 17% faster and 9% more energy efficient than the code produced originally by this tool.

TL;DR: This paper gives an O(V2) solution to the problem of detecting tainted flow attacks by using Bodik et al.'s extended Static Single Assignment (e-SSA) program representation and shows that this approach tends to outperform the data-flow algorithm for bigger inputs.

TL;DR: This thesis presents a suite of machine learning based novel techniques to improve existing software reliability practices for helping developers find software bugs more effective and efficient, and introduces an n-gram language based static bug detection technique, i.e., Bugram, to detect new types of bugs with less false positives.

TL;DR: It is shown that not only improving the visualization technique from a technical viewpoint is needed, but also improving it from a human cognitive viewpoint should be placed at a higher priority.

TL;DR: An intermediate program representation, called the program dependence graph (PDG), that makes explicit both the data and control dependences for each operation in a program, allowing transformations to be triggered by one another and applied only to affected dependences.

TL;DR: Applications of program slicing are surveyed, ranging from its first use as a debugging technique to current applications in property verification using finite state models, and a summary of research challenges for the slicing community is discussed.

TL;DR: This text provides a comprehensive introduction both to type systems in computer science and to the basic theory of programming languages, with a variety of approaches to modeling the features of object-oriented languages.

TL;DR: In this article, the authors present new algorithms that efficiently compute static single assignment forms and control dependence graphs for arbitrary control flow graphs using the concept of {\em dominance frontiers} and give analytical and experimental evidence that these data structures are usually linear in the size of the original program.