Symbolic simulation on complicated loops for WCET path analysis

10.1145/2038642.2038692Embedded Systems Week 2011, ESWEEK 2011 - Proceedings of the 9th ACM International Conference on Embedded Software, EMSOFT'11319-32

Detecting Dissimilar Classes of Source Code Defects

Software maintenance accounts for the most part of the software development cost and efforts, with its major activities focused on the detection, location, analysis and removal of defects present in the software. Although software defects can be originated, and be present, at any phase of the software development life-cycle, implementation (i.e., source code) contains more than three-fourths of the total defects. Due to the diverse nature of the defects, their detection and analysis activities have to be carried out by equally diverse tools, often necessitating the application of multiple tools for reasonable defect coverage that directly increases maintenance overhead. Unified detection tools are known to combine different specialized techniques into a single and massive core, resulting in operational difficulty and maintenance cost increment. The objective of this research was to search for a technique that can detect dissimilar defects using a simplified model and a single methodology, both of which should contribute in creating an easy-to-acquire solution. Following this goal, a ‘Supervised Automation Framework’ named FlexTax was developed for semi-automatic defect mapping and taxonomy generation, which was then applied on a large-scale real-world defect dataset to generate a comprehensive Defect Taxonomy that was verified using machine learning classifiers and manual verification. This Taxonomy, along with an extensive literature survey, was used for comprehension of the properties of different classes of defects, and for developing Defect Similarity Metrics. The Taxonomy, and the Similarity Metrics were then used to develop a defect detection model and associated techniques, collectively named Symbolic Range Tuple Analysis, or SRTA. SRTA relies on Symbolic Analysis, Path Summarization and Range Propagation to detect dissimilar classes of defects using a simplified set of operations. To verify the effectiveness of the technique, SRTA was evaluated by processing multiple real-world open-source systems, by direct comparison with three state-of-the-art tools, by a controlled experiment, by using an established Benchmark, by comparison with other tools through secondary data, and by a large-scale fault-injection experiment conducted using a Mutation-Injection Framework, which relied on the taxonomy developed earlier for the definition of mutation rules. Experimental results confirmed SRTA’s practicality, generality, scalability and accuracy, and proved SRTA’s applicability as a new Defect Detection Technique

Ernst Denert Award for Software Engineering 2020

This open access book provides an overview of the dissertations of the eleven nominees for the Ernst Denert Award for Software Engineering in 2020. The prize, kindly sponsored by the Gerlind & Ernst Denert Stiftung, is awarded for excellent work within the discipline of Software Engineering, which includes methods, tools and procedures for better and efficient development of high quality software. An essential requirement for the nominated work is its applicability and usability in industrial practice. The book contains eleven papers that describe the works by Jonathan Brachthäuser (EPFL Lausanne) entitled What You See Is What You Get: Practical Effect Handlers in Capability-Passing Style, Mojdeh Golagha’s (Fortiss, Munich) thesis How to Effectively Reduce Failure Analysis Time?, Nikolay Harutyunyan’s (FAU Erlangen-Nürnberg) work on Open Source Software Governance, Dominic Henze’s (TU Munich) research about Dynamically Scalable Fog Architectures, Anne Hess’s (Fraunhofer IESE, Kaiserslautern) work on Crossing Disciplinary Borders to Improve Requirements Communication, Istvan Koren’s (RWTH Aachen U) thesis DevOpsUse: A Community-Oriented Methodology for Societal Software Engineering, Yannic Noller’s (NU Singapore) work on Hybrid Differential Software Testing, Dominic Steinhofel’s (TU Darmstadt) thesis entitled Ever Change a Running System: Structured Software Reengineering Using Automatically Proven-Correct Transformation Rules, Peter Wägemann’s (FAU Erlangen-Nürnberg) work Static Worst-Case Analyses and Their Validation Techniques for Safety-Critical Systems, Michael von Wenckstern’s (RWTH Aachen U) research on Improving the Model-Based Systems Engineering Process, and Franz Zieris’s (FU Berlin) thesis on Understanding How Pair Programming Actually Works in Industry: Mechanisms, Patterns, and Dynamics – which actually won the award. The chapters describe key findings of the respective works, show their relevance and applicability to practice and industrial software engineering projects, and provide additional information and findings that have only been discovered afterwards, e.g. when applying the results in industry. This way, the book is not only interesting to other researchers, but also to industrial software professionals who would like to learn about the application of state-of-the-art methods in their daily work

Ernst Denert Award for Software Engineering 2020

This open access book provides an overview of the dissertations of the eleven nominees for the Ernst Denert Award for Software Engineering in 2020. The prize, kindly sponsored by the Gerlind & Ernst Denert Stiftung, is awarded for excellent work within the discipline of Software Engineering, which includes methods, tools and procedures for better and efficient development of high quality software. An essential requirement for the nominated work is its applicability and usability in industrial practice. The book contains eleven papers that describe the works by Jonathan Brachthäuser (EPFL Lausanne) entitled What You See Is What You Get: Practical Effect Handlers in Capability-Passing Style, Mojdeh Golagha’s (Fortiss, Munich) thesis How to Effectively Reduce Failure Analysis Time?, Nikolay Harutyunyan’s (FAU Erlangen-Nürnberg) work on Open Source Software Governance, Dominic Henze’s (TU Munich) research about Dynamically Scalable Fog Architectures, Anne Hess’s (Fraunhofer IESE, Kaiserslautern) work on Crossing Disciplinary Borders to Improve Requirements Communication, Istvan Koren’s (RWTH Aachen U) thesis DevOpsUse: A Community-Oriented Methodology for Societal Software Engineering, Yannic Noller’s (NU Singapore) work on Hybrid Differential Software Testing, Dominic Steinhofel’s (TU Darmstadt) thesis entitled Ever Change a Running System: Structured Software Reengineering Using Automatically Proven-Correct Transformation Rules, Peter Wägemann’s (FAU Erlangen-Nürnberg) work Static Worst-Case Analyses and Their Validation Techniques for Safety-Critical Systems, Michael von Wenckstern’s (RWTH Aachen U) research on Improving the Model-Based Systems Engineering Process, and Franz Zieris’s (FU Berlin) thesis on Understanding How Pair Programming Actually Works in Industry: Mechanisms, Patterns, and Dynamics – which actually won the award. The chapters describe key findings of the respective works, show their relevance and applicability to practice and industrial software engineering projects, and provide additional information and findings that have only been discovered afterwards, e.g. when applying the results in industry. This way, the book is not only interesting to other researchers, but also to industrial software professionals who would like to learn about the application of state-of-the-art methods in their daily work