Safety verification test study based on demand analysis

2020 ◽  
Author(s):  
Wei Yan ◽  
Leili Hu ◽  
Shuizhong Chen ◽  
Shiyong Guo ◽  
Baolin Du ◽  
...  
Keyword(s):  
Demand Analysis ◽  
Safety Verification ◽  
On Demand ◽  
Test Study ◽  
Verification Test

scholarly journals Optimal and Perfectly Parallel Algorithms for On-demand Data-Flow Analysis

2020 ◽  
pp. 112-140 ◽  
Author(s):  
Krishnendu Chatterjee ◽  
Amir Kafshdar Goharshady ◽  
Rasmus Ibsen-Jensen ◽  
Andreas Pavlogiannis
Keyword(s):  
Data Flow ◽  
Flow Analysis ◽  
Demand Analysis ◽  
Finite Domain ◽  
Data Flow Analysis ◽  
On Demand ◽  
Time Optimal ◽  
Speed Up ◽  
Flow Functions ◽  
Flow Graphs

AbstractInterprocedural data-flow analyses form an expressive and useful paradigm of numerous static analysis applications, such as live variables analysis, alias analysis and null pointers analysis. The most widely-used framework for interprocedural data-flow analysis is IFDS, which encompasses distributive data-flow functions over a finite domain. On-demand data-flow analyses restrict the focus of the analysis on specific program locations and data facts. This setting provides a natural split between (i) an offline (or preprocessing) phase, where the program is partially analyzed and analysis summaries are created, and (ii) an online (or query) phase, where analysis queries arrive on demand and the summaries are used to speed up answering queries.In this work, we consider on-demand IFDS analyses where the queries concern program locations of the same procedure (aka same-context queries). We exploit the fact that flow graphs of programs have low treewidth to develop faster algorithms that are space and time optimal for many common data-flow analyses, in both the preprocessing and the query phase. We also use treewidth to develop query solutions that are embarrassingly parallelizable, i.e. the total work for answering each query is split to a number of threads such that each thread performs only a constant amount of work. Finally, we implement a static analyzer based on our algorithms, and perform a series of on-demand analysis experiments on standard benchmarks. Our experimental results show a drastic speed-up of the queries after only a lightweight preprocessing phase, which significantly outperforms existing techniques.

scholarly journals Demand Driven Web Services

2010 ◽  
pp. 35-55 ◽  
Author(s):  
Zhaohao Sun ◽  
Dong Dong ◽  
John Yearwood
Keyword(s):  
Web Services ◽  
Web Service ◽  
Service Providers ◽  
Service Science ◽  
Demand Analysis ◽  
Pivotal Role ◽  
Business Service ◽  
Service Computing ◽  
On Demand ◽  
Intelligence Service

Web services are playing a pivotal role in e-business, service intelligence, and service science. Demand-driven web services are becoming important for web services and service computing. However, many fundamental issues are still ignored to some extent. For example, what is the demand theory for web services, what is a demand-driven architecture for web services and what is a demand-driven web service lifecycle remain open. This chapter addresses these issues by examining fundamentals for demand analysis in web services, and proposing a demand-driven architecture for web services. It also proposes a demand-driven web service lifecycle for the main players in web services: Service providers, service requestors and service brokers, respectively. It then provides a unified perspective on demand-driven web service lifecycles. The proposed approaches will facilitate research and development of web services, e-services, service intelligence, service science and service computing.

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