We’re back from our short break, with a fantastically interesting episode:
In 1989, a message was found in a virus: “Eddie Lives…Somewhere in Time!”. ‘Eddie’ was a particularly nasty virus, and its discovery led a young Bulgarian security researcher down a rabbit hole, on a hunt for the prolific creator of the Eddie virus: The Dark Avenger.
After describing the Software Crisis in the previous episode, we discuss the various methodologies and practices implemented over the years to combat the complexities of software development. We’ll tell the sad story of the FBI’s VCF project – perhaps the most expensive failed software project ever – and hear about Dr. Fred Brooks’ classic book, ‘The Mythical Man-Month’.
In this episode, we’re continuing our discussion about the Software Crisis, which we introduced last week. If you missed that episode, you might want to go back and have a read before listening to this one.
The question we asked was: why do so many large software projects fail so often? THAT is the Software Crisis, a term that was first coined in 1968.
“Failure”, in the context of software, has many aspects: software projects tend to deviate from schedule and budgets, produce software that does not meet the customer’s specs or expectation – and often contains a significant number of errors and bugs. It is a question that troubled many engineers and computer scientists over the years: what makes software so complicated to engineer?
The solutions to this problem changed over the years, along with changes in the business culture of the High Tech world.
The Waterfall Methodology
In the 1960s, The dominant approach to software development – especially when it came to complicated projects – was known as the “Waterfall” methodology. This approach divides the software projects into well-defined stages: first, the customer defines the requirements for the product. A software architect – usually an experienced programmer – creates the outline of the system that fits these requirements, and then a team of programmers writes the actual code that fits this outline. In essence, the Waterfall approach is the same approach a carpenter would use when creating a new piece of furniture: Learn what the customer wants, draw a schematic outline of the product, measure twice – and cut once.
The name “Waterfall” hints at the progression between stages: a new stage in the project will begin only when the last one is complete, just like water flowing down a waterfall. You can’t start writing code until the client has defined their needs and wants. Seems like a sensible approach, and indeed the Waterfall methodology served engineers outside of the software industry for hundreds of years. Why shouldn’t it be used here as well?
But in the last twenty years, the “Waterfall” method has been under constant and profound criticism, coming from software developers and business leaders. The main argument against Waterfall is that even though it served other engineering disciplines, from architecture to electronics – it is not well-suited to the software field.
And why is that? Let’s examine this question through an example which is, most likely, one of the most expensive failures in the history of software engineering.
VCF – Virtual Case File
In the year 2000, the FBI decided to replace its entire computer system and network. Many of the agency’s computers were old and outdated and had no longer suited the needs of agents and investigators. Some of the computers still used 1980s green screens and didn’t even support using a mouse…After September 11th, FBI agents had to fax photos of suspects because the software they used couldn’t attach a document to their e-mails! It can’t get much worse than that…
Finally, at the end of that year, Congress approved a budget of four hundred million dollars for upgrading the FBI computer system and network. The project was supposed to take three years, and replace all computer stations with modern and capable machines, connected via a fast optic cable network system.
The crowning glory of the new system was a software called VCF, for “Virtual Case File”. VCF was supposed to allow agents at a crime scene to upload documents, images, audio files, and any other investigation material to a central database, in order to cross-reference information on suspects that they could later present in court. The company hired to write the advanced software was called SAIC.
The FBI Goes Waterfall
It’s important to note that the FBI has hundreds of thousands of people, and as most large organizations – it tends to be very bureaucratic and conservative. Naturally, the preferred methodology for the VCF project was the Waterfall, and so the project managers begun by writing an eight hundred page long document that specified all the requirements from the new software. This document was extremely detailed, with sentences like: “In such and such screen, there will be a button on the top left corner. The button’s label will read – ‘E-Mail’.” They didn’t leave the developers a lot of room for questions…
But in an organization as huge and varied as the FBI, it’s doubtful that there is one person, or even one group, who understands the practical daily needs of all the departments and groups for which the program was written. As the project progressed, it became clear that the original requirements didn’t meet the day-to-day needs of agents.
So, special groups were assigned to study the needs of the agents in the field, and they constantly updated the project’s requirements. As you might imagine, the constant changes made the requirements document almost irrelevant to the developers in SAIC who actually wrote the code. The events of September 11th gave the project a new sense of urgency, and the tight schedule soon created conflicts between the programmers and FBI management. The software developers were frustrated over the ever-changing requirements, while FBI agents felt their needs were being ignored.
A Dramatic Failure
Things got worse and worse, and by the beginning of 2003, it was clear that the new software wouldn’t be ready on time. Since the VCF project was deemed a matter of importance to national security, Congress approval an additional budget of two hundred million dollars. But that didn’t help either.
In December of 2003, a year after it was supposed to be ready, SAIC finally released the VCF’s first version. The FBI rejected it almost immediately! Not only was the software buggy and error-prone, it also lacked basic functions like “bookmarking” and search history. It was totally inadequate for field or office work.
In an effort to save the failing project, the FBI invited a committee of outside experts to consult the agency. One of the committee members, Professor Matt Blaze, later said that he and his colleagues were shocked once they analyzed the software. He jokingly told a reporter later, quote, “That was a little bit horrifying. A bunch of us were planning on committing a crime spree the day they switched over. If the new system didn’t work, it would have just put the FBI out of business.”
In January 2005, the head of the FBI decided to abandon the project. This wasn’t an easy decision since it meant that all the agency’s personnel would have to continue using the ancient computers from the 1980s and 90s for at least five more years. This had a sizeable impact on national security, not to mention all that money that was spent for nothing.
Why Did VCF Fail?
The VCF project failed even though the FBI used the age old approach of “measure twice, cut once”. It defined all the software requirements up front, and left nothing to chance – or so it seemed. Critics of the Waterfall methodology claim that the problem was that the FBI was never able to define its needs perfectly, or even adequately. In such a complex and big organization, defining all the software requirements up front is an almost hopeless task, since no single person knows everything that’s going on in the organization and also has a good grasp of what the technology can and can’t do.
The FBI’s VCF fiasco is typical, it seems, for large-scale software projects. I recently had a chance to speak with a very experienced programmer who has worked on a different large scale project.
“My name is Aviran Mordo, I’m the Head of Engineering for Wix.com. I’ve been working in the software industry for over twenty years, from startup companies here in Israel to developing the US National Archives.
“So working on a government project is everything that you hear that is wrong with Software Development, like Waterfall and long processes. We tried to be as Agile as we can, and during the prototyping phase, we actually succeeded – that is why we won the project. But when we started the actual writing of the project, hundreds of people came and worked on humongous documents that nobody read, and built this huge architecture with very very long processes. You could see that this is going to take a long time, and the project just suffered so badly… That was the point that I switched to a smaller team, to do that on the civilian market. We were just five people. We started about six months after the big project started. We were five people against a hundred people. After six months we were a year ahead of their development schedule.”
“They actually had to restart the project twice. [Ran: when you’re saying ‘restart’ you mean they just developed everything from the beginning?] Yes, they had to develop everything from the beginning. The architecture, everything. “
I asked Aviran why, in his opinion, the Waterfall methodology – which does a great job in other engineering disciplines – fails so miserably in software engineering.
“Several Things. One, you do the architecture up front and think you have all the answers. If you don’t have all the answers, you plan for the things you don’t actually know. So you build a lot of things that are wasting your time for future features that you think may affect the product or for requirements that may change in the future – but since the release cycle is so long, and it costs so much to do a new version, you try to cramp up as many features as you can into a project. This derails you from whatever really need to be achieved and have a quick feedback from the market and from the client. [it’s] A waste of time.”
Aviram’s view is echoed by many other developers, including the ones who investigated the failed FBI project. Waterfall assumes you have all the information you need before the project begins. As we already saw, software projects tend to be so complex, that this assumption is often wrong.
The Agile Methodology
So in the 1990s and early 2000s, an alternative to the unsuccessful Waterfall methodology appeared: its name was Agile Programming. The Agile methodology is almost the exact opposite of Waterfall: it encourages maximum flexibility during the development process. The strict requirement documents are abandoned in favor of constant and direct communication with the client.
Say, for example, that the customer wants an email client. The developers work for a week or two, and create a rough skeleton of the software: it might have just the very basic functions, or maybe just buttons that don’t do anything yet. They show the mockup to the customer, who then gives them his feedback: that button is good, that one is wrong, etc. The developers work on the mockup some more, fixing what needs to be fixed and maybe adding a few more features. There’s another demonstration and more feedback from the customer. This process repeats itself over and over until the software is perfected. Experience shows that projects developed using the Agile methodology are much less prone to failure: this is because the customers have ample time and opportunity to understand their true needs and “mold” the software to fit.
Not A Perfect Solution
So, is Agile the solution for the software crisis? Well, Probably not. Aviran, Wix’s Head of Engineering says that Agile is not suited for every kind of software project.
“It’s harder to plan ahead what’s the end goal. This [Agile] works well for a product which is innovative but it won’t work well for a product which is revolutionary. For example, the iPhone. The iPhone cannot work this way – it’s a really huge project with a lot of things in it, and it revolutionized the market. It could be developed with Agile, but you miss the step of getting it in front of your customer. So if you’re doing something which is ‘more of the same’ or you’re not trying to change the market – Agile works extremely well. If you’re trying to change the market and do something revolutionary, you could do Agile to some extent until you actually get to market.”
Also, Agile has been around for twenty years – and large-scale projects do still fail all around us. It is a big improvement over Waterfall, no doubt, but it probably won’t solve the software crisis.
So, what is the solution? Maybe a new and improved methodology? A higher-level programming language?
Dr. Frederick Brooks
One of the many computer scientists who tried to tackle this question was Dr. Frederick Brooks. In the 1960s and 70s Brooks managed some of IBM’s most innovative software projects – and naturally suffered some failures himself. Prompt by his own painful experiences, Brooks wrote a book in 1975 called “The Mythical Man-Month”. A “Man-Month” is a sort of a standard work-unit in a software project: the work an average programmer does in a single month.
Brooks’ book, and another important article he published called “No silver bullet”, influenced a whole generation of software programmers and managers. In his writings, Brooks analyzed the main differences between the craft of software writing and other engineering disciplines, focusing on what he perceived to be the most critical and important characteristic of software: its complexity.
Brooks claims there is no such thing as a “simple software”. Software, he writes, is a product of the human thinking process, which is unique to every individual. No two developers will write the exact same code, even if they are faced with the exact same problem. Each piece of software is always unique since each brain is unique. Imagine a world where each and every clock has its own unique clockwork mechanism. Now imagine a clockmaker trying to fix these clocks: each and every clock he opens is different from the rest! The levers, the tiny screws, the springs – there’s no uniformity. A new clock, a whole new mechanism. This uniqueness would make clock-fixing a complex task that requires a great deal of expertise – and that’s the same situation with software.
Now, high complexity can be found in other engineering disciplines – but we can almost always find ways to overcome it. Take electronic circuits, for example: in many cases, it is possible to overcome complexity by duplicating identical sub-circuits. You could increase a computer’s memory capacity by adding more memory cells: you’ll get an improved computer but the design’s complexity would hardly change since we’re basically just adding more of the same thing. Sadly, that’s often not true for software: each feature you add to a piece of software is usually unique.
What about architecture? Well, architects overcome the complexities of their designs by creating good schematics. Humans are generally good at working with drawings: an architect can open the schematics, take a quick look, and get a fairly good idea of what’s going on in the project. But software development, explains Brooks, does not allow such visualization. A typical software has both a dimension of time – that is, do this, then do that – and a dimension of space, such as moving information from one file to another. A diagram can usually represent only a single dimension, and so can never capture the whole picture. Imagine an architectural schematic that tries to capture both the walls and levels of a building – and the organizational structure of the company that will populate it… many times a software programmer is left with no choice but to build a mental model of the entire project he is working on; or if it is too complex, parts of it.
In other words, Brooks argues that unlike electronics or architecture, it is impossible to avoid the “built-in” complexity of software. And if this is true, then computer software will always contain bugs and errors, and large projects will always have a high risk of failure. There is no “Silver Bullet” to solve the Software Crisis, says Brooks.
But you might be asking – what about high-level languages? As we learned in the previous episode, advanced software languages like FORTRAN, C, and others greatly improved a programmer’s ability to tackle software complexity. They made programming easier, even suitable for kids. Isn’t is possible that in the future someone will invent a new, more successful programming language that would overcome the frustrating complexity of software?
The answer, according to Brooks, is no. High-level languages allow us to ignore the smaller details of programming and focus on the more abstract problems, like thinking up new algorithms. In a way, they remove some of the barriers between our thought processes and their implementation in the computer. But since software complexity is a direct result of our own thought processes, the natural complexity of the human mind – a higher level language will not solve the software crisis.
But Fredrik Brooks does have a rather simple solution – one which might solve the problems of most companies. His suggestion: don’t write software – buy it!
Purchasing software, says Brooks, will always be cheaper and easier than developing it. After all, buying Microsoft’s Office suite takes minutes, while developing it from scratch might take years – and fail. True, a purchased one-size-fits-all software will never meet all the organization’s needs – but it’s often easier to adjust to an existing software then create a new one. Brooks uses salary calculation software to illustrate his point: in the 1960s, most companies preferred writing custom software to handle their salary calculation. Why? Because back then, a computer system cost millions of dollars while writing software only a few tens of thousands. The costs of customized software seemed reasonable when compared to the cost of the hardware. Nowadays, however, computers cost just a few thousand dollars – while large-scale software projects cost millions. Therefore, almost all organizations learned to compromise and purchase standard office software such as “Excel” and “Word”. They adjusted their needs to fit the available, ready-made, software.
Brooks gave another piece of advice, this time to the software companies themselves: nurture your developers! Some brains are better suited to handle the natural complexity of software development. Just as with sports and music, not all people are born equally talented. There are “good programmers” – and then there are “outstanding programmers”. Brooks’ experience taught him that a gifted programmer will create software that is ten times better than the one made by an average programmer”. Software companies should try and identify these gifted individuals early in their careers, and nurture them properly: assign them good tutors, invest in their professional education, and so on. That kind of nurturing isn’t cheap – but neither is a failed software project.
To summarize, we started by asking whether software bugs and errors are inevitable – or can we hope to eliminate them sometime in the future. Digging deeper, we discovered an even more fundamental problem: large-scale software projects not only have plenty of bugs – they also tend to fail spectacularly. This is known as the Software Crisis.
Modern software development methodologies such as Agile can sometimes improve the prospects of large-scale projects – but not always, and not completely. The only real solution, at least according to Dr. Fredrick Brooks, is finding developers who are naturally gifted at handling the complexities of software – and helping them grow to their full potential. And until we find the Silver Bullet that will solve the Software Crisis, we’ll just have to…well – bite the bullet.
Software errors and random bugs are rather common: We’ve all seen the infamous Windows “blue screen of death”… But is there really nothing we can do about it? Are these errors – from small bugs to catastrophic mistakes – inevitable? In this episode, we’ll tell the story of FORTRAN, the groundbreaking high-level computer language, and the sad, sad tale of the Denver Airport Baggage Disaster. Don’t laugh, it’s a serious matter.
A car that breaks once every few weeks is simply unacceptable. We expect our cars to have a certain level of reliability. But when it comes to computers – software errors and random bugs are rather common. We’ve all seen the infamous Windows “blue screen of death”, and most smartphones require a reboot every once in awhile.
In a way, we’ve learned to live with software errors and take them for granted. But is there really nothing we can do about it? Are these errors – from small bugs to catastrophic mistakes – inevitable, or is there hope that as technology and innovation move forward, we’ll be able to overcome this annoying problem – and make software bugs a thing of the past? This will be the main question of this episode.
How Software Works
Software bugs are nothing new, of course. Writing computer software in the 1940s and 50s was a complicated and difficult task, so it’s no wonder that the first generation of computer programmers considered bugs and errors inevitable.
But let’s start from the basics, with a quick refresher on how computer software works. A computer is a pretty complex system, and its two main parts are the processor and the memory. The memory cells contain numbers; the processor’s role is to read a number from the memory, apply some sort of a mathematical operation on it such as adding or subtracting and then write the result back to the memory.
A software is a sequence of commands telling the processor where certain information is located in the memory and what needs to be done with it. Think of the information in a computer’s memory as food ingredients: the software is the recipe. It tells us what we need to do with the different ingredients at every given moment. A software error is an error in the sequence of commands. It might be a missing command, two commands given in the wrong order, or an altogether wrong command.
Just Plain Numbers
So why were software bugs seen as a fact of life back in the 1950s? Back then, both information and commands were given not as words – bus as plain numbers. For example, the numeral forty-two might represent the command “copy,” so that the sequence 42-11-56 might represent an action like: “copy the content of memory cell eleven to memory cell fifty-six.” Even a mildly complicated calculation, like solving a mathematical equation, might require hundreds – if not thousands – of such command sequences. Each such sequence had to be perfectly correct, or else the entire calculation might fail – just like in baking: if we put the frosting on the cake before baking the batter, that cake will be a disaster.
But software is even less forgiving than baking. You can’t even make a small mistake because then the entire equation will fail. It’s like a house of cards. It’s no wonder then that at the time, only computer fanatics were willing to devote their time to programming. It was a truly Sisyphean task.
In the late 1940s, a new computer language was developed. It was called “Assembly”, also known as “machine language.” Assembly replaced some of the numbers with meaningful words that were somewhat easier to remember. For example, the number 42 was replaced by the word MOV. These textual commands were then fed to a special software named the “Assembler” that converted the words back to numbers – since that’s ultimately what computers understand.
For programmers, Assembly represented a real improvement: for humans, words are much easier to work with than random numbers. But Assembly didn’t eliminate software bugs. It was still too “Low Level” – meaning even simple calculations still required thousands upon thousands of code lines. Programming was still an exhausting and Sisyphean task.
One of those exhausted programmers was John Backus. Backus was a mathematician who worked for IBM, calculating the trajectories of rockets. He absolutely hated programming in Assembly and the tedious process of finding and eliminating software bugs.
So in 1953 Backus decided to do something about it. He wrote a memo to his supervisors and suggested that IBM should develop a new software language that will replace Assembly. This new language, wrote Backus, will be a “High-Level Programming Language”: each individual command will represent numerous Assembly commands. For example, you could use the command “Print” – and “behind the scenes” it will evoke hundreds of simpler Assembly commands that will handle the actual process of printing a character on the screen or on a page. This level of abstraction will make programming easier, simpler – and hopefully, a lot less prone to errors.
But if a High-Level programming language was such a great idea, how come no one thought about it before? Well, it turns out that Backus wasn’t the first. In fact, similar computer languages were developed as early as the 1940s, and many computer scientists found them to be a fascinating research subject. In reality, though, none of these early high-level languages threatened Assembly’s dominance. Why is that?
Recall that the computer, as a rule, understands nothing but numbers. Much like Assembly had to have an “Assembler” to translate the textual commands to numbers – A high-level programming language needs a special software called a “Compiler” to translate the high-level commands. Unfortunately, the translated code produced by the early compilers was very inefficient, when compared to code written in Assembly by a human programmer. The compiler could create ten lines of code – where a human, with a bit of creative thinking, could accomplish the same task with a single line.
This inefficiency meant that software written in high-level code tended to be slow. Since in the 1940s and 50s, computers were already weak and slow, this hit in computation performance was a penalty that no one was willing to pay. And so, high-level programming languages remained an unfulfilled promise.
A High-Level Language
Backus was aware of the challenge, but he was determined. In his memo to IBM, he stressed the potential financial benefits: programming in a high-level language could reduce the number of bugs in a software project, shorten development time, and reduce costs by as much as seventy-five percent.
Backus made a convincing argument, and IBM’s CEO approved his idea. Backus was made the head of the development team and recruited talented and enthusiastic engineers who welcomed the challenge of creating this high-level language. They worked days and nights, and often they slept at a hotel near the offices in order to get available computer time even before sunrise.
Their main task was writing the compiler: the software that translated the high-level code to low-level machine language. Backus and his people knew that the success of their project depended on the compiler’s efficiency: if the code it produced was too inefficient, their new language would fail just as its predecessors did.
Four years later, in 1957, the first version of the new high-level programming language was ready. Backus named it FORTRAN, short for Formula Translation. The name reflects on what is was intended to be used for scientific and mathematical calculations. IBM had just launched a new computer model named IBM-704, and Backus sent the new compiler and a detailed FORTRAN manual to all customers who bought the new computer.
FORTRAN Takes The World By Storm
The response was overwhelmingly positive. Programmers were delighted by how easy and fast they could write software using FORTRAN! One customer recalled how shocked he was to see one of his colleagues – a physicist in a nuclear research institute – writing a complicated piece of software in a single afternoon, whereas writing the same code in Assembly would have taken several weeks!
FORTRAN took the software world by storm! Within less than a year, almost half of the IBM-704 programmers were using FORTRAN on a daily basis. It was the salvation that all bleary-eyed programmers had prayed for: code written in FORTRAN was up to twenty times shorter than one written in Assembly, while still being efficient and blazingly fast. In fact, the new FORTRAN compiler was so successful that it was considered the best of its kind even twenty years later.
This was a big stride towards a future clean from software bugs. Backus’ team was so thrilled by FORTRAN’s success, they hardly included in the language any tools for detecting software errors and analyzing them. They believed that these tools weren’t needed anymore, as the new language had reduced the number of bugs considerably.
FORTRAN Is Made A Standard
In 1961, the American National Standards Institute decided to make FORTRAN a standard language. This was a big deal since until then FORTRAN only worked with IBM-704 computers: making it a national standard meant that it could now be used on computers from other manufacturers as well. Programming became easy and fun! It was no longer restricted to hardcore mathematicians and engineers. Amateur programmers taught themselves FORTRAN from books. Assembly was almost gone, and FORTRAN had taken over the market.
FORTRAN’s success ushered in a new generation of high-level programming languages like COBOL, ALGOL, ADA, and C – the most successful of them all. These languages not only improved on FORTRAN’s ideas and made programming even easier, but they also made programming suitable to a larger variety of tasks: from accounting to artificial intelligence.
You might be surprised to learn that fifty years after it was first released – FORTRAN is still alive and kicking! It’s gone through changes and updates over the years, but is very much still relevant today – and some scientists and researchers still prefer it for complicated calculations. This is an amazing feat for a language designed in an era when programming was done with punched cards!
John Backus passed away in 2007. He was fortunate enough to see how the language he helped create changed the programming world. It transformed programming from a dreadful task – to a sort of positive challenge, even a hobby embraced by millions around the world.
What About The Bugs?!
All’s well that ends well! But Wait a minute! Wait just a minute…are we not forgetting something? What about bugs? Did high-level languages solve the problem of software errors?
No, unfortunately, they didn’t. You see, while high-level languages did make programming a lot easier – they also allowed software to become much more complex. It’s like having the option to buy LEGO blocks instead of fabricating them yourself: you can invest all your time in creating bigger and bigger creations instead of doing everything from scratch. Similarly, high-level languages allow developers to add more features to their programs – and so the advantages of high-level languages were balanced by the ever increasing complexity of the programs themselves. The bugs never went away.
A Fundamental Problem in Software Design
In the 1960s it became clear to many computer programmers that reliability was a fundamental problem in software design. Despite all the great developments, it was still almost impossible to create a piece of software with no errors. I mean, a complex and feature-rich software, not some trivial program.
Worse yet, it seemed that it was getting harder and harder to complete a software development project “successfully.” What do I mean by “successfully”? A successful software project is one whose output is a high-quality, bug-free piece of code, tailored to meet the customer’s specifications, completed within schedule and without budget overruns. This goal was proving to be more elusive with every passing year.
Modern research clearly shows that when it comes to software projects – failure rates are extremely high compared to other engineering projects. A basic software project has a twenty-five percent chance of going over budget, or over its deadline, or producing software that doesn’t meet the customer’s expectations. That’s one out of every four projects! And if the project lasts more than eighteen months, or if the staff is larger than twenty people – the risk of failing becomes more than fifty percent. When it comes to even larger projects that go on for years and involve many teams of programmers, the likelihood of failure is close to a hundred percent. About ten percent of those projects fail so dramatically, that the entire software is thrown away and never used at all. What a waste!
This realization hit many programmers badly. I’m a software developer myself, you know – and us developers take our profession very seriously. We can spend years – and I’m not joking – debating the proper way to capitalize variable names in the code.
Over time, software developers started squinting at other engineering fields, like architecture for example and asked themselves why they couldn’t be more similar. I mean, architects and engineers build tall buildings, long bridges and other structures that are reliable, they don’t go over budget or schedule (well, at least most of the time) and they are built according to spec. Experience has taught software programmers that their projects usually won’t reach the same result.
In 1968 some of the world’s leading software engineers and computer scientists gathered in a NATO convention in Germany, in order to discuss this obvious difficulty of creating successful software. The convention didn’t result in any solution, but it did give the problem a name: “The Software Crisis.”
Building A New Airport
So, what does the software crisis looks like in real life? Here’s an example.
In 1989, the city of Denver, Colorado, announced it was embarking on one of the most ambitious projects of its history: building a new modern airport that would march state tourism and local business towards the twenty-first century.
The jewel in the modern airport’s crown was to be a new and sophisticated baggage transportation system. I mean, baggage transportation is an important part of every modern airport. If a suitcase takes too long to get from point to point – passengers might end up missing their connecting flights. If a suitcase gets lost – that’s a ruined vacation. It’s obvious why the project’s leaders took their new baggage transportation system very seriously.
The company that was chosen to plan the new system was BAE, an experienced company within its field. BAE’s engineers examined the blueprints of the future airport and realized that this was going to be a momentous challenge: Denver’s airport was going to be much larger than was usual for airports, and this meant that transporting a piece of baggage from one end of the airport to the other might take up to 45 minutes! So to solve that problem, BAE designed the most advanced baggage transportation system ever built.
A Breathtaking Design
The plan called for a fully automated system. From the moment an airplane lands, until the moment the luggage is picked up from the carousel – no human hands would touch it. Barcode scanners would identify the suitcase’s destination, and a computerized control system would make sure that an empty cart would be waiting for it at just the right place and time, to transport it as quickly as possible via underground tracks, to the correct terminal. Timing was incredibly important: the carts weren’t even supposed to stop: suitcases were supposed to fall from the one track onto a moving cart at the exact right moment.
Just to give you some perspective on BAE’s breathtaking design: there were 435,000 miles of cables and wires, 25 miles of underground tracks and 10,000 electrical engines to power them. The control system included about 300 computers to supervise the engines and carts. It is no wonder that Denver’s mayor said that the new project was as challenging as, quote, “building the Panama canal.”
The entire city followed the project with interest. The new airport was supposed to open at the end of 1993, but a few weeks before the due date the mayor announced that the opening would be delayed due to some final testing to the baggage transportation system. No one was too surprised: after all, this was a complicated and innovative new system, and it was likely that testing it will take some time.
A breathtaking Failure
But no one was prepared for the embarrassment that took place in March 1994, when the proud mayor invited the media to a celebrated demonstration of the new system.
Instead of an efficient and punctual transportation system, the amazed journalists watched in a mixture of horror and delight at a sort of technological version of Dante’s inferno. Carts that made their way too quickly fell off the tracks and rolled on the floor. Suitcases flew in the air because the carts that were supposed to wait for them never came. Pieces of clothing that fell out of the suitcases got shredded in the engines or tangled in the wheels of passing carts. Suitcases that somehow made their way to an empty cart reached the wrong terminal because barcode scanners failed to identify the stickers on the suitcases. In short – nothing worked properly.
The journalists who witnessed the demonstration didn’t know whether to laugh or cry. If it wasn’t for the project costing the taxpayers close to 200 million dollars, it could have been a like classic Charlie Chaplin comedy. The headlines of the following morning undoubtedly made the mayor cringe.
Behind the scenes, there were desperate attempts to salvage the system. Technicians ran to fix the tracks, but finding a solution at one spot created two other problems elsewhere; Each and every day of delay cost the city of Denver another one million dollars. By the end of 1994, with the airport’s project nowhere near completion – Denver faced the very real possibility of bankruptcy.
The mayor had no choice; after conducting several external tests and emergency discussions, it was decided to dismantle a big chunk of the new automated system. Instead, a traditional more manual system was put in place. The final cost of the airport project, including the cost of the new system, was 375 million dollars – twice the original budget.
In February 1995, almost a year and a half after the original date, the new Denver airport opened to flights, travelers, and suitcases. Only one airline, United, agreed to use the new baggage transportation system, but it too soon gave up. The system experienced so many problems and errors that the monthly maintenance cost was close to a million dollars. In 2005, United Airlines announced it would stop using the automated system, and go back to a manual transportation system.
So what went wrong in Denver? Why was the project’s failure so massive and absolute?
Several investigations highlighted the many factors leading to the failure of the Denver Airport project. Some of these factors included: Management decisions that were too affected by political considerations, changes that were made during construction just to please the airlines and an electricity supply that was constantly interrupted. if all that wasn’t enough, the project’s main architect had died unexpectedly. In short, everything that could have gone wrong – did. Having said that, most of the investigators agreed that the biggest problem of this ambitious project was its software component.
As we mentioned before, the original plan dictated that 3000 carts would travel independently around the airport using the underground tracks. In order for that to happen, about 300 computers were supposed to communicate with each other and make rapid decisions in “real time.”
For example, one of the common scenarios was where an empty cart traveled to a specific location in order to pick up a suitcase. Its route turned out to be quite complicated: the empty cart had to use several tracks, change directions, and perhaps move over or under other carts. Also, a cart’s specific route depended not only on its location but on the location of other carts as well. This meant that if a “traffic jam” occurred for any reason, the software had to recalculate an alternative route. Let’s not forget that we are talking about many thousands of carts, each going to a different destination and each supposed to arrive on time; and that the decisions were supposed to be made by hundreds of computers running simultaneously!
Twenty software programmers worked on the project for two whole years, but the system was so complicated that none of them could have seen the entire picture and truly understand, from a “bird’s eye view,” how the system actually behaved. The final result was a complex and complicated software that was full of errors. Denver’s airport project is a perfect example of the Software Crisis: a large project that went over schedule, over budget, and didn’t reach its goals.
Is There A Solution To The Software Crisis?
Dr. Winston Royce, a leading computer scientist, defined the situation best in 1991 when he said:
“The construction of new software that is both pleasing to the user/buyer and without latent errors is an unexpectedly hard problem. It is perhaps the most difficult problem in engineering today and has been recognized as such for more than 15 years. […]. It has become the longest continuing “crisis” in the engineering world, and it continues unabated.”
So what can we do? Is there a solution to the software crisis? That question will be the focus of our next episode. We will get to know the two methods developed over time to tackle the challenges of creating complicated software: Waterfall and Agile. We’ll also tell the incredible story of a computerized system developed for the FBI at a cost of half a billion dollars… and how it turned out to be a breathtaking failure.
And finally, we will get to know Fred Brooks – a computer scientist who wrote an influential book called “The Mythical Man-Month”. In his book, Brooks asks – Is there a “silver bullet” that will allow us to solve the software crisis?
The fall of Napster (see Part I of this series) has left a vacuum in the world of file sharing – and as the saying goes, the Internet abhors vacuum… Various File Sharing programs such as Gnutella, Kazaa and others quickly filled the void.
In this episode, we’ll describe Grokster’s legal battle against the Record Companies, the sinister poisoning of file sharing networks by OverPeer – and the rise of BitTorrent.
Napster, a revolutionary Peer-to-Peer file sharing software, was launched in 1999 – and forever changed the media world. In this episode, we’ll tell the story of Sean Fanning and Sean Parker, its creators, and talk about the legal battle it fought with the record companies – and Metallica.
This series explores the history and future of podcasting, and each episode will feature a single guest who is a pioneer of podcasting. This time, we’re interviewing Todd Cochrane, CEO of RawVoice (better known as Blubrry) and the host of Geek News Central Podcast.
Todd has an amazing story which begun with a serious injury – but ultimately led to a surprising career as an early entrepreneur in the new media of podcasting. He wrote the first book on podcasting and signed one of the first advertising deals. Today, Todd’s company is one of the biggest players in this new media.
This series explores the history and future of podcasting, and each episode will feature a single guest who is a pioneer of podcasting. This time, we’re interviewing Leo Laporte, from This Week In Tech.
Leo Laporte is one of the very first podcasters. In 2005 Leo left – or almost left – traditional radio to start his own podcasting network, centered around cutting edge technology news, called TWIT. TWIT quickly became one of the most successful podcast networks with millions of downloads and award winning show such as This Week In Tech, Security Now and the New Screen Savers.
This series explores the history and future of podcasting, and each episode will feature a single guest who is a pioneer of podcasting. This time, we’re interviewing Jay Soderberg – AKA The Pod Vader. Head of Content at BlogTalkRadio and Host of the Next Fan Up show.
Jay Soderberg started in podcasting back in 2006. Jay’s story is rather unique, since his first steps in podcasting were in the corporate world, whereas the vast majority of podcasters back then were independent creators. We talked about the advantages and disadvantages of podcasting in a corporate environment, Jay’s vision as Head of Content and, of course, the origins of his nickname – the Pod Vader.
With Special Guests: Richard Stallman & Tim O’Reilly!
In 1998, a group of people broke away from the Free Software Foundation and created instead the Open Source Initiative. What were their motives? Richard Stallman, the founder of the FSF, and Tim O’Reilly who helped popularize the term ‘Open Source’ discuss the history of Open Source & Free Software.
In the early 1980’s Richard Stallman founded the Free Software Foundation (FSF): a socio-technological movement that revolutionized the software world. In this episode, we’ll hear Stallman himself talking about the roots of the movement, and learn of its early struggles.