Methods and Tools for Formal Software Engineering
Total Page:16
File Type:pdf, Size:1020Kb
Load more
Recommended publications
-
Data-Driven Grasp Synthesis - a Survey Jeannette Bohg, Member, IEEE, Antonio Morales, Member, IEEE, Tamim Asfour, Member, IEEE, Danica Kragic Member, IEEE
TRANSACTIONS ON ROBOTICS 1 Data-Driven Grasp Synthesis - A Survey Jeannette Bohg, Member, IEEE, Antonio Morales, Member, IEEE, Tamim Asfour, Member, IEEE, Danica Kragic Member, IEEE specific metric. This process is usually based on some existing Abstract—We review the work on data-driven grasp synthesis grasp experience that can be a heuristic or is generated in and the methodologies for sampling and ranking candidate simulation or on a real robot. Kamon et al. [5] refer to this grasps. We divide the approaches into three groups based on whether they synthesize grasps for known, familiar or unknown as the comparative and Shimoga [2] as the knowledge-based objects. This structure allows us to identify common object rep- approach. Here, a grasp is commonly parameterized by [6, 7]: resentations and perceptual processes that facilitate the employed • the grasping point on the object with which the tool center data-driven grasp synthesis technique. In the case of known point (TCP) should be aligned, objects, we concentrate on the approaches that are based on • the approach vector which describes the 3D angle that object recognition and pose estimation. In the case of familiar objects, the techniques use some form of a similarity matching the robot hand approaches the grasping point with, to a set of previously encountered objects. Finally, for the • the wrist orientation of the robotic hand and approaches dealing with unknown objects, the core part is the • an initial finger configuration extraction of specific features that are indicative of good grasps. Data-driven approaches differ in how the set of grasp candi- Our survey provides an overview of the different methodologies dates is sampled, how the grasp quality is estimated and how and discusses open problems in the area of robot grasping. -
Verification and Formal Methods
Verification and Formal Methods: Practice and Experience J. C. P. Woodcock University of York, UK and P. G. Larsen Engineering College of Aarhus, Denmark and J. C. Bicarregui STFC Rutherford Appleton Laboratory, UK and J. S. Fitzgerald Newcastle University, UK We describe the state of the art in the industrial use of formal verification technology. We report on a new survey of the use of formal methods in industry, and compare it with the most significant surveys carried out over the last 20 years. We review the literature on formal methods, and present a series of industrial projects undetaken over the last two decades. We draw some observations from these surveys and records of experience. Based on this, we discuss the issues surrounding the industrial adoption of formal methods. Finally, we look to the future and describe the development of a Verified Software Repository, part of the worldwide Verified Software Initiative. We introduce the initial projects being used to populate the repository, and describe the challenges they address. Categories and Subject Descriptors: D.2.4 [Software/Program Verification]: Assertion check- ers, Class invariants, Correctness proofs, Formal methods, Model checking, Programming by contract; F.3.1 [Specifying and Verifying and Reasoning about Programs]: Assertions, Invariants, Logics of programs, Mechanical verification, Pre- and post-conditions, Specification techniques; F.4.1 [Mathematical Logic]: Mechanical theorem proving; I.2.2 [Automatic Pro- gramming]: Program verification. Additional Key Words and Phrases: Experimental software engineering, formal methods surveys, Grand Challenges, Verified Software Initiative, Verified Software Repository. 1. INTRODUCTION Formal verification, for both hardware and software, has been a topic of great sig- nificance for at least forty years. -
Formal Methods
SE 5302: Formal Methods Course Instructor: Parasara Sridhar Duggirala, Ph.D. Catalog Description. 3 credits. This course is designed to provide students with an introduction to formal methods as a framework for the specification, design, and verification of software-intensive embedded systems. Topics include automata theory, model checking, theorem proving, and system specification. Examples are driven by cyber-physical systems. The course is addressed to students in engineering who have had at least a year of software or embedded systems design experience. Pre- Requisites: SE 5100 or SE 5101 or SE 5102 and at least one year of software or embedded systems design experience. Course Delivery Method. The course will be offered online, asynchronously, in small recorded modules according to the course schedule and syllabus. Direct and live communication with the instructor will be available each week, according to the class schedule, for discussion, questions, examples, and quizzes. Attendance at live sessions is required, and you must notify the instructor in advance if you cannot attend. A social networking tool called Slack will be used to communicate with students and the instructor between live sessions. Course Objective. This course is designed to provide students with an introduction to formal methods as a framework for the specification, design, and verification of software- intensive embedded systems. Topics include automata theory, model checking, theorem proving, and system specification. Examples are driven by control systems and software systems. Anticipated Student Outcomes. By the end of the course, a student will be able to (1) Gain familiarity with current system design flows in industry used for embedded system design, implementation and verification. -
Identifying and Defining Relationships: Techniques for Improving Student Systemic Thinking
AC 2011-897: IDENTIFYING AND DEFINING RELATIONSHIPS: TECH- NIQUES FOR IMPROVING STUDENT SYSTEMIC THINKING Cecelia M. Wigal, University of Tennessee, Chattanooga Cecelia M. Wigal received her Ph.D. in 1998 from Northwestern University and is presently a Professor of Engineering and Assistant Dean of the College of Engineering and Computer Science at the University of Tennessee at Chattanooga (UTC). Her primary areas of interest and expertise include complex process and system analysis, process improvement analysis, and information system analysis with respect to usability and effectiveness. Dr. Wigal is also interested in engineering education reform to address present and future student and national and international needs. c American Society for Engineering Education, 2011 Identifying and Defining Relationships: Techniques for Improving Student Systemic Thinking Abstract ABET, Inc. is looking for graduating undergraduate engineering students who are systems thinkers. However, genuine systems thinking is contrary to the traditional practice of using linear thinking to help solve design problems often used by students and many practitioners. Linear thinking has a tendency to compartmentalize solution options and minimize recognition of relationships between solutions and their elements. Systems thinking, however, has the ability to define the whole system, including its environment, objectives, and parts (subsystems), both static and dynamic, by their relationships. The work discussed here describes two means of introducing freshman engineering students to thinking systemically or holistically when understanding and defining problems. Specifically, the modeling techniques of Rich Pictures and an instructor generated modified IDEF0 model are discussed. These techniques have roles in many applications. In this case they are discussed in regards to their application to the design process. -
Formal Methods for Biological Systems: Languages, Algorithms, and Applications Qinsi Wang CMU-CS-16-129 September 2016
Formal Methods for Biological Systems: Languages, Algorithms, and Applications Qinsi Wang CMU-CS-16-129 September 2016 School of Computer Science Computer Science Department Carnegie Mellon University Pittsburgh, PA Thesis Committee Edmund M. Clarke, Chair Stephen Brookes Marta Zofia Kwiatkowska, University of Oxford Frank Pfenning Natasa Miskov-Zivanov, University of Pittsburgh Submitted in partial fulfillment of the requirements for the Degree of Doctor of Philosophy Copyright c 2016 Qinsi Wang This research was sponsored by the National Science Foundation under grant numbers CNS-0926181 and CNS- 1035813, the Army Research Laboratory under grant numbers FA95501210146 and FA955015C0030, the Defense Advanced Research Projects Agency under grant number FA875012C0204, the Office of Naval Research under grant number N000141310090, the Semiconductor Research Corporation under grant number 2008-TJ-1860, and the Mi- croelectronics Advanced Research Corporation (DARPA) under grant number 2009-DT-2049. The views and conclusions contained in this document are those of the author and should not be interpreted as rep- resenting the official policies, either expressed or implied, of any sponsoring institution, the U.S. government or any other entity. Keywords: Model checking, Formal specification, Formal Analysis, Boolean networks, Qual- itative networks, Rule-based modeling, Multiscale hybrid rule-based modeling, Hybrid systems, Stochastic hybrid systems, Symbolic model checking, Bounded model checking, Statistical model checking, Bounded reachability, Probabilistic bounded reachability, Parameter estimation, Sensi- tivity analysis, Statistical tests, Pancreatic cancer, Phage-based bacteria killing, Prostate cancer treatment, C. elegans For My Beloved Mom & Dad iv Abstract As biomedical research advances into more complicated systems, there is an in- creasing need to model and analyze these systems to better understand them. -
Automated Malware Analysis Report For
ID: 330706 Sample Name: RFQ0270004296- PR0720001831-Grasp Trading Pvt. Ltd.doc Cookbook: defaultwindowsofficecookbook.jbs Time: 14:51:31 Date: 15/12/2020 Version: 31.0.0 Red Diamond Table of Contents Table of Contents 2 Analysis Report RFQ0270004296-PR0720001831-Grasp Trading Pvt. Ltd.doc 4 Overview 4 General Information 4 Detection 4 Signatures 4 Classification 4 Startup 4 Malware Configuration 4 Yara Overview 4 Sigma Overview 4 Signature Overview 4 AV Detection: 5 Mitre Att&ck Matrix 5 Behavior Graph 5 Screenshots 6 Thumbnails 6 Antivirus, Machine Learning and Genetic Malware Detection 7 Initial Sample 7 Dropped Files 7 Unpacked PE Files 7 Domains 7 URLs 7 Domains and IPs 9 Contacted Domains 9 URLs from Memory and Binaries 9 Contacted IPs 12 General Information 12 Simulations 13 Behavior and APIs 13 Joe Sandbox View / Context 13 IPs 14 Domains 14 ASN 14 JA3 Fingerprints 14 Dropped Files 14 Created / dropped Files 14 Static File Info 16 General 16 File Icon 17 Static RTF Info 17 Objects 17 Network Behavior 17 UDP Packets 17 Code Manipulations 18 Statistics 18 System Behavior 18 Analysis Process: WINWORD.EXE PID: 896 Parent PID: 792 18 General 18 File Activities 18 File Created 18 File Deleted 19 Registry Activities 19 Key Created 19 Key Value Created 19 Copyright null 2020 Page 2 of 23 Key Value Modified 21 Disassembly 23 Copyright null 2020 Page 3 of 23 Analysis Report RFQ0270004296-PR0720001831-Grasp …Trading Pvt. Ltd.doc Overview General Information Detection Signatures Classification Sample RFQ0270004296- Name: PR0720001831-Grasp Muullltttiii AAVV SSccaannnneerrr ddeettteecctttiiioonn fffoorrr ssuubbm… Trading Pvt. -
GRASP Patterns
GRASP Patterns David Duncan November 16, 2012 Introduction • GRASP (General Responsibility Assignment Software Patterns) is an acronym created by Craig Larman to encompass nine object‐oriented design principles related to creating responsibilities for classes • These principles can also be viewed as design patterns and offer benefits similar to the classic “Gang of Four” patterns • GRASP is an attempt to document what expert designers probably know intuitively • All nine GRASP patterns will be presented and briefly discussed What is GRASP? • GRASP = General Responsibility Assignment Software Patterns (or Principles) • A collection of general objected‐oriented design patterns related to assigning defining objects • Originally described as a collection by Craig Larman in Applying UML and Patterns: An Introduction to Object‐Oriented Analysis and Design, 1st edition, in 1997. Context (1 of 2) • The third edition of Applying UML and Patterns is the most current edition, published in 2005, and is by far the source most drawn upon for this material • Larman assumes the development of some type of analysis artifacts prior to the use of GRASP – Of particular note, a domain model is used • A domain model describes the subject domain without describing the software implementation • It may look similar to a UML class diagram, but there is a major difference between domain objects and software objects Context (2 of 2) • Otherwise, assumptions are broad: primarily, the practitioner is using some type of sensible and iterative process – Larman chooses -
Use of Formal Methods at Amazon Web Services
Use of Formal Methods at Amazon Web Services Chris Newcombe, Tim Rath, Fan Zhang, Bogdan Munteanu, Marc Brooker, Michael Deardeuff Amazon.com 29th September, 2014 Since 2011, engineers at Amazon Web Services (AWS) have been using formal specification and model checking to help solve difficult design problems in critical systems. This paper describes our motivation and experience, what has worked well in our problem domain, and what has not. When discussing personal experiences we refer to authors by their initials. At AWS we strive to build services that are simple for customers to use. That external simplicity is built on a hidden substrate of complex distributed systems. Such complex internals are required to achieve high availability while running on cost-efficient infrastructure, and also to cope with relentless rapid business growth. As an example of this growth; in 2006 we launched S3, our Simple Storage Service. In the 6 years after launch, S3 grew to store 1 trillion objects [1]. Less than a year later it had grown to 2 trillion objects, and was regularly handling 1.1 million requests per second [2]. S3 is just one of tens of AWS services that store and process data that our customers have entrusted to us. To safeguard that data, the core of each service relies on fault-tolerant distributed algorithms for replication, consistency, concurrency control, auto-scaling, load balancing, and other coordination tasks. There are many such algorithms in the literature, but combining them into a cohesive system is a major challenge, as the algorithms must usually be modified in order to interact properly in a real-world system. -
A Systematic Literature Review of the Use of Formal Methods in Medical Software Systems∗
JOURNAL OF SOFTWARE: EVOLUTION AND PROCESS J. Softw. Evol. and Proc. 2017; 00:1–23 Published online in Wiley InterScience (www.interscience.wiley.com). DOI: 10.1002/smr A Systematic Literature Review of the use of Formal Methods in Medical Software Systems∗ Silvia Bonfanti∗, Angelo Gargantini1, Atif Mashkoor2 ∗University of Bergamo, [email protected] 1University of Bergamo, [email protected] 2Software Competence Center Hagenberg GmbH, [email protected] SUMMARY The use of formal methods is often recommended to guarantee the provision of necessary services and to assess the correctness of critical properties, such as functional safety, cybersecurity and reliability, in medical and health-care devices. In the past, several formal and rigorous methods have been proposed and consequently applied for trustworthy development of medical software and systems. In this paper, we perform a systematic literature review on the available state of the art in this domain. We collect the relevant literature on the use of formal methods for modeling, design, development, verification and validation of software-intensive medical systems. We apply standard systematic literature review techniques and run several queries in well-known repositories in order to obtain information that can be useful for people who are either already working in this field or planning to start. Our study covers both quantitative and qualitative aspects of the subject. Copyright c 2017 John Wiley & Sons, Ltd. Received . KEY WORDS: Formal Methods, Systematic Literature Review, Medical Device Software 1. INTRODUCTION In modern medical devices, human safety depends upon the correct operation of software controlling the device: software malfunctioning can cause injuries to, or even the death of, patients. -
FORMAL METHODS: BENEFITS, CHALLENGES and FUTURE DIRECTION Mona Batra1, Amit Malik2, Dr
Volume 4, No. 5, May 2013 Journal of Global Research in Computer Science REVIEW ARTICLE Available Online at www.jgrcs.info FORMAL METHODS: BENEFITS, CHALLENGES AND FUTURE DIRECTION Mona Batra1, Amit Malik2, Dr. Meenu Dave3 1 M. Tech. Scholar Department of Computer Science, Jagan Nath University, Jaipur, India [email protected] 2Sr. Analyst, HCL Technologies Ltd. , Noida-201304, India [email protected] 3Assistant Professor Department of Computer Science, Jagan Nath University, Jaipur, India [email protected] Abstract: There is an increasing demand of current information systems to incorporate the use of a higher degree of formalism in the development process. Formal Methods consist of a set of tools and techniques based on mathematical model and formal logic that are used to specify and verify requirements and designs for hardware and software systems. This paper presents a detailed analysis of formal methods along with their goals and benefits followed by limitations. This research work is aimed to help the software engineers to identify the use of formal methods at different stages of software development, with special reference to the requirements phase. Keywords- Formal Methods, Requirements Engineering, Formal Specification, Feasibility Analysis etc. of mathematics in design and construction to ensure product INTRODUCTION quality is common practice in established engineering disciplines, such as bridge or aircraft building, and even In today’s commercial environment, the primary measure of computer (hardware) construction, where one applies success of software projects is the extent to which a mathematically expressed physical and other natural laws to software system fulfills the purpose, which it is intended for. -
Do Formal Methods Improve Code Quality?
Do Formal Methods Improve Code Quality? Shari Lawrence Pfleeger Les Hatton Centre for Software Reliability Programming Research Ltd. Northampton Square Glenbrook House, 1/11 Molesey Road London EC1V 0HB Hersham, Surrey KT12 4RH England England phone: +44 171 477-8426 +44 932 888080 fax: +44 171 477-8585 +44 932 888081 email: [email protected] [email protected] Abstract Formal methods are advocated on many projects, in the hope that their use will improve the quality of the resulting software. However, to date there has been little quantitative evidence of their effectiveness, especially for safety-critical applications. We examined the code and development records for a large air traffic control support system to see if the use of formal methods made a measurable difference. In this paper, we show that formal specification, in concert with thorough unit testing and careful reviews, can lead to high-quality code. But we also show that improved measurement and record-keeping could have made analysis easier and the results more clear-cut. As practitioners and researchers, we continue to look for methods and tools that help us to improve our software development processes and products. Articles in IEEE Software and elsewhere focus on candidate technologies that promise increased productivity, better quality, lower cost or enhanced customer satisfaction. But we are reminded that these methods and tools should be tested empirically and rigorously to determine if they make a quantifiable difference to software we produce.1,2 Often, such evaluation is not considered until after the technology has been used, making careful, quantitative analysis difficult if not impossible. -
A Debate on Teaching Computing Science
Teaching Computing Science t the ACM Computer Science Conference last Strategic Defense Initiative. William Scherlis is February, Edsger Dijkstra gave an invited talk known for his articulate advocacy of formal methods called “On the Cruelty of Really Teaching in computer science. M. H. van Emden is known for Computing Science.” He challenged some of his contributions in programming languages and the basic assumptions on which our curricula philosophical insights into science. Jacques Cohen Aare based and provoked a lot of discussion. The edi- is known for his work with programming languages tors of Comwunications received several recommenda- and logic programming and is a member of the Edi- tions to publish his talk in these pages. His comments torial Panel of this magazine. Richard Hamming brought into the foreground some of the background received the Turing Award in 1968 and is well known of controversy that surrounds the issue of what be- for his work in communications and coding theory. longs in the core of a computer science curriculum. Richard M. Karp received the Turing Award in 1985 To give full airing to the controversy, we invited and is known for his contributions in the design of Dijkstra to engage in a debate with selected col- algorithms. Terry Winograd is well known for his leagues, each of whom would contribute a short early work in artificial intelligence and recent work critique of his position, with Dijkstra himself making in the principles of design. a closing statement. He graciously accepted this offer. I am grateful to these people for participating in We invited people from a variety of specialties, this debate and to Professor Dijkstra for creating the backgrounds, and interpretations to provide their opening.