Bidirectional Tracing of Requirements in Embedded Software Development
Total Page:16
File Type:pdf, Size:1020Kb
Load more
Recommended publications
-
Navigating the Next Evolution of Application Development Using Distributed Tracing
Navigating the Next Evolution of Application Development Using Distributed Tracing Navigating the Next Evolution of Application Development 1 Table of Contents Introduction ...........................................................................................................................................................................................3 How has software been built? Waterfall vs. DevOps ................................................................................. ............................. 4 The next evolution: Microservices ................................................................................................................................................5 What will you need to do differently to capitalizeon modern application development? ..........................................6 Get started with Epsagon on AWS ...............................................................................................................................................8 Case Study: Bastian Solutions .......................................................................................................................................................9 Learn More ..........................................................................................................................................................................................10 Navigating the Next Evolution of Application Development 2 Introduction Building and maintaining a competitive edge often requires you to evolve with your customers’ -
Traceability Establishment and Visualization of Software Artefacts in Devops Practice: a Survey
(IJACSA) International Journal of Advanced Computer Science and Applications, Vol. 10, No. 7, 2019 Traceability Establishment and Visualization of Software Artefacts in DevOps Practice: A Survey D. A. Meedeniya1, I. D. Rubasinghe2, I. Perera3 Dept. of Computer Science and Engineering, University of Moratuwa, Sri Lanka Abstract—DevOps based software process has become the artefacts in the SDLC [2][3]. There are different forms of popular with the vision of an effective collaboration between the relationships between the homogeneous and heterogeneous development and operations teams that continuously integrates software artefacts. Some artefacts may be highly coupled, and the frequent changes. Traceability manages the artefact some may depend on other artefacts in different degrees, consistency during a software process. This paper explores the unidirectionally or bidirectionally. Thus, software artefacts trace-link creation and visualization between software artefacts, consistency management helps to fine-tune the software existing tool support, quality aspects and the applicability in a process. The incomplete, outdated software artefacts and their DevOps environment. As the novelty of this study, we identify the inconsistencies mislead both the development and maintenance challenges that limit the traceability considerations in DevOps process. Thus, artefact management is essential such that the and suggest research directions. Our methodology consists of changes are accurately propagated to the impacted artefacts concept identification, state-of-practice exploration and analytical review. Despite the existing related work, there is a without creating inconsistencies. Traceability is the potential to lack of tool support for the traceability management between relate artefacts considering their relationships [4][5]; thus, a heterogeneous artefacts in software development with DevOps solution for artefact management. -
Linuxcon North America 2012
LinuxCon North America 2012 LTTng 2.0 : Tracing, Analysis and Views for Performance and Debugging. E-mail: [email protected] Mathieu Desnoyers August 29th, 2012 1 > Presenter ● Mathieu Desnoyers ● EfficiOS Inc. ● http://www.efficios.com ● Author/Maintainer of ● LTTng, LTTng-UST, Babeltrace, Userspace RCU Mathieu Desnoyers August 29th, 2012 2 > Content ● Tracing benefits, ● LTTng 2.0 Linux kernel and user-space tracers, ● LTTng 2.0 usage scenarios & viewers, ● New features ready for LTTng 2.1, ● Conclusion Mathieu Desnoyers August 29th, 2012 3 > Benefits of low-impact tracing in a multi-core world ● Understanding interaction between ● Kernel ● Libraries ● Applications ● Virtual Machines ● Debugging ● Performance tuning ● Monitoring Mathieu Desnoyers August 29th, 2012 4 > Tracing use-cases ● Telecom ● Operator, engineer tracing systems concurrently with different instrumentation sets. ● In development and production phases. ● High-availability, high-throughput servers ● Development and production: ensure high performance, low-latency in production. ● Embedded ● System development and production stages. Mathieu Desnoyers August 29th, 2012 5 > LTTng 2.0 ● Rich ecosystem of projects, ● Key characteristics of LTTng 2.0: – Small impact on the traced system, fast, user- oriented features. ● Interfacing with: Common Trace Format (CTF) Interoperability Between Tracing Tools Tracing Well With Others: Integration with the Common Trace Format (CTF), of GDB Tracepoints Into Trace Tools, Mathieu Desnoyers, EfficiOS, Stan Shebs, Mentor Graphics, -
System Wide Tracing and Profiling in Linux
SYSTEM WIDE TRACING AND PROFILING IN LINUX Nadav Amit Agenda • System counters inspection • Profiling with Linux perf tool • Tracing using ftrace Disclaimer • Introductory level presentation • We are not going to cover many tools • We are not going to get deep into the implementation of the tools • I am not an expert on many of the issues Collect Statistics • First step in analyzing the system behavior • Option 1: Resource statistics tools • iostat, vmstat, netstat, ifstat • dstat Examples: dstat --vm --aio • dstat • dstat --udp --tcp --socket • dstat --vm --aio dstat --udp --tcp --socket Watch system behavior online • Option 2: Sample the counter • top • Use –H switch for thread specific • Use ‘f’ to choose additional fields: page faults, last used processor • Use ‘1’ to turn off cumulative mode • iotop • Remember to run as sudoer top Inspect Raw Counters • Option 3: Go to the raw counters • General • /proc/stat • /proc/meminfo • /proc/interrupts • Process specific • /proc/[pid]/statm – process memory • /proc/[pid]/stat – process execution times • /proc/[pid]/status – human readable • Device specific • /sys/block/[dev]/stat • /proc/dev/net • Hardware • smartctl /proc/interrupts /sys/block/[dev]/stat Name units description ---- ----- ----------- read I/Os requests number of read I/Os processed read merges requests number of read I/Os merged with in-queue I/O read sectors sectors number of sectors read read ticks milliseconds total wait time for read requests write I/Os requests number of write I/Os processed write merges requests number -
Debugging and Profiling with Arm Tools
Debugging and Profiling with Arm Tools [email protected] • Ryan Hulguin © 2018 Arm Limited • 4/21/2018 Agenda • Introduction to Arm Tools • Remote Client Setup • Debugging with Arm DDT • Other Debugging Tools • Break • Examples with DDT • Lunch • Profiling with Arm MAP • Examples with MAP • Obtaining Support 2 © 2018 Arm Limited Introduction to Arm HPC Tools © 2018 Arm Limited Arm Forge An interoperable toolkit for debugging and profiling • The de-facto standard for HPC development • Available on the vast majority of the Top500 machines in the world • Fully supported by Arm on x86, IBM Power, Nvidia GPUs and Arm v8-A. Commercially supported by Arm • State-of-the art debugging and profiling capabilities • Powerful and in-depth error detection mechanisms (including memory debugging) • Sampling-based profiler to identify and understand bottlenecks Fully Scalable • Available at any scale (from serial to petaflopic applications) Easy to use by everyone • Unique capabilities to simplify remote interactive sessions • Innovative approach to present quintessential information to users Very user-friendly 4 © 2018 Arm Limited Arm Performance Reports Characterize and understand the performance of HPC application runs Gathers a rich set of data • Analyses metrics around CPU, memory, IO, hardware counters, etc. • Possibility for users to add their own metrics Commercially supported by Arm • Build a culture of application performance & efficiency awareness Accurate and astute • Analyses data and reports the information that matters to users insight • Provides simple guidance to help improve workloads’ efficiency • Adds value to typical users’ workflows • Define application behaviour and performance expectations Relevant advice • Integrate outputs to various systems for validation (e.g. -
Traceability in Agile Software Projects
Traceability in Agile software projects Master of Science Thesis in Software Engineering & Management VUONG HOANG DUC University of Gothenburg Chalmers University of Technology Department of Computer Science and Engineering Göteborg, Sweden, May 2013 The Author grants to Chalmers University of Technology and University of Gothenburg the non-exclusive right to publish the Work electronically and in a non-commercial purpose make it accessible on the Internet. The Author warrants that he/she is the author to the Work, and warrants that the Work does not contain text, pictures or other material that violates copyright law. The Author shall, when transferring the rights of the Work to a third party (for example a publisher or a company), acknowledge the third party about this agreement. If the Author has signed a copyright agreement with a third party regarding the Work, the Author warrants hereby that he/she has obtained any necessary permission from this third party to let Chalmers University of Technology and University of Gothenburg store the Work electronically and make it accessible on the Internet. Traceability in Agile software projects VUONG.HOANG DUC VUONG. HOANG DUC, May 2013. Examiner: CHRISTIAN.BERGER University of Gothenburg Chalmers University of Technology Department of Computer Science and Engineering SE-412 96 Göteborg Sweden Telephone + 46 (0)31-772 1000 ABSTRACT Context: Software applications have been penetrating every corner of our daily life in the past decades. This condition demands high quality software. Traceability activities have been recognized as important factors supporting various activities during the development process of a software system with the aim of improving software quality. -
Distributed Architecture for an Integrated Development Environment, Large Trace Analysis, and Visualization
sensors Article Distributed Architecture for an Integrated Development Environment, Large Trace Analysis, and Visualization Yonni Chen Kuang Piao 1, Naser Ezzati-jivan 2,* and Michel R. Dagenais 1 1 Computer Engineering and Software Engineering Department, Ecole Polytechnique Montreal, Montreal, QC h3t 1j4, Canada; [email protected] (Y.C.K.P.); [email protected] (M.R.D.) 2 Computer Science Department, Brock University, St. Catharines, ON l22 3a1, Canada * Correspondence: [email protected] Abstract: Integrated development environments (IDEs) provide many useful tools such as a code editor, a compiler, and a debugger for creating software. These tools are highly sophisticated, and their development requires a significant effort. Traditionally, an IDE supports different programming languages via plugins that are not usually reusable in other IDEs. Given the high complexity and constant evolution of popular programming languages, such as C++ and even Java, the effort to update those plugins has become unbearable. Thus, recent work aims to modularize IDEs and reuse the existing parser implementation directly in compilers. However, when IDE debugging tools are insufficient at detecting performance defects in large and multithreaded systems, developers must use tracing and trace visualization tools in their software development process. Those tools are often standalone applications and do not interoperate with the new modular IDEs, thus losing the power and the benefits of many features provided by the IDE. The structure and use cases of tracing tools, with the potentially massive execution traces, significantly differ from the other tools in IDEs. Thus, it is a considerable challenge, one which has not been addressed previously, to integrate them into the new modular IDEs. -
Devops/Continuous Delivery Tooling
DevOps/Continuous Delivery Tooling Launchpad for the Digital Enterprise Report Summary ENTERPRISE MANAGEMENT ASSOCIATES® (EMA™) Research Report Written by Julie Craig, Research Director, Application Management Spring 2017 Sponsored by: IT & DATA MANAGEMENT RESEARCH, INDUSTRY ANALYSIS & CONSULTING Report Summary – DevOps/Continuous Delivery Tooling: Launchpad for the Digital Enterprise Table of Contents Overview .....................................................................................................................................................1 10 Key Takeaways ........................................................................................................................................2 DevOps and Continuous Delivery: People, Processes, and Technology Interacting Across the Lifecycle .....3 Automation Supporting DevOps and Continuous Delivery in the Digital Enterprise ................................3 Background and Methodology ...................................................................................................................5 Digital Business in 2017 ..............................................................................................................................5 Technology Landscapes ................................................................................................................................6 Automation and Tooling for the Digital Business ........................................................................................7 Continuous Delivery .................................................................................................................................11 -
Requirements Traceability and the Effect on the System Development Lifecycle (SDLC)
Requirements Traceability and the Effect on the System Development Lifecycle (SDLC) by Glenn A. Stout (STOUT) DISS 725: Systems Development Process Spring Cluster, 2001 Research Paper 2 Glenn A. Stout (STOUT) Table of Contents Overview........................................................................................................................................3 Purpose..........................................................................................................................................3 Traceability....................................................................................................................................3 Traceability and Traceability Item Defined...............................................................................4 Traceability Links..................................................................................................................4 Traditional Requirements Gathering.............................................................................................5 In General..................................................................................................................................5 Engaging in the Practice of Tracing Requirements.......................................................................6 Software Requirements Specification (SRS).............................................................................6 Use Case Methodology..............................................................................................................7 -
Monitoring, Tracing, Debugging (Under Construction)
Monitoring, Tracing, Debugging (Under Construction) I was already tempted to drop this topic from my lecture on operating systems when I found Stephan Siemen's article "Top Speed" in Linux World 10/2003. He mentions a whole range of useful tools for performance tracking and bug finding on Linux and I decided to take his list and give some additional background on how these things work.After being a unix kernel hacker for some year I moved into user space and started to develop more and more user level code. I soon realized that the style of development used for kernel hacking is quite different to the one needed for servers, frameworks and applications. Some concepts still apply, like logging events. Others change, e.g. using garbage collectors. Some of the tools that made the biggest impression where Pure Atria's Purify (now IBM Rational) - object code instrumentation the easy way. And the Visual Age (now Eclipse) Debugger which made me give up on printf/println style of finding bugs. Look at the resource section at the end for links. Introduction 2 / 30 Goals 1. A word on monitoring, tracing, debugging. 2. Modern approaches for tracing, logging and auditing. 3. Understanding interfaces within and between programs and environments. Remember: every problem in computer science is solved with one more level of indirection. And interfaces are the locations where program flow can be re-directed. 4. Monitoring Levels 5. Different techniques for monitoring 6. Performance and memory tracking. How garbage collection works will be explained in detail in our session on virtual memory. -
Recovering Traceability Links in Software Artifact Management Systems Using Information Retrieval Methods
13 Recovering Traceability Links in Software Artifact Management Systems using Information Retrieval Methods ANDREA DE LUCIA, FAUSTO FASANO, ROCCO OLIVETO, and GENOVEFFA TORTORA University of Salerno The main drawback of existing software artifact management systems is the lack of automatic or semi-automatic traceability link generation and maintenance. We have improved an artifact management system with a traceability recovery tool based on Latent Semantic Indexing (LSI), an information retrieval technique. We have assessed LSI to identify strengths and limitations of using information retrieval techniques for traceability recovery and devised the need for an incremental approach. The method and the tool have been evaluated during the development of seventeen software projects involving about 150 students. We observed that although tools based on information retrieval provide a useful support for the identification of traceability links during software development, they are still far to support a complete semi-automatic recovery of all links. The results of our experience have also shown that such tools can help to identify quality problems in the textual description of traced artifacts. Categories and Subject Descriptors: D.2.7 [Software Engineering]: Distribution, Maintenance, and Enhancement; D.2.9 [Software Engineering]: Management—Software configuration man- agement; G.1.3 [Numerical Analysis]: Numerical Linear Algebra—Singular value decomposition; H.3.1 [Information Storage and Retrieval]: Content Analysis and Indexing—indexing methods; H.3.3 [Information Storage and Retrieval]: Information Search and Retrieval General Terms: Documentation, Management Additional Key Words and Phrases: Software artifact management, traceability management, impact analysis, latent semantic indexing ACM Reference Format: De Lucia, A., Fasano, F., Oliveto, R., and Tortora, G. -
Ninja: Towards Transparent Tracing and Debugging On
Ninja: Towards Transparent Tracing and Debugging on ARM Zhenyu Ning and Fengwei Zhang, Wayne State University https://www.usenix.org/conference/usenixsecurity17/technical-sessions/presentation/ning This paper is included in the Proceedings of the 26th USENIX Security Symposium August 16–18, 2017 • Vancouver, BC, Canada ISBN 978-1-931971-40-9 Open access to the Proceedings of the 26th USENIX Security Symposium is sponsored by USENIX Ninja: Towards Transparent Tracing and Debugging on ARM Zhenyu Ning and Fengwei Zhang Wayne State University fzhenyu.ning, [email protected] Abstract lar hardware components, and performance slowdown. The hardware-assisted virtualization technique [17, 50] Existing malware analysis platforms leave detectable fin- can improve the transparency of the virtualization-based gerprints like uncommon string properties in QEMU, systems; however, this approach still leaves artifacts on signatures in Android Java virtual machine, and arti- basic instruction execution semantics that could be easily facts in Linux kernel profiles. Since these fingerprints detected by malware [39]. provide the malware a chance to split its behavior de- To address this challenge, researchers study the mal- pending on whether the analysis system is present or ware on bare-metal devices via modifying the system not, existing analysis systems are not sufficient to ana- software [22, 37, 44, 55] or leveraging OS APIs [15, 56] lyze the sophisticated malware. In this paper, we pro- to monitor the runtime behavior of malware. Although pose NINJA, a transparent malware analysis framework bare-metal based approaches eliminate the detection of on ARM platform with low artifacts. NINJA leverages a the emulator or hypervisor, the artifacts introduced by the hardware-assisted isolated execution environment Trust- analysis tool itself are still detectable by malware.