Sometimes Bug Severity Isn't the Most Important Thing

Generally you need to take into account both the consequence of a software defect as well as how often it occurs when doing bug triage.  (See: Using a Risk Analysis Table to Categorize Bug Priority)

But an important special case is one in which the consequence is a business consequence such as brand tarnish rather than a spectacular software crash.   I used to use a hypothetical example of the audience's company name being misspelled on the system display to illustrate the point.  Well, it's not hypothetical any more!

Lamborghini sells a quarter-million dollar SUV with numerous software defects, including spelling the company name as "Lanborghini"   Guess which defect gets the press?

https://carbuzz.com/news/lamborghini-urus-experiencing-major-software-bugs

And it turns out that a software update not only didn't solve the typo, but also broke a bunch more functionality.  

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Different types of risk analysis: ALARP, GAMAB, MEMS and more

When we talk about how much risk is enough, it is common to do things like compare the risk to current systems, or argue about whether something is more (or less) likely than events such as being killed by lightning. There are established ways to think about this topic, each with tradeoffs.

The next time you need to think about how much risk is appropriate in a safety-critical system, try these existing approaches on for size instead of making up something on your own:

ALARP: "As Low As Reasonably Practicable"  Some risks are acceptable. Some are unacceptable. Some are worth taking in exchange for benefit, but if that is done the risk must be reduced to be ALARP.

GAMAB: "Globalement Au Moins Aussi Bon"  Offer a level of risk at least as good as the risk offered by an equivalent existing system. (i.e., no more dangerous than what we have already for a similar function)

MEM: "Minimum Endogenous Mortality"  The technical system must not create a significant risk compared to globally existing risks. For example, this should cause a minimal increase in overall death rates compared to the existing population death rates.

MGS: "Mindestens Gleiche Sicherheit"   (At least the same level of safety) Deviations from accepted practices must be supported by an explicit safety argument showing at least the same level of safety. This is more about waivers than whole-system evaluation.

NMAU: "Nicht Mehr Als Unvermeidbar"  (Not more than unavoidable)  Assuming there is a public benefit to the operation of the system, hazards should be avoided by reasonable safety measures implemented with reasonable cost.

Each of these approaches has pros and cons.  The above terms were paraphrased from this nice discussion:
Kron, On the evaluation of risk acceptance principles,
http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.455.4506&rep=rep1&type=pdf

There is an interesting set of slides that covers similar ground here, and works some examples. In particular the graphs involving whether risks are taken voluntarily for different scenarios is thought provoking:
http://agse3.informatik.uni-kl.de/teaching/suze/ws2014/material/folien/SRES_03_Risk_Acceptance.pdf

In general, if you want to dig deeper into this area, a search on
    gamab mem alarp 
will bring up a number of hits

Also note that legal and other types of considerations exist, especially regarding product liability.

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Using a Risk Analysis Table to Categorize Bug Priority

Perhaps the single most difficult thing to get right in a bug report is assigning a priority. It is tempting to assign a priority based on how spectacular the result is. But you also need to take into account how likely the bug is to manifest in a deployed system. For example, a bug that causes a system to crash and automatically reboot may be a lot more dramatic than a confusing screen message, but if that confusing screen message results in thousands of tech support calls, it could be a disaster for your company.  The best approach is one that combines severity and probability.

It is tempting to try to use fancy math to combine severity and probability. Usually that doesn't work out so well in practice. Instead, I recommend borrowing a technique from the safety critical system community. They use a Risk Table to assign a "criticality" to a particular adverse event as part of their Preliminary Hazard Analysis (PHA). You can use the same table in a different way and just say you are assigning bug "priority" instead of "risk."  Below is an example Risk Table:

Probability is your best estimate as to how often the bug will be seen in use. Consequence is how big a problem it will cause. The Risk (indicated by each box in the grid) is how big the risk is to product reputation -- which ought to be the same as the bug priority.  It helps to have clearly defined statements to guide assigning any particular bug to a row and to a column. Once you assign probability and consequence, the table tells you the priority of that particular bug.


You can modify this table to have 3 to 6 rows and 3 to 6 columns depending upon your needs (the table can be a rectangle rather than a square).  You can also modify the asymmetry of assigning risks as has been done in this example (consequence is weighted a bit higher than probability for this table by putting extra "Very High" boxes on the top row and so on). The point is not the table itself, but rather that binning things in this way makes assigning bug priority a lot easier for people to do in practice.

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Embedded Software Risk Areas -- Five Forbodes Failure

Series Intro: this is one of a series of posts summarizing the different red flag areas I've encountered in more than a decade of doing design reviews of industry embedded system software projects. You can read more about the study here. The results of this study inspired the chapters in my book.


To conclude these series of postings, here is an observation to ponder.

One of the informal observations made across the course of these reviews was that developer teams with exactly 5 primary contributors have the most spectacular project failures. Invariably these teams had previously completed a project with 3 or 4 members successfully, and increased the team size to tackle a more complex project without making any changes in their software process. But they failed with the new, 5-person team.

While this is an anecdotal result, projects that grow past 4 developers in size should seriously consider switching to a heavier weight software process (more paper, more formality, more methodical rigor). Smaller teams still seem to benefit from good process, but basically can get away with informality with less dramatic risks than larger teams (5 or more developers) working on more complex projects.

Does this mean with fewer than 5 people you can simply ignore all the risk areas I've posted? No. Most of the reviews (perhaps 80%) were conducted on teams with fewer than 5 people. What this does mean is that with only one or a few developers you can get away with a lot and only have a few red flag risk areas. If you are lucky you will survive them, and if you are unlucky they will bite you. Hard. But most of the time you will slide by well enough that you will work nights, weekends, and have no social life -- but you will still have a job.

But, if you have more than 5 people you probably have to do most or even all of the process activities listed in these risk areas. If you blow off using a rigorous process, it is pretty likely you will fail. Probably you will fail spectacularly.

At least this is what I have observed doing 95 reviews over 10 years in industry.  Your mileage may vary.

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Embedded Software Risk Areas -- People

Series Intro: this is one of a series of posts summarizing the different red flag areas I've encountered in more than a decade of doing design reviews of industry embedded system software projects. You can read more about the study here. If one of these bullets applies to your project, you should consider whether that presents undue risk to project success (whether it does or not depends upon your specific project and goals). The results of this study inspired the chapters in my book.

Here are the People red flags:

• High turnover and developer overload

Developers have a high turnover rate. As a result, code quality and style varies. Lack of a robust paper trail makes it difficult to continue development. Often more important is that replacement developers may lack the domain experience necessary for understanding the details of system requirements.

• No training for managing outsource relationships

Engineers who are responsible for interacting with outsource partners do not have adequate time and skills to do so, especially for multi-cultural partnering. This can lead to significant ineffectiveness or even failure of such relationships.

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Embedded Software Risk Areas -- Project Management -- Part 2

Series Intro: this is one of a series of posts summarizing the different red flag areas I've encountered in more than a decade of doing design reviews of industry embedded system software projects. You can read more about the study here. If one of these bullets applies to your project, you should consider whether that presents undue risk to project success (whether it does or not depends upon your specific project and goals). The results of this study inspired the chapters in my book.

Here are some of the Project Management red flags (part 2 of 2):

• Schedule not taken seriously

The software development schedule is externally imposed on an arbitrary basis or otherwise not grounded in reality. As a result, developers may burn out or simply feel they have no stake in following development schedules.

• Presumption in project management that software is free

Project managers and/or customers (and sometimes developers) make decisions that presume software costs virtually nothing to develop or change. This is one contributing cause of requirements churn.

• Risk of problems with external tools and components

External tools, software components, and vendors are a critical part of the system development plan, and no strategy is in place to deal with unexpected bugs, personnel turnover, or business failure of partners and vendors.

• Disaster recovery not tested

Backups and disaster recovery plans may be in place but untested. Data loss can occur if backups are not being done properly.

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Embedded Software Risk Areas -- Project Management -- Part 1

Series Intro: this is one of a series of posts summarizing the different red flag areas I've encountered in more than a decade of doing design reviews of industry embedded system software projects. You can read more about the study here. If one of these bullets applies to your project, you should consider whether that presents undue risk to project success (whether it does or not depends upon your specific project and goals). The results of this study inspired the chapters in my book.

Here are some of the Project Management red flags (part 1 of 2):

• No version control

Sometimes source code is not under version control. More commonly, the source code is under version control but associated tools, libraries, and other support software components are not. As a result, it may be difficult or impossible to recreate and modify old software versions to fix bugs.

• No backward compatibility and version management plan

There is no plan for dealing with backward compatibility with old products, product migration, or installations with a mix of old and new product versions. The result may be incompatibilities with fielded equipment or a combinatorial explosion of multi-component compatibility testing scenarios necessary for system validation.

• Use of cheap tools (software components, etc.) instead of good ones

Developers have inadequate or substandard tools (for example, free demo compilers instead of paid-for full-featured compilers) because tool costs can’t be reckoned against savings in developer time in the cost accounting system being used. As a result, developers spend significant time creating or modifying tools to avoid spending money on tool procurement.

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Embedded Software Risk Areas -- An Industry Study

I've had the opportunity to do many design reviews of real embedded software projects over the past decade or so.  About 95 reviews since 1996. For each review I usually had access to the project's source code and design documentation.  And in most cases I got to spend a day with the designers in person. The point of the reviews was usually identifying risk areas that they should address before the product went into production. Sometimes the reviews were post mortems -- trying to find out what caused a project failure so it could be fixed. And sometimes the reviews were more narrow (for example, just look at security or safety issues for a project). But in most cases I (sometimes with a co-reviewer) found one or more "red flag" issues that really needed to be addressed.

In other postings I'll summarize the red flag issues I found from all those reviews. Perhaps surprisingly, even engineers with no formal training in embedded systems tend to get the basics right. The books that are out there are good enough for a well trained non-computer engineer to pick up what they need to get basic functionality right most of the time. Where they have problems are in the areas of complex system integration (for example, real time scheduling) and  software process. I'm a hard-core lone cowboy techie at heart, and process is something I've learned gradually over the years as that sort of thing proved to be a problem for projects I observed. Well, based on a decade of design reviews I'm here to tell you that process and a solid design methodology matters. A lot. Even for small projects and small teams. Even for individuals. Details to follow in upcoming posts.

I'm giving a keynote talk at an embedded system education workshop at the end of October. But for non-academics, you'd probably just like me to summarize what I found:

(The green bar means it is things most embedded system experts think are the usual problems -- they were still red flags!) In other words, of all the red flag issues identified in these reviews, only about 1/3 were technical issues. The rest were either pieces missing from the software process or things that weren't being written down well enough.

Before you dismiss me as just another process guy who wants you to generate lots of useless paper, consider these points:

• I absolutely hate useless paper. Seriously!  I'm a techie, not a process guy. So I got dragged kicking and screaming to the conclusion that more process and more paper help (sometimes).

• These were not audits or best practice reviews. What I mean by that is we did NOT say "the rule book says you have to have paper of type X, and it is missing, so you get a red flag." What we DID say, probably most of the time, was "this paper is missing, but it's not going to kill you -- so not a red flag."  Only once in a while was a process or paperwork problem such high risk that it got a red flag.

• Most reviews had only a handful of red flags, and every one was a time bomb waiting to explode. Most of the time bombs were in process and paperwork, not technology.

In other postings (click here to see the list as it grows) I'll summarize the 43 areas that had red flags (yes, including the technology red flags). They'll be organized, loosely, by phase in the design cycle. No doubt you have seen some project-killer risks that aren't on the lists, and I welcome brief war story postings about them.

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Embedded Software Risk Areas -- Dependability -- Part 2

Series Intro: this is one of a series of posts summarizing the different red flag areas I've encountered in more than a decade of doing design reviews of industry embedded system software projects. You can read more about the study here. If one of these bullets applies to your project, you should consider whether that presents undue risk to project success (whether it does or not depends upon your specific project and goals). The results of this study inspired the chapters in my book.

Here are some of the Dependability red flags (part 2 of 2):

• Insufficient consideration of system reset approach

System resets might not ensure a safe state during reboots that occur when the system is already in operation, resulting in unsafe transient actuator commands.

• Neither run-time fault instrumentation nor error logs

There is no run-time instrumentation to record anomalous operating conditions, nor are there error logs to record events such as software crashes. This makes it difficult to diagnose problems in devices returned from customers.

• No software update plan

There is no plan for distributing patches or software updates, especially for systems which do not have continuous Internet access. This can be an especially significant problem if the security strategy ends up requiring regular patch deployment. Updating software may require technician visits, equipment replacement, or other expensive and inconvenient measures.

• No IP protection plan

There is no plan to protect the intellectual property of the product from code extraction, reverse engineering, or hardware/software cloning. (Protection strategies can be legal as well as technical.) As a result, competitors may find it excessively easy to successfully extract and sell products with exact software images or extracted proprietary software technology.

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Embedded Software Risk Areas -- Dependability -- Part 1

Series Intro: this is one of a series of posts summarizing the different red flag areas I've encountered in more than a decade of doing design reviews of industry embedded system software projects. You can read more about the study here. If one of these bullets applies to your project, you should consider whether that presents undue risk to project success (whether it does or not depends upon your specific project and goals). The results of this study inspired the chapters in my book.

Here are some of the Dependability red flags (part 1 of 2):

• No or incorrect use of watchdog timers

Watch dog timers are turned off or are serviced in a way that defeats their intended role in the system. For example, a watchdog might be kicked by an interrupt service routine that is triggered by a timer regardless of the status of the rest of the software system. Systems with ineffective watchdog timers may not reset themselves after a software timing fault.

• Insufficient consideration of reliability/availability

There is no defined dependability goal or approach for the system, especially with respect to software. In most cases there is no requirement that specifies what dependability means in the context of the application (e.g., is a crash and fast reboot OK, or is it a catastrophic event for typical customer?). As a result, the degree of dependability is not being actively managed.

• Insufficient consideration of security

There is no statement of requirements and intentional design approach for ensuring adequate security, especially for network-connected devices. The resulting system may be compromised, with unforeseen consequences.

• Insufficient consideration of safety

In some systems that have modest safety considerations, no safety analysis has been done. In systems that are more overtly safety critical (but for which there is no mandated safety certification), the safety approach falls short of recommended practices. The result is exposure to unforeseen legal liability and reputation loss.

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Embedded Software Risk Areas -- Verification & Validation

Series Intro: this is one of a series of posts summarizing the different red flag areas I've encountered in more than a decade of doing design reviews of industry embedded system software projects. You can read more about the study here. If one of these bullets applies to your project, you should consider whether that presents undue risk to project success (whether it does or not depends upon your specific project and goals). The results of this study inspired the chapters in my book.

Here are the Verification and Validation red flags:

• No peer reviews

Code, requirements, design and other documents are not subject to a methodical peer review, or undergo ineffective peer reviews. As a result, most bugs are found late in the development cycle when it is more expensive to fix them.

• No test plan

Testing is ad hoc, and not according to a defined plan. Typically there is no defined criterion for how much testing is enough. This can result in poor test coverage or an inconsistent depth of testing.

• No defect tracking

Defects and other issues are not being put into a bug tracking system. This can result in losing track of outstanding bugs and poor prioritization of bug-fixing activities.

• No stress testing

There is no specific stress testing to ensure that real time scheduling and other aspects of the design can handle worst case expected operating conditions. As a result, products may fail when used for demanding applications.

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Embedded Software Risk Areas -- Implementation -- Part 2

Series Intro: this is one of a series of posts summarizing the different red flag areas I've encountered in more than a decade of doing design reviews of industry embedded system software projects. You can read more about the study here. If one of these bullets applies to your project, you should consider whether that presents undue risk to project success (whether it does or not depends upon your specific project and goals). The results of this study inspired the chapters in my book.

Here are some of the Implementation red flags (part 2 of 2):

• Ignoring compiler warnings

Programs compile with ignored warnings and/or the compilers used do not have robust warning capability. A static analysis tool is not used to make up for poor compiler warning capabilities. The result can be that software defects which could have been caught by the compiler must be found via testing, or miss detection entirely. If assembly language is used extensively, it may contain the types of bugs that a good static analysis tool would have caught in a high level language.

• Inadequate concurrency management

Mutexes or other appropriate concurrent data access approaches aren’t being used. This leads to potential race conditions and can result in tricky timing bugs.

• Use of home-made RTOS

An in-house developed RTOS is being used instead of an off-the-shelf operating system. While the result is sometimes technically excellent, this approach commits the company to maintaining RTOS development skills as a core competency, which may not be the best strategic use of limited resources.

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Embedded Software Risk Areas -- Implementation -- Part 1

Series Intro: this is one of a series of posts summarizing the different red flag areas I've encountered in more than a decade of doing design reviews of industry embedded system software projects. You can read more about the study here. If one of these bullets applies to your project, you should consider whether that presents undue risk to project success (whether it does or not depends upon your specific project and goals). The results of this study inspired the chapters in my book.

Here are some of the Implementation red flags (part 1 of 2):

• Inconsistent coding style

Coding style varies dramatically across the code base, and often there is no written coding style guideline. Code comments vary significantly in frequency, level of detail, and type of content. This makes it more difficult to understand and maintain the code.

• Resources too full

Memory or CPU resources are overly full, leading to risk of missing real time deadlines and significantly increased development costs. An extreme example is zero bytes of program and data memory left over on a small processor. Significant developer time and energy can be spent squeezing software and data to fit, leaving less time to develop or refine functionality.

• Too much assembly language

Assembly language is used extensively when an adequate high level language compiler is available. Sometimes this is due to lack of big enough hardware resources to execute compiled code.  But more often it is due to developer preference, reuse of previous project code, or a need to economize on purchasing development tools. Assembly language software is usually more expensive to develop and more bug-prone than high level language code.

• Too many global variables

Global variables are used instead of parameters for passing information among software modules. The result is often code that has poor modularity and is brittle to changes.

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