1,687 Comments

1. January 17, 2019 at 8:48 pm

   Tomi Engdahl says:

   https://hackaday.com/2019/01/12/preventing-embedded-fails-with-watchdogs/

   Reply
2. January 18, 2019 at 11:12 am

   Tomi Engdahl says:

   Taming Concurrency
   https://semiengineering.com/taming-concurrency/

   What hoops will designers have to jump through to avoid concurrency bugs?

   Reply
3. January 18, 2019 at 2:22 pm

   Tomi Engdahl says:

   5 Technologies Embedded System Engineers Should Master in 2019
   https://www.designnews.com/electronics-test/5-technologies-embedded-system-engineers-should-master-2019/53720324260073?ADTRK=UBM&elq_mid=7141&elq_cid=876648

   Here are the technologies that have the greatest impact on the way we design and develop embedded systems.

   Technology #1 – Defect Management

   In 2018, I spent a lot of time talking about debugging techniques that developers can use to minimize the defects that are in their systems. The fact is, debugging techniques are the last resort to remove defects from an embedded system. The processes that are put in place during the design and development are far more important in minimizing defects. There have been several advances in the last few years that many embedded developers have not been taking advantage of. These include:

   Continuous integration servers
   Hardware-in-loop testing
   Unit testing
   Automated testing

   There is a lot that developers can do in these areas to reduce the time spent debugging. In many cases developers tell themselves that they will look into these items or implement them after the next delivery when there is more time.

   Technology #2 – Cloud Connectivity

   Many “traditional” embedded systems are, or were, disconnected systems that had no access to the Internet. With the big push for the IoT, many systems are now adding wireless or wired connectivity and streaming loads of data up to the cloud for processing and storage. The traditional embedded software developer in general doesn’t have much experience with setting up cloud services, working with MQTT, or the many other technologies that are required for use with the cloud. There are several activities that developers should put into their calendars this year in order to become more familiar with cloud connectivity. These activities include:

   Setting up a cloud service provider such as Amazon Web Services, Google Cloud, etc

   Set up private and public keys along with a device certificate.
   Write a device policy for devices connecting to the cloud service
   Connect an embedded system to the cloud service
   Transmit and receive information to the cloud
   Build a basic dashboard to examine data in the cloud and control the device

   Technology #3 – Security

   With many devices now connecting to the cloud, a major concern facing developers is how to secure their systems. There are several new technologies, more than I could list in this post, that will be impacting how developers design their systems. These technologies vary from using security processors, Arm TrustZone, and multi-core microcontrollers to partition secure and non-secure application code. While there are several hardware technology sets available, the available software solutions have been expanding at an extraordinary rate. Many of these technologies are just being introduced and 2019 is an excellent year to focus in and master security concepts and apply them your embedded systems.

   Technology #4 – Machine Learning

   A major theme that we are going to hear about nearly non-stop in 2019 is about moving machine learning from the cloud to the edge. Machine learning has been a force to reckon with in the cloud and the ability to move machine learning to microcontroller-based systems is going to be a game changer.

   Technology #5 – Low Power Design

   Embedded designers have always had to contend with battery operated devices but with more IoT connected devices and sensor nodes, low power design is becoming a crucial design criteria that can dramatically affect the operating costs of a company.

   Developers working with battery operated devices need to stay up to date in several key areas:

   Wireless radio technologies
   Hardware energy monitoring
   Software energy consumption monitoring
   Battery architectures
   Power regulators

   Reply
4. January 23, 2019 at 2:21 pm

   Tomi Engdahl says:

   5 Technologies Embedded System Engineers Should Master in 2019
   https://www.designnews.com/electronics-test/5-technologies-embedded-system-engineers-should-master-2019/53720324260073?ADTRK=UBM&elq_mid=7146&elq_cid=876648

   Here are the technologies that have the greatest impact on the way we design and develop embedded systems.

   Technology #1 – Defect Management
   Technology #2 – Cloud Connectivity
   Technology #3 – Security
   Technology #4 – Machine Learning
   Technology #5 – Low Power Design

   While we should be looking to master these technologies, each area itself could require years to master. It’s important that developers select at least one technology to work at mastering and then at least keep abreast of the basics and advancements in the other areas.

   Reply
5. January 29, 2019 at 11:57 am

   Tomi Engdahl says:

   Making Embedded Software Safe and Secure
   https://www.eeweb.com/profile/jayabraham/articles/making-embedded-software-safe-and-secure

   Traditional verification techniques of code review and testing may be inadequate to find bugs or to prove that the code is safe and secure

   Code review: If we manually inspect this code, we will quickly identify that line 21 may result in a safety concern. On this line of code, we are performing the operation x / (x – y). A divide operation is being performed with integers, and if the variables x and y are equal, a divide-by-zero will occur. Manual inspection of the code prior to this operation is not trivial, and we cannot say with ease that x shall never be equal to zero. Hours of additional analysis may be needed to check this condition. We could create a guard condition, but this would add inefficiency to the code and add further requirements and design work to determine what action must be taken if x == y.

   Testing approach: If you consider testing, you would need only two test cases for full modified condition/decision coverage (MCDC). These test cases would execute all branches of the code, but they do not sweep the full complement of inputs to the function. Is this sufficient to confirm robustness and safety? An exhaustive test would consider all possible values for each of the inputs, but exhaustive testing for the full combination of two 32-bit integers is not technically feasible.

   Although code review and testing reveal some facets of our software, we are still left with the possibility that the code may contain a bug that results in a divide-by-zero program crash. Let’s consider static analysis, including augmenting this approach with formal methods.

   Static analysis: Static analysis is often used to supplement test cases. Static analysis, which automates many manual verification tasks such as enforcing coding standards and style guides, can also find defects based on heuristics. For this example, a static analysis tool could broaden test coverage by checking many possible values for the variables. However, as a side effect, it will produce many false warnings for values that will never occur.

   Formal methods: Static analysis tools that are based on formal methods verify run-time behavior and prove the absence of errors.

   Reply
6. January 29, 2019 at 12:05 pm

   Tomi Engdahl says:

   5 Technologies Embedded System Engineers Should Master in 2019
   https://www.designnews.com/electronics-test/5-technologies-embedded-system-engineers-should-master-2019/53720324260073?ADTRK=UBM&elq_mid=7214&elq_cid=876648

   Here are the technologies that have the greatest impact on the way we design and develop embedded systems.

   Technology #1 – Defect Management

   In 2018, I spent a lot of time talking about debugging techniques that developers can use to minimize the defects that are in their systems. The fact is, debugging techniques are the last resort to remove defects from an embedded system. The processes that are put in place during the design and development are far more important in minimizing defects. There have been several advances in the last few years that many embedded developers have not been taking advantage of. These include:

   Continuous integration servers
   Hardware-in-loop testing
   Unit testing
   Automated testing

   Technology #2 – Cloud Connectivity

   Many “traditional” embedded systems are, or were, disconnected systems that had no access to the Internet. With the big push for the IoT, many systems are now adding wireless or wired connectivity and streaming loads of data up to the cloud for processing and storage. The traditional embedded software developer in general doesn’t have much experience with setting up cloud services, working with MQTT, or the many other technologies that are required for use with the cloud. There are several activities that developers should put into their calendars this year in order to become more familiar with cloud connectivity. These activities include:

   Setting up a cloud service provider such as Amazon Web Services, Google Cloud, etc

   Set up private and public keys along with a device certificate.
   Write a device policy for devices connecting to the cloud service
   Connect an embedded system to the cloud service
   Transmit and receive information to the cloud
   Build a basic dashboard to examine data in the cloud and control the devi

   Technology #3 – Security

   With many devices now connecting to the cloud, a major concern facing developers is how to secure their systems.

   These technologies vary from using security processors, Arm TrustZone, and multi-core microcontrollers to partition secure and non-secure application code. While there are several hardware technology sets available, the available software solutions have been expanding at an extraordinary rate.

   Technology #4 – Machine Learning

   A major theme that we are going to hear about nearly non-stop in 2019 is about moving machine learning from the cloud to the edge. Machine learning has been a force to reckon with in the cloud and the ability to move machine learning to microcontroller-based systems is going to be a game changer.

   Technology #5 – Low Power Design

   Embedded designers have always had to contend with battery operated devices but with more IoT connected devices and sensor nodes, low power design is becoming a crucial design criteria that can dramatically affect the operating costs of a company.

   Developers working with battery operated devices need to stay up to date in several key areas:

   Wireless radio technologies
   Hardware energy monitoring
   Software energy consumption monitoring
   Battery architectures
   Power regulators

   Reply
7. January 29, 2019 at 12:13 pm

   Tomi Engdahl says:

   Crash your code – Lessons Learned From Debugging Things That Should Never Happen™
   https://hackaday.com/2019/01/22/crash-your-code-lessons-learned-from-debugging-things-that-should-never-happen/

   Let’s be honest, no one likes to see their program crash. It’s a clear sign that something is wrong with our code, and that’s a truth we don’t like to see. We try our best to avoid such a situation, and we’ve seen how compiler warnings and other static code analysis tools can help us to detect and prevent possible flaws in our code, which could otherwise lead to its demise. But what if I told you that crashing your program is actually a great way to improve its overall quality? Now, this obviously sounds a bit counterintuitive, after all we are talking about preventing our code from misbehaving, so why would we want to purposely break it?

   When Things Go Wrong

   Crash Where Crashing Is Due

   The thing is, by the time we can tell that our data isn’t as expected, it’s already too late. By working around the symptoms, we’re not only introducing unnecessary complexity (which we most likely have to drag along to every other place the data is passed on to), but are also covering up the real problem hiding underneath. That hidden problem won’t disappear by ignoring it, and sooner or later it will cause real consequences that force us to debug it for good. Except, by that time, we may have obscured its path so well that it takes a lot more effort to work our way back to the origin of the problem.

   Worst case, we never get there, and instead, we keep on implementing workaround after workaround, spinning in circles, with the next bug just waiting to happen. We tiptoe around the issue for the sake of keeping the program running, and ignore how futile that is as a long-term solution. We might as well give up and abort right here and now — and I say, you should do exactly that.

   Sure, crashing our program is no long-term solution either, but it also isn’t meant to be one. It is meant as indicator that we ended up in a situation that we didn’t anticipate, and our code is therefore not prepared to properly handle it. What led us there, and whether we are dealing with an actual bug or simply flawed logic in our implementation is a different story, and for us to find out.

   Assertions Are Optional

   By design, assertions are meant as a debugging tool during development, and while the libc documentation advises against it, it is common practice to disable them for a release build. But what if we don’t catch a problem during development, and it shows up in the wild one day? And chances are, that’s exactly what’s going to happen. Without the assertion code, neither the check that would prevent the problem is performed, nor would we get any information about it.

   Okay, we are talking about purposely crashing our code here, so we could just make it a habit to always leave the assertions enabled, regardless of debug or release build. But that leaves still one other problem.

   Assertion Messages Are Useless

   If we take a look at the output from a failed assertion, we will know which assert() call exactly failed: the one that made sure the value is in valid range. So we also know that we are dealing with an invalid value. What we don’t know is the actual value that failed the assertion.

   Sure, if we happen to get a core dump, and the executable contains debug information, we can use gdb to find out more about that. But unfortunately, we don’t often have that luxury outside of our own development environment, and we have to work with error logs and other debug output instead. In that case, we are left with output of very little value.

   Crashing Better

   If you ever find yourself in a situation where you have a myriad of reports of the exact same issue, and you are lucky enough to have an error log available for each individual incident, you will learn how frustratingly helpless it feels to know a certain condition failed, but to have zero information what exactly made it fail. It is when you realize and learn the hard way how useless, and almost counterproductive, error messages in the form of “expected situation is not true, period” without any further details really are.

   Consider the following two error messages:

   Assertion `data->value value is 255, expected value value (0x564d379681fc) was 234

   As programmers, we grow up being indoctrinated on the importance of error handling, but in our early years, we rarely learn how to properly utilize it, and we might fail to see any actual benefit or even use for it at all.

   Reply
8. January 29, 2019 at 12:16 pm

   Tomi Engdahl says:

   Can You Trust Your C Compiler?
   https://hackaday.com/2019/01/24/can-you-trust-your-c-compiler/

   If you are writing a hello world program, you probably aren’t too concerned about how the compiler translates your source code to machine code. However, if your code runs on something that people’s lives depend on, you will want to be a bit pickier and use something like the COMPCERT compiler. It’s a formally verified compiler, meaning there is a mathematical proof that what you write in C will be correctly translated to machine code. The compiler can generate for PowerPC, ARM, RISC-V, and x86, accepting a subset of ISO C 99 with a few extensions. While it doesn’t produce code that runs as fast as gcc, you can be sure the generated code will do what you asked it to do.

   CompCert
   http://compcert.inria.fr/

   The CompCert project investigates the formal verification of realistic compilers usable for critical embedded software. Such verified compilers come with a mathematical, machine-checked proof that the generated executable code behaves exactly as prescribed by the semantics of the source program. By ruling out the possibility of compiler-introduced bugs, verified compilers strengthen the guarantees that can be obtained by applying formal methods to source programs.

   The main result of the project is the CompCert C verified compiler, a high-assurance compiler for almost all of the C language (ISO C99), generating efficient code for the PowerPC, ARM, RISC-V and x86 processors.

   The latest release of the CompCert C compiler is version 3.4, released in September 2018.

   Reply
9. January 29, 2019 at 12:19 pm

   Tomi Engdahl says:

   Cool Tools: A Little Filesystem that Keeps Your Bits on Lock
   https://hackaday.com/2019/01/24/cool-tools-a-little-filesystem-that-keeps-your-bits-on-lock/

   Filesystems for computers are not the best bet for embedded systems. Even those who know this fragment of truth still fall into the trap and pay for it later on while surrounded by the rubble that once was a functioning project. Here’s how it happens.

   Reply
10. January 29, 2019 at 1:22 pm

    Tomi Engdahl says:

    Solving the Year 2038 problem in the Linux kernel
    How the quest to prevent time from running out led to all corners of the Linux kernel.
    https://opensource.com/article/19/1/year2038-problem-linux-kernel

    Because of the way time is represented in Linux, a signed 32-bit number can’t support times beyond January 19, 2038 after 3:14:07 UTC. This Year 2038 (Y2038 or Y2K38) problem is about the time data type representation. The solution is to use 64-bit timestamps.

    The problem also involves user space, C library, POSIX, and C standards. I found that the problem is really about interfaces between layers.

    Solving one problem in the kernel rarely involves just one thing; it also involves the complexity of interrelated things in the kernel (there is always one more cleanup needed before the change) and interactions with the community (especially true as a newcomer).

    The problem: The in-kernel representation of inode timestamps was in struct timespec, which is not Y2038 safe. The proposed solution: Change the representation to struct timespec64, which is Y2038 safe.

    In January 2016, I posted the first request for comments (RFC) for this, asking if there was any opposition to the approach described above.

    I posted another series (actually three) for solving the problem in three separate ways.

    But we had to get rid of some old time interfaces before we could do the change. When I posted a series of this, Linus Torvalds did not like one of the interfaces (current_fs_time(sb)) because it took the superblock as an argument to access timestamp granularity. But the timestamps are really a feature of the inode, not the superblock. So, we got rid of this API.

    By the end of this whole exercise, we got rid of three in-kernel APIs, rearranged some of the filesystem timestamp handling, handled print formats to support larger timestamps, analyzed 32-bit architecture object dumps, and rewrote at least five versions of the series from scratch. And this was just one of the problems we solved for the kernel. But Y2038 has been one of my favorite projects yet.

    Reply
11. January 29, 2019 at 1:54 pm

    Tomi Engdahl says:

    2019 Will Be the Year of Open Source
    https://www.designnews.com/electronics-test/2019-will-be-year-open-source/174144007660005?ADTRK=UBM&elq_mid=7086&elq_cid=876648

    From software and even hardware, we saw more activity in open source than ever before in 2018. And the momentum isn’t likely to slow down in 2019.

    Reply
12. January 29, 2019 at 3:18 pm

    Tomi Engdahl says:

    Get Ready for Intelligent Real-Time Systems
    https://www.designnews.com/electronics-test/get-ready-intelligent-real-time-systems/17528569560076?ADTRK=UBM&elq_mid=7283&elq_cid=876648

    Intelligence is quickly making its way from the cloud to the edge. Now is the time to start understanding Intelligent Real-Time Systems.

    Intelligent Real-time Systems (IRS). Intelligent Real-time Systems are microcontroller-based devices that have the ability to learn to use data by running a resident, artificial intelligence algorithm (AI).

    There have always been two different ways that teams could leverage artificial intelligence in their products. The first, and the most realistic for the last decade, has been to execute the AI algorithms in the cloud. The cloud has provided a unique platform where processing power seems limitless when compared to the processing available on a microcontroller. Machine learning (ML) algorithms could be provided with data and trained to recognize patterns that would otherwise have been nearly impossible for a developer to program (think handwriting character recognition).

    Systems that use machine learning in the cloud can still use a real-time embedded system to collect data, but that data is then sent to the cloud for processing and any return-response then would be relayed back to the embedded system. As the reader can imagine, this is hardly a real-time or deterministic operation. Using the cloud, though, has worked and will continue to work in applications for the foreseeable future.

    The second approach, which has generally been out of reach for most systems, is to process the data and execute the machine learning algorithm on the microcontroller. This is a far more interesting solution because it removes latency that would otherwise exist if the data needs to be processed in the cloud. The potential for businesses here is huge for several different reasons such as:

    No longer requiring an internet connection which could reduce bill of material (BOM) costs and system complexity
    Decrease in operating costs for cloud services and data processing plans
    Offline product differentiation
    Reduction in processing latencies and energy consumption
    Improved product reliability and potentially security
    The use of machine learning in deterministic, real-time systems

    First, ARM has released CMSIS-NN, which is a C library designed for running low-level, optimized neural network algorithms on a Cortex-M processor. This allows developers to design and train their high-level machine learning algorithms and then deploy them onto a microcontroller. This can be considered the required foundation in order to run machine learning in an efficient manner, locally without the cloud.

    A great example is the OpenMV which is a camera module based on the STM32 and provides local processing for capabilities such as”

    Face detection
    Eye detection
    Color tracking
    Video recording
    Etc

    Machine vision is a leading intelligence capability that many real-time embedded systems will require.

    Reply
13. January 29, 2019 at 3:24 pm

    Tomi Engdahl says:

    Notes on Build Hardening
    https://blog.erratasec.com/2018/12/notes-on-build-hardening.html

    What is build safety?
    Modern languages (Java, C#, Go, Rust, JavaScript, Python, etc.) are inherently “safe”, meaning they don’t have “buffer-overflows” or related problems.

    However, C/C++ is “unsafe”, and is the most popular language for building stuff that interacts with the network. In other cases, while the language itself may be safe, it’ll use underlying infrastructure (“libraries”) written in C/C++. When we are talking about hardening builds, making them safe or security, we are talking about C/C++.

    In the last two decades, we’ve improved both hardware and operating-systems around C/C++ in order to impose safety on it from the outside. We do this with options when the software is built (compiled and linked), and then when the software is run.

    That’s what the paper above looks at: how consumer devices are built using these options, and thereby, measuring the security of these devices.

    In particular, we are talking about the Linux operating system here and the GNU compiler gcc. Consumer products almost always use Linux these days

    How software is built
    Software is first compiled then linked. Compiling means translating the human-readable source code into machine code. Linking means combining multiple compiled files into a single executable.

    Build Safety of Software in 28 Popular Home Routers
    https://cyber-itl.org/assets/papers/2018/build_safety_of_software_in_28_popular_home_routers.pdf

    For many, wireless access points and home routers are just commodity appliances. However,
    an insecure access point or router can be as damaging to a user’s security and privacy as an
    insecure web browser or document suite

    Reply
14. January 30, 2019 at 1:41 pm

    Tomi Engdahl says:

    Implementing an IoT Edge Device While Minimizing NRE
    https://www.mentor.com/tannereda/resources/overview/implementing-an-iot-edge-device-while-minimizing-nre-486621a5-f399-4641-8e3a-5a92a7ec9258?uuid=486621a5-f399-4641-8e3a-5a92a7ec9258&clp=1&contactid=1&PC=L&c=2019_01_29_ic_tanner_iotedge_device_nre_w

    One designer in a garage, a small startup, small to mid-size companies, and even small groups within large companies with a “startup attitude” are designing IoT edge devices. These designers need to keep non-recurring expense (NRE) down by using affordable design tools that are easy to use to quickly produce results and by minimizing IP and fabrication costs. Their goal is to deliver a functioning device to their stakeholders while spending as little money as
    possible to get there.

    Reply
15. January 31, 2019 at 12:12 pm

    Tomi Engdahl says:

    Shifting the Burden of Tool Safety Compliance from Users to Vendor
    https://semiengineering.com/shifting-the-burden-of-tool-safety-compliance-from-users-to-vendor/

    What safety-compliance strategies are used for tool classification and qualification in safety-critical hardware projects, focusing on ISO 26262, IEC 61508 and EN 50128.

    Reply
16. January 31, 2019 at 8:15 pm

    Tomi Engdahl says:

    Smoothsort Demystified
    http://www.keithschwarz.com/smoothsort/

    A few years ago I heard about an interesting sorting algorithm (invented by the legendary Edsger Dijkstra) called smoothsort with great memory and runtime guarantees.

    Reply
17. February 1, 2019 at 8:46 am

    Tomi Engdahl says:

    GitHub Helps Developers Keep Dependencies Secure via Dependabot
    https://www.securityweek.com/github-helps-developers-keep-dependencies-secure-dependabot

    Microsoft-owned GitHub informed developers on Thursday that they can easily ensure that the dependencies used by their applications are always secure and up to date through an integration of its Security Advisory API with Dependabot.

    Created by London-based developer Grey Baker, Dependabot is a management tool that helps GitHub users keep their dependencies up to date. The tool checks a user’s dependency files every day and creates pull requests in case an update is available. Users can manually review the requests and merge them, or they can configure Dependabot for automatic merger based on certain criteria.

    https://github.com/marketplace/dependabot

    Reply
18. February 1, 2019 at 1:03 pm

    Tomi Engdahl says:

    Using Memory Differently
    https://semiengineering.com/using-memory-differently/

    Optimizing complex chips requires decisions about overall system architecture, and memory is a key variable.

    What’s changed
    But with so much memory on the chip—in some cases it accounts for half the area of large SoCs—little changes can have a big impact. This is particularly true in AI applications, where small memories are often scattered around the chips with highly specific processing elements in order to process massive amounts of data more quickly. The challenge now is to minimize the movement of that data.

    “It has been through the emergence of the AI market and AI architectures that the idea of near-memory computing or in-memory computing has found its revival,” Macián said. “Once the idea was back on the table, people started looking at ways to use that same concept for things like RISC-V processors. Obviously, all processors have memories, and it has long been very important to select the right memories to obtain a good implementation of the processor in any die. We now have processor developers asking for memory that would perform some operation on the addresses before actually retrieving the data from the memory proper in order to simplify the circuitry around the memory. We are talking here about doing huge amounts of computation in the memory or near the memory, but with key elements, key operations that simplify greatly the logic around it.”

    What differentiates AI chips from other architectures is a relatively simple main computing element—the multiply accumulate (MAC) block. This block is parallelized and repeated thousands of times in an ASIC. Because of this replication, any small improvement made in the area or power, for example, has a huge overall effect in the chip, Macian explained.

    Reply
19. February 1, 2019 at 2:07 pm

    Tomi Engdahl says:

    Data Protection Laws Will Change How Electronics Systems are Designed
    https://www.eeweb.com/profile/loucovey/articles/data-protection-laws-will-change-how-electronics-systems-are-designed

    The handwriting is on the wall about what data breaches will cost in the next decade; it’s time for the hardware industry to get serious about dealing with this issue

    The advent of 5G cellular service is upon us (see “The 5G Future Begins Now!”). This is great news for the chip and electronic system industries and — possibly — outstanding news for the digital security industry.

    The potential for designing secure mobile services is tremendous. Much of the most effective technology is available today. The question is whether providers are willing to make the additional expense. So far, the answer is “No!” Communications providers are loath to make their services secure because doing so hasn’t been cheap, and it is much easier to pass the blame onto others — specifically, the users for their lax security. That changed in May of last year with the launch of the General Data Protection Regulation (GDPR) in the European Union, and things will become more expensive in California when the California Consumer Protection Act (CCPA) takes effect in 2020. Both laws are targeted at the usual suspects in the data collection domain — like social media and online retailers — so the hardware and software industries are not really thinking about it. They should be.

    Reply
20. February 15, 2019 at 9:28 am

    Tomi Engdahl says:

    Updating your safety critical product – a nightmare waiting to happen?
    https://www.mentor.com/embedded-software/resources/overview/updating-your-safety-critical-product-a-nightmare-waiting-to-happen–662fa66b-718a-4b79-b5b5-2a8633c76a28?uuid=662fa66b-718a-4b79-b5b5-2a8633c76a28&clp=1&contactid=1&PC=L&c=2019_02_14_esd_updating_safety_product_wp

    Almost all modern products include embedded software. Many of these products are targeted at safety critical applications, such as automotive, aerospace, and medical. The ability to update the embedded software in such products after shipments has significantly extended product life expectations. This in turn places increased requirements for long term software maintenance on the manufacturer.

    Reply
21. February 15, 2019 at 11:16 am

    Tomi Engdahl says:

    https://semiengineering.com/week-in-review-design-low-power-29/

    AdaCore says it is working with NVIDIA to implement Ada and Spark programming languages in some of NVIDIA’s security-critical firmware used in safety- and security-critical applications, such as automated and autonomous driving. NVIDIA is migrating some of its SoCs to the open-source RISC-V instruction set architecture and rewriting some of its security firmware from C to Ada and Spark.

    ANSYS announced its ANSYS Cloud to give its customers on-demand simulation and high-performance computing. Engineers can get high-fidelity simulation results and save time when evaluating design variations by using ANSYS’s Cloud. “ANSYS Cloud puts the power of on-demand hardware and software delivered from the cloud in the hands of ANSYS customers to tackle their largest simulation models and provide unprecedented insights into product designs,”

    Reply
22. February 15, 2019 at 12:16 pm

    Tomi Engdahl says:

    The Biggest Embedded Software Issue Is …
    Too many developers are writing software code without considering what could go wrong.
    https://www.designnews.com/electronics-test/biggest-embedded-software-issue/4835890360082?ADTRK=UBM&elq_mid=7413&elq_cid=876648

    There are many different problems and challenges that embedded software developers are facing today. One of the biggest and least spoken about issues that I have encountered is that developers are writing their software for success. Writing for success sounds great, except that what I mean is that developers are writing their software assuming that nothing will ever go wrong! What they are writing is functional prototype code that executes in a controlled, lab environment without issues. Don’t believe me? Let’s look at a publicly available example that I’ve recently encountered before discussing the failure mindset developers should be adopting.

    Reply
23. February 15, 2019 at 6:47 pm

    Tomi Engdahl says:

    Warnings Are Your Friend – A Code Quality Primer
    https://hackaday.com/2018/11/06/warnings-are-your-friend-a-code-quality-primer/

    Reply
24. February 15, 2019 at 6:56 pm

    Tomi Engdahl says:

    Software: It Is All In The Details
    https://hackaday.com/2019/01/06/software-it-is-all-in-the-details/

    Who’s the better programmer? The guy that knows 10 different languages, or someone who knows just one? It depends. Programming is akin to math, or perhaps it is that we treat some topics differently than others which leads to misconceptions about what makes a good programmer, mathematician, or engineer. We submit that to be a great programmer is less about the languages you know and more about the algorithms and data structures you understand.

    If you know how to solve the problem, mapping it to a particular computer language should be almost an afterthought. While there are many places that you can learn those things, there is a lot more focus on how to write the languages, C++ or Java or Python or whatever

    Reply
25. February 15, 2019 at 7:12 pm

    Tomi Engdahl says:

    Warnings On Steroids – Static Code Analysis Tools
    https://hackaday.com/2018/12/12/warnings-on-steroids-static-code-analysis-tools/

    Reply
26. February 15, 2019 at 7:16 pm

    Tomi Engdahl says:

    https://hackaday.com/2018/12/17/a-deep-dive-into-low-power-wifi-microcontrollers/

    Reply
27. February 24, 2019 at 3:34 pm

    Tomi Engdahl says:

    A subset of the Scheme dialect of Lisp running on CircuitPython. How meta.
    https://learn.adafruit.com/scheme-in-circuitpython?view=all

    Reply
28. March 1, 2019 at 10:26 am

    Tomi Engdahl says:

    Hyvää koodia on todella vähän
    http://www.etn.fi/index.php/13-news/9149-hyvaa-koodia-on-todella-vahan

    Reply
29. March 5, 2019 at 1:28 pm

    Tomi Engdahl says:

    Can Debug Be Tamed?
    Can machine learning bring debug back under control?
    https://semiengineering.com/bigger-debug-challenges-ahead/

    Debug consumes more time than any other aspect of the chip design and verification process, and it adds uncertainty and risk to semiconductor development because there are always lingering questions about whether enough bugs were caught in the allotted amount of time.

    Recent figures suggest that the problem is getting worse, too, as complexity and demand for reliability continue to rise. The big question now is whether new tool developments and different approaches can stem the undesirable trajectory of debug cost.

    Time spent in debug has been tracked by the Mentor, a Siemens Company and the Wilson Research Group over several years. The latest numbers, shown in Figure 1, reveal that the largest amount of an IC and ASIC verification engineer’s time—44%—is spent in debugging.

    Debug
    The removal of bugs from a design
    https://semiengineering.com/knowledge_centers/eda-design/verification/debug/

    Reply
30. March 5, 2019 at 1:31 pm

    Tomi Engdahl says:

    The Problem With Post-Silicon Debug
    https://semiengineering.com/the-problem-with-post-silicon-debug/

    Rising costs, tighter market windows and more heterogeneous designs are forcing chipmakers to rethink fundamental design approaches.

    Reply
31. March 5, 2019 at 1:33 pm

    Tomi Engdahl says:

    Open source software breaches surge in the past 12 months
    A simple lack of time is blamed for a lack of security governance in open-source projects.
    https://www.zdnet.com/article/open-source-software-breaches-surge-in-the-past-12-months/

    Security breaches related to open-source security projects are on the rise and a lack of time being made available to developers to resolve vulnerabilities is believed to be to blame.

    According to Sonatype’s DevSecOps Community Survey, in which over 5,500 IT professionals were asked to give their opinion on today’s open-source projects and the community’s security stance, open-source breaches have increased by 71 percent over the last five years.

    Reply
32. March 8, 2019 at 10:11 am

    Tomi Engdahl says:

    Debunking the Top Myths About Unsupported Linux for Embedded Development
    https://www.eetimes.com/document.asp?doc_id=1334334

    Reply
33. March 19, 2019 at 1:27 pm

    Tomi Engdahl says:

    A Brief History of Formal Verification
    https://www.eeweb.com/profile/adarbari/articles/a-brief-history-of-formal-verification

    As conventional simulation-based testing has increasingly struggled to cope with design complexity, strategies centered around formal verification have quietly evolved

    Reply
34. March 19, 2019 at 1:34 pm

    Tomi Engdahl says:

    Boeing’s B737 Max and Automotive ‘Autopilot’
    https://www.eetimes.com/author.asp?section_id=36&doc_id=1334444

    Why the catastrophic plane crashes of Indonesia’s Lion Air last October and another by Ethiopian Airlines last week should be setting off alarms in the automotive industry.

    Should the catastrophic plane crashes of Indonesia’s Lion Air last October and another by Ethiopian Airlines last week set off alarms in the automotive industry?

    Absolutely.

    Reply
35. March 19, 2019 at 1:38 pm

    Tomi Engdahl says:

    Debunking the Top Myths About Unsupported Linux for Embedded Development
    https://www.eetimes.com/document.asp?doc_id=1334334

    Embedded solution developers are often attracted to the “free” aspect of Linux and choose the RYO development route. However, an unsupported distribution might leave developers vulner­able to a wide range of hidden costs, risks, and time-consuming activities. This paper explores the top questions and myths about unsupported Linux for embedded applications.

    Reply
36. March 20, 2019 at 12:40 pm

    Tomi Engdahl says:

    MicroPython May Be Powering Your Next Embedded Device
    MicroPython has announced that their pyboard D-series modules are now available.
    https://www.designnews.com/electronics-test/micropython-may-be-powering-your-next-embedded-device/164173310860457?ADTRK=UBM&elq_mid=7879&elq_cid=876648

    MicroPython has been an interesting project to watch over the last few years. If you’ve not heard of it, MicroPython is an open source project to port Python to run in a real-time, microcontroller-based environment. The ports typically are for ARM Cortex-M processors but there are several ports that run other architectures from Microchip Technology Inc. and other vendors. There are several advantages to using MicroPython over a traditional programming language like C such as:

    Easy to learn (I’ve seen elementary students write Python code)
    It is object-oriented.
    Is an interpreted scripting language which removes compilation
    Supported by a robust community including many add-on libraries which minimizes re-inventing the wheel
    Includes error handling (something that C didn’t get the memo on)
    Easily extensible

    The Pyboard D-Series Module

    As of this week, MicroPython has announced that their pyboard D-series modules are now available. These modules are particularly interesting because they provide a MicroPython compatible microcontroller along with built-in Wi-Fi and Bluetooth that can be connected to a carrier board through a mezzanine connector as shown below in Figure 1. This overcomes the challenges that developers face with using MicroPython in a production environment that forced them spin their own MicroPython compatible boards since the pyboard D-series is a module.

    The first is their standard model which utilizes a STM32F722 microcontroller from STMicroelectronics N.V. to provide 256k RAM and 512k of internal flash.

    The second option available is the pyboard D-series high-performance module. This module is based on the STM32F767, which provides 512k of RAM and 2MB of internal flash for application scripts.

    Reply
37. March 20, 2019 at 12:42 pm

    Tomi Engdahl says:

    5 Techniques for Accelerating Engineering Development
    These techniques could help you get to market faster while reducing costs.
    https://www.designnews.com/electronics-test/5-techniques-accelerating-engineering-development/37355547060410?ADTRK=UBM&elq_mid=7879&elq_cid=876648

    Whether its a parts company, software supplier, or all the way to system integrators and even consultants, no one seems immunte to the ideas of decreasing costs and faster time to market, while improving product quality.

    Here are my top five techniques for accelerating engineering development. These five techniques are just a few examples of low-hanging fruit that companies and developers can consider when trying to accelerate engineering development.

    1.) Master Your Defects
    2.) Have the Right Tools for the Job
    3.) Focus on Your Value; Outsource the Rest
    4.) Leverage Existing Software Platforms
    5.) Leverage Existing Hardware Platforms

    Reply
38. March 20, 2019 at 1:51 pm

    Tomi Engdahl says:

    Boeing’s B737 Max and Automotive ‘Autopilot’
    https://www.eetimes.com/author.asp?section_id=36&doc_id=1334444

    Reply
39. March 21, 2019 at 12:55 pm

    Tomi Engdahl says:

    http://www.etn.fi/index.php/13-news/9245-c-on-ylivoimaisesti-suosituin-kieli-sulautetuissa

    Reply
40. March 21, 2019 at 12:56 pm

    Tomi Engdahl says:

    The Joy Of Properly Designed Embedded Systems
    https://hackaday.com/2019/03/20/the-joy-of-properly-designed-embedded-systems/

    The ages-old dream of home automation has never been nearer to reality. Creating an Internet of Things device or even a building-wide collection of networked embedded devices is “easy” thanks to cheap building blocks like the ESP8266 WiFi-enabled microcontroller. Yet for any sizable project, it really helps to have a plan before getting started. But even more importantly, if your plan is subject to change as you work along, it is important to plan for flexibility. Practically, this is going to mean expansion headers and over-the-air (OTA) firmware upgrades are a must.

    I’d like to illustrate this using a project I got involved in a few years ago, called BMaC, which grew in complexity and scope practically every month.

    https://github.com/MayaPosch/BMaC

    Reply
41. March 21, 2019 at 2:33 pm

    Tomi Engdahl says:

    http://www.etn.fi/index.php/13-news/9254-linux-on-ykkonen-sulautetuissa

    Reply
42. March 22, 2019 at 8:42 am

    Tomi Engdahl says:

    Accelerating Innovation with Embedded Motion Control
    https://www.eeweb.com/profile/trinamic-cb/articles/accelerating-innovation-with-embedded-motion-control

    Embedded motion controllers reduce multiple cycles of algorithm development, implementation, and testing to setting a few parameters and exporting the code to your own firmware

    What do self-driving cars, advanced 3D printers, and the next generation of “smart” prosthetic limbs have in common? They are all beneficiaries of the emergence of embedded motion-control technologies (see also “Three Trends Driving Embedded Motion Control”). These systems, which pair application-specific motion-control silicon with open hardware and software platforms, are part of the Fourth Industrial Revolution, a trend that is accelerating the rate of innovation for robotics, industrial automation, and even consumer products that use mechatronic technology.

    This new class of devices simplifies the development of mechatronic products by “encapsulating” most basic control functions as hardware logic or verified software building blocks that embedded developers can work with using the same rich toolsets and code libraries that they use for conventional applications. In addition to dramatically shortening development cycles, embedded motion controllers make it possible to add new capabilities to existing products while also facilitating the emergence of many new classes of products.

    Three Trends Driving Embedded Motion Control
    https://www.eeweb.com/profile/trinamic-cb/articles/three-trends-driving-embedded-motion-control

    Battery/low-power operation
    Living on the IoT
    Bringing motion control to consumer and commercial applications

    Conclusion
    Embedded motion control technology’s lower cost, compact form factor, and versatility is reducing the cost of control automation and other traditional industrial applications. These advantages have also made it possible for embedded motion control technology to address new application spaces in the commercial and industrial sectors, where developers face new demands and requirements such as battery operation, IoT capability, and shorter development cycles.

    Reply
43. March 22, 2019 at 9:27 am

    Tomi Engdahl says:

    The Joy Of Properly Designed Embedded Systems
    https://hackaday.com/2019/03/20/the-joy-of-properly-designed-embedded-systems/

    Reply
44. March 22, 2019 at 12:46 pm

    Tomi Engdahl says:

    IoT Is the Top Technology for Developers
    https://www.designnews.com/design-hardware-software/iot-top-technology-developers/111730606260481?ADTRK=UBM&elq_mid=7905&elq_cid=876648

    Of all the emerging technologies, product developers point to IoT as the most important, though security remains a challenge.

    According to a survey of developers by Avnet, IoT is cited most often as the most improved and the most important technology. This is followed by sensor technology, which is an integral part of IoT. Avnet surveyed 1190 members of its Hackster.io and Element 14 communities to find out how they’re focusing their development efforts and what challenges they’ve faced over the past year.

    Results from the survey include:

    26 percent of developers agree that IoT was the most improved technology over the past year. IoT also tops the list of most important technologies (37 percent), followed by sensors (24 percent).
    An overwhelming majority (81 percent) of developers working at startups say IoT security is a major roadblock when launching new products and services.
    One in 3 developers have recently looked for partners to help bring products to market. When looking for a partner, 76 percent of developers prefer the flexibility of choosing specialized expertise.

    IoT technology was cited by respondents as the most significant growth in importance, up 14 percent from last year, followed closely by drones and robotics projects, which were up 8 percent. More than a quarter of developers (26 percent) also noted that IoT is also the most improved technology of the past year, followed closely by artificial intelligence at 25 percent.

    Reply
45. March 23, 2019 at 3:03 pm

    Tomi Engdahl says:

    The 3 least secure programming languages
    https://www.techrepublic.com/article/the-3-least-secure-programming-languages/

    Here’s how the seven most widely-used coding languages stack up when it comes to the total open source security vulnerabilities per language, according to the report:

    C (47%)
    PHP (17%)
    Java (11%)
    JavaScript (10%)
    Python (5%)
    C++ (5%)
    Ruby (4%)

    C has the highest number of vulnerabilities out of these seven languages, accounting for nearly 50% of all reported vulnerabilities over the last 10 years, according to the report.

    Reply
46. March 23, 2019 at 3:04 pm

    Tomi Engdahl says:

    How to Write a Secure Code in C/C++ Programming Languages
    https://pentestmag.com/write-secure-code-cc-programming-languages/?fbclid=IwAR2lt0uw9sPRxEO9amJU25D90MRytboRXuB-BJXawVFm5SCOelKpygu5PbQ

    Secure coding in C/C++ programming languages is a big deal. The two languages, which are commonly used in a multitude of applications and operating systems, are popular, flexible, and versatile. However, these languages are inherently vulnerable to exploitation.
    Sometimes the solution is to code using a safer language like Java, that has suitable bounds-checking arrays and wonderful automatic garbage-collection feature. However, this is not always the best alternative, particularly if top performance is required or if C or C++ is preferred for developing the legacy code.
    Therefore, to avoid shooting yourself in the foot, it is important to learn how to create a bulletproof, un-exploitable code in the C/C++ programming languages.

    Reply
47. March 23, 2019 at 3:09 pm

    Tomi Engdahl says:

    Is One Programming Language More Secure Than The Rest?
    https://resources.whitesourcesoftware.com/blog-whitesource/is-one-language-more-secure

    focus our attention on some of the most popular languages in use in the open source community over the past few years: C, Java, JavaScript, Python, Ruby, PHP, and C++.

    Is One Programming Language More Secure Than The Rest?
    MARCH 19, 2019
    AYALA GOLDSTEIN
    which language is the most secure

    Want to liven up an open space full of software developers? Ask them what the best programming language is, and why. I think we all know that there is a high chance that lively debate will end with tears, rage, and broken friendships. Coders tend to take their programming languages very personally and in their battle to prove the dominance of their favorite language, the security card is often brought up.

    Feeling the right mixture of brave and curious, we decided to address the debate over which programming language is the most secure head-on, and being as we’re in the business of open source security, we decided to write our latest WhiteSource report about how some of the top programming languages measure up when it comes to their security.

    ANNUAL REPORT: THE STATE OF OPEN SOURCE VULNERABILITIES
    Download Full Report

    We dug through our open source vulnerabilities database, which aggregates information on open source vulnerabilities from multiple sources like the National Vulnerability Database (NVD), security advisories, GitHub and other popular open source projects issue trackers, to see if we could clearly crown one of the seven popular programming languages as the most secure.

    Searching For The Most Secure Programming Language
    First, we needed to decide which languages to take a closer look at. We managed to get through that potentially explosive debate by choosing to focus our attention on some of the most popular languages in use in the open source community over the past few years: C, Java, JavaScript, Python, Ruby, PHP, and C++.

    We scoured our database to see the number of known open source security vulnerabilities in each language over the past ten years, as well as the breakdown of these vulnerabilities’ severity over time. In addition, we checked to see which CWEs are most common for each language.

    Who Has The Most Vulnerabilities of Them All?
    When looking at the total of reported open source vulnerabilities for each of the seven languages over the past 10 years, C took the top spot with nearly 50% of all of the reported vulnerabilities.

    This is not to say that C is less secure than the other languages. The high number of open source vulnerabilities in C can be explained by several factors. For starters, C has been in use for longer than any of the other languages we researched and has the highest volume of written code. It is also one of the languages behind major infrastructure like Open SSL and the Linux kernel. This winning combination of volume and centrality explains the high number of known open source vulnerabilities in C.

    the percentage of critical vulnerabilities is declining in most of the languages covered in the report, except for JavaScript and PHP.

    Two CWEs reigned supreme and featured among the three most common 70% of the languages: Cross-Site-Scripting (XSS) also known as CWE-79 and Input Validation, otherwise known as CWE-20.

    Nearly all languages also have quite a few top ten CWEs in common. In addition to XSS and Input Validation, other CWEs that are were prominent across most languages are Information Leak/ Disclosure (CWE-200), Path Traversal (CWE-22), CWE-264 Permissions, Privileges, and Access Control, which is replaced in more recent years with its more specific close relative — Improper Access Control (CWE-284).

    WhiteSource

    Is One Programming Language More Secure Than The Rest?
    MARCH 19, 2019
    AYALA GOLDSTEIN
    which language is the most secure

    Want to liven up an open space full of software developers? Ask them what the best programming language is, and why. I think we all know that there is a high chance that lively debate will end with tears, rage, and broken friendships. Coders tend to take their programming languages very personally and in their battle to prove the dominance of their favorite language, the security card is often brought up.

    Feeling the right mixture of brave and curious, we decided to address the debate over which programming language is the most secure head-on, and being as we’re in the business of open source security, we decided to write our latest WhiteSource report about how some of the top programming languages measure up when it comes to their security.

    ANNUAL REPORT: THE STATE OF OPEN SOURCE VULNERABILITIES
    Download Full Report

    We dug through our open source vulnerabilities database, which aggregates information on open source vulnerabilities from multiple sources like the National Vulnerability Database (NVD), security advisories, GitHub and other popular open source projects issue trackers, to see if we could clearly crown one of the seven popular programming languages as the most secure.

    Searching For The Most Secure Programming Language
    First, we needed to decide which languages to take a closer look at. We managed to get through that potentially explosive debate by choosing to focus our attention on some of the most popular languages in use in the open source community over the past few years: C, Java, JavaScript, Python, Ruby, PHP, and C++.

    We scoured our database to see the number of known open source security vulnerabilities in each language over the past ten years, as well as the breakdown of these vulnerabilities’ severity over time. In addition, we checked to see which CWEs are most common for each language.

    Who Has The Most Vulnerabilities of Them All?
    When looking at the total of reported open source vulnerabilities for each of the seven languages over the past 10 years, C took the top spot with nearly 50% of all of the reported vulnerabilities.

    This is not to say that C is less secure than the other languages. The high number of open source vulnerabilities in C can be explained by several factors. For starters, C has been in use for longer than any of the other languages we researched and has the highest volume of written code. It is also one of the languages behind major infrastructure like Open SSL and the Linux kernel. This winning combination of volume and centrality explains the high number of known open source vulnerabilities in C.
    total reported open source vulnerabilities per language

    Open Source Security Vulnerabilities Per Language Over Time
    We then looked at the number of open source vulnerabilities over time. The data showed that every programming language had its own security highs and lows over the past ten years. However, there was one trend that stood out across all of the languages, and that’s the substantial rise in the number of known open source security vulnerabilities across all languages over the past two years. This rise can be explained by the rise in awareness of known security vulnerabilities in open source components, along with the continuously growing popularity of open source. As more resources have been invested in open source security research, the number of issues discovered has increased. The use of automated tools and the growing investment in bug bounty programs have further contributed to the sharp rise in the amount of disclosed open source security vulnerabilities.

    Open source vulnerabilities over time per language

    Open Source Vulnerabilities Over Time, per Language​

    Let’s Get Critical: High Severity Open Source Vulnerabilities Over Time
    When we took a closer look and focused on high severity open source security vulnerabilities (scores above 7 according to CVSS v2), we saw that the percentage of critical vulnerabilities is declining in most of the languages covered in the report, except for JavaScript and PHP.

    The decrease in the percentage of critical vulnerabilities could be a result of the concerted effort from security researchers to use automated tools to discover vulnerabilities in open source components. These tools are usually less capable of finding more complex and critical issues. While many of these tools are doing a good job of discovering vulnerabilities, many of the issues are not critical, and so we see a rise in the number of mostly medium vulnerabilities over the past few years in most of the programming languages that we studied.

    High Severity Open Source Security Vulnerabilities Over Time, per Language Over Time​

    What’s the CWE?: Most Common CWEs per Programming Language
    In order to learn as much as possible about each of the programming language’s strong and weak points security-wise, we also looked at the most common CWEs per language. Two CWEs reigned supreme and featured among the three most common 70% of the languages: Cross-Site-Scripting (XSS) also known as CWE-79 and Input Validation, otherwise known as CWE-20.

    Nearly all languages also have quite a few top ten CWEs in common. In addition to XSS and Input Validation, other CWEs that are were prominent across most languages are Information Leak/ Disclosure (CWE-200), Path Traversal (CWE-22), CWE-264 Permissions, Privileges, and Access Control, which is replaced in more recent years with its more specific close relative — Improper Access Control (CWE-284).

    And the Winner Of Most Secure Programming Language Is…No One and Everyone!
    While the game of “my programming language is safer than yours” is certainly a fun way to pass time, and the debate over the most secure programming language will often include some interesting points, finding the answer will probably not help you create the most innovative or secure software out there. Nor will it help you enjoy a secure and agile delivery of said innovation.

    Reply
48. March 24, 2019 at 9:26 am

    Tomi Engdahl says:

    Scott Shawcroft Is Squeezing Python Into Microcontrollers
    https://spectrum.ieee.org/at-work/tech-careers/scott-shawcroft-is-squeezing-python-into-microcontrollers

    As Python’s domination of the desktop and the cloud continues, two camps—MicroPython and CircuitPython—are working on hardware-centered versions of the interpreted language for embedded projects such as microcontroller-based gadgets.

    Reply
49. March 24, 2019 at 6:24 pm

    Tomi Engdahl says:

    Linus Torvalds “Nothing better than C”
    https://m.youtube.com/watch?v=CYvJPra7Ebk

    Reply
50. March 25, 2019 at 12:54 pm

    Tomi Engdahl says:

    Design for Reliability: How Stress Simulations Can Help
    https://www.eetimes.com/author.asp?section_id=36&doc_id=1334463

    A method for simulating stress and faults early in the design phase to aid in the “Design for Reliability” of a product.

    Reliability of a product is the probability for it to perform the intended functions without failure under stated conditions for a stated period of time. This number plays a pivotal role in the success of the product apart from other factors, such as efficiency, ease of use, etc. A product with poor reliability not only degrades the customer’s experience but also deteriorates the company’s reputation in addition to increased service and warranty costs.

    This blog introduces a method of simulating stress and faults early in the design phase to aid in the “Design for Reliability” of a product. This can be achieved by using an industry-proven multi-domain system design simulation software.

    The failure rate curve is comprised of three parts:

    1. Decreasing failure rate early in the life
    2. Constant failure rate during mid-life
    3. Increasing failure rate at the end of life

    Stress analysis

    Stress on a component is a measure of the ratio of the actual quantity (voltage/current/power/temperature) applied on it when it is placed in an electrical circuit to its maximum rating. For instance, if the power rating of a resistor is 0.25 watt and the actual power dissipation in it when connected in an electrical circuit is 0.20 watt, the stress on the resistor is 80%. This value is normally estimated based on the experience of the electric circuit and calculations, if available.

    Reply