The Experts below are selected from a list of 423606 Experts worldwide ranked by ideXlab platform
Gerald Lüttgen - One of the best experts on this subject based on the ideXlab platform.
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Symbolic object Code Analysis
International Journal on Software Tools for Technology Transfer, 2014Co-Authors: Jan Tobias Mühlberg, Gerald LüttgenAbstract:Software model checkers quickly reach their limits when being applied to verifying pointer safety properties in source Code that includes function pointers and inlined assembly. This article introduces a novel technique for checking pointer safety violations, called symbolic object Code Analysis (SOCA), which is based on bounded symbolic execution, incorporates path-sensitive slicing, and employs the SMT solver Yices as its execution and verification engine. Extensive experimental results of a prototypic SOCA Verifier, using the Verisec suite and almost 10,000 Linux device driver functions as benchmarks, show that SOCA performs competitively to modern source-Code model checkers, scales well when applied to real operating systems Code and pointer safety issues, and effectively explores niches of pointer-complex software that current software verifiers do not reach.
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SPIN - Symbolic object Code Analysis
Model Checking Software, 2010Co-Authors: Jan Tobias Mühlberg, Gerald LüttgenAbstract:Current software model checkers quickly reach their limits when being applied to verifying pointer safety properties in source Code that includes function pointers and inlined assembly. This paper introduces an alternative technique for checking pointer safety violations, called Symbolic Object Code Analysis (SOCA), which is based on bounded symbolic execution, incorporates path-sensitive slicing, and employs the SMT solver Yices as its execution and verification engine. Experimental results of a prototypic SOCA Verifier, using the Verisec suite and almost 10,000 Linux device driver functions as benchmarks, show that SOCA performs competitively to source-Code model checkers and scales well when applied to real operating systems Code and pointer safety issues.
Jan Tobias Mühlberg - One of the best experts on this subject based on the ideXlab platform.
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Symbolic object Code Analysis
International Journal on Software Tools for Technology Transfer, 2014Co-Authors: Jan Tobias Mühlberg, Gerald LüttgenAbstract:Software model checkers quickly reach their limits when being applied to verifying pointer safety properties in source Code that includes function pointers and inlined assembly. This article introduces a novel technique for checking pointer safety violations, called symbolic object Code Analysis (SOCA), which is based on bounded symbolic execution, incorporates path-sensitive slicing, and employs the SMT solver Yices as its execution and verification engine. Extensive experimental results of a prototypic SOCA Verifier, using the Verisec suite and almost 10,000 Linux device driver functions as benchmarks, show that SOCA performs competitively to modern source-Code model checkers, scales well when applied to real operating systems Code and pointer safety issues, and effectively explores niches of pointer-complex software that current software verifiers do not reach.
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SPIN - Symbolic object Code Analysis
Model Checking Software, 2010Co-Authors: Jan Tobias Mühlberg, Gerald LüttgenAbstract:Current software model checkers quickly reach their limits when being applied to verifying pointer safety properties in source Code that includes function pointers and inlined assembly. This paper introduces an alternative technique for checking pointer safety violations, called Symbolic Object Code Analysis (SOCA), which is based on bounded symbolic execution, incorporates path-sensitive slicing, and employs the SMT solver Yices as its execution and verification engine. Experimental results of a prototypic SOCA Verifier, using the Verisec suite and almost 10,000 Linux device driver functions as benchmarks, show that SOCA performs competitively to source-Code model checkers and scales well when applied to real operating systems Code and pointer safety issues.
Juergen Rilling - One of the best experts on this subject based on the ideXlab platform.
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Software trustworthiness 2.0-A semantic web enabled global source Code Analysis approach
Journal of Systems and Software, 2014Co-Authors: Iman Keivanloo, Juergen RillingAbstract:Introduction of a Semantic Web enabled global source Code Analysis infrastructure.Novel source Code Analysis approach combining crowdsourcing and linked-data.Novel proactive approach to improve trustworthiness of software systems.Case studies illustrating the applicability of the approach using different resources. There has been an ongoing trend toward collaborative software development using open and shared source Code published in large software repositories on the Internet. While traditional source Code Analysis techniques perform well in single project contexts, new types of source Code Analysis techniques are ermerging, which focus on global source Code Analysis challenges. In this article, we discuss how the Semantic Web, can become an enabling technology to provide a standardized, formal, and semantic rich representations for modeling and analyzing large global source Code corpora. Furthermore, inference services and other services provided by Semantic Web technologies can be used to support a variety of core source Code Analysis techniques, such as semantic Code search, call graph construction, and clone detection. In this paper, we introduce SeCold, the first publicly available online linked data source Code dataset for software engineering researchers and practitioners. Along with its dataset, SeCold also provides some Semantic Web enabled core services to support the Analysis of Internet-scale source Code repositories. We illustrated through several examples how this linked data combined with Semantic Web technologies can be harvested for different source Code Analysis tasks to support software trustworthiness. For the case studies, we combine both our linked-data set and Semantic Web enabled source Code Analysis services with knowledge extracted from StackOverflow, a crowdsourcing website. These case studies, we demonstrate that our approach is not only capable of crawling, processing, and scaling to traditional types of structured data (e.g., source Code), but also supports emerging non-structured data sources, such as crowdsourced information (e.g., StackOverflow.com) to support a global source Code Analysis context.
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COMPSAC - Semantic Web - The Missing Link in Global Source Code Analysis?
2012 IEEE 36th Annual Computer Software and Applications Conference, 2012Co-Authors: Iman Keivanloo, Juergen Rilling, Philippe CharlandAbstract:There has been an ongoing trend towards open and shared source Code that is published on the Internet in large software repositories to support collaborative development processes. While traditional source Code Analysis techniques perform well in single project contexts, new types of global source Code Analysis techniques are slowly introduced to address the Analysis of global distributed and often incomplete source Code. In this article, we discuss how the Semantic Web, an enabling technology for these emerging source Code Analysis domains, can support a standardized, formal, and semantic rich representation to model these corpora. We also illustrate how inference services can be used to provide support for emerging source Code Analysis approaches on this data, such as search, call graph construction, and clone detection.
Balawal Shehzad - One of the best experts on this subject based on the ideXlab platform.
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Multilingual Source Code Analysis: A Systematic Literature Review
IEEE Access, 2017Co-Authors: Zaigham Mushtaq, Ghulam Rasool, Balawal ShehzadAbstract:Contemporary software applications are developed using cross-language artifacts, which are interdependent with each other. The source Code Analysis of these applications requires the extraction and examination of artifacts, which are build using multiple programming languages along with their dependencies. A large number of studies presented on multilingual source Code Analysis and its applications in the last one and half decade. The objective of this systematic literature review (SLR) is to summarize state of the art and prominent areas for future research. This SLR is based on different techniques, tools, and methodologies to analyze multilingual source Code applications. We finalized 56 multi-discipline published papers relevant to multilingual source Code Analysis and its applications out of 3820 papers, filtered through multi-stage search criterion. Based on our findings, we highlight research gaps and challenges in the field of multilingual applications. The research findings are presented in the form of research problems, research contributions, challenges, and future prospects. We identified 46 research issues and requirements for analyzing multilingual applications and grouped them in 13 different software engineering domains. We examined the research contributions and mapped them with individual research problems. We presented the research contributions in the form of tools techniques and approaches that are presented in the form of research models, platforms, frameworks, prototype models, and case studies. Every research has its limitations or prospects for future research. We highlighted the limitations and future perspectives and grouped them in various software engineering domains. Most of the research trends and potential research areas are identified in static source Code Analysis, program comprehension, refactoring, reverse engineering, detection, and traceability of cross-language links, Code coverage, security Analysis, cross-language parsing, and abstraction of source Code models.
Iman Keivanloo - One of the best experts on this subject based on the ideXlab platform.
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Software trustworthiness 2.0-A semantic web enabled global source Code Analysis approach
Journal of Systems and Software, 2014Co-Authors: Iman Keivanloo, Juergen RillingAbstract:Introduction of a Semantic Web enabled global source Code Analysis infrastructure.Novel source Code Analysis approach combining crowdsourcing and linked-data.Novel proactive approach to improve trustworthiness of software systems.Case studies illustrating the applicability of the approach using different resources. There has been an ongoing trend toward collaborative software development using open and shared source Code published in large software repositories on the Internet. While traditional source Code Analysis techniques perform well in single project contexts, new types of source Code Analysis techniques are ermerging, which focus on global source Code Analysis challenges. In this article, we discuss how the Semantic Web, can become an enabling technology to provide a standardized, formal, and semantic rich representations for modeling and analyzing large global source Code corpora. Furthermore, inference services and other services provided by Semantic Web technologies can be used to support a variety of core source Code Analysis techniques, such as semantic Code search, call graph construction, and clone detection. In this paper, we introduce SeCold, the first publicly available online linked data source Code dataset for software engineering researchers and practitioners. Along with its dataset, SeCold also provides some Semantic Web enabled core services to support the Analysis of Internet-scale source Code repositories. We illustrated through several examples how this linked data combined with Semantic Web technologies can be harvested for different source Code Analysis tasks to support software trustworthiness. For the case studies, we combine both our linked-data set and Semantic Web enabled source Code Analysis services with knowledge extracted from StackOverflow, a crowdsourcing website. These case studies, we demonstrate that our approach is not only capable of crawling, processing, and scaling to traditional types of structured data (e.g., source Code), but also supports emerging non-structured data sources, such as crowdsourced information (e.g., StackOverflow.com) to support a global source Code Analysis context.
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COMPSAC - Semantic Web - The Missing Link in Global Source Code Analysis?
2012 IEEE 36th Annual Computer Software and Applications Conference, 2012Co-Authors: Iman Keivanloo, Juergen Rilling, Philippe CharlandAbstract:There has been an ongoing trend towards open and shared source Code that is published on the Internet in large software repositories to support collaborative development processes. While traditional source Code Analysis techniques perform well in single project contexts, new types of global source Code Analysis techniques are slowly introduced to address the Analysis of global distributed and often incomplete source Code. In this article, we discuss how the Semantic Web, an enabling technology for these emerging source Code Analysis domains, can support a standardized, formal, and semantic rich representation to model these corpora. We also illustrate how inference services can be used to provide support for emerging source Code Analysis approaches on this data, such as search, call graph construction, and clone detection.