Computer Science Education: Where Are the Software Engineers of Tomorrow?

CrossTalk - The Journal of Defense Software Engineering Jan 2008 Issue

Computer Science Education: Where Are the Software Engineers of Tomorrow?

Dr. Robert B.K. Dewar, 
AdaCore Inc.
Dr. Edmond Schonberg, 
AdaCore Inc.

It
is our view that Computer Science (CS) education is neglecting basic
skills, in particular in the areas of programming and formal methods.
We consider that the general adoption of Java as a first programming
language is in part responsible for this decline. We examine briefly
the set of programming skills that should be part of every software
professional’s repertoire.


It
is all about programming! Over the last few years we have noticed
worrisome trends in CS education. The following represents a summary of
those trends:

  1. Mathematics requirements in CS programs are shrinking.
  2. The
    development of programming skills in several languages is giving way to
    cookbook approaches using large libraries and special-purpose packages.
  3. The
    resulting set of skills is insufficient for today’s software industry
    (in particular for safety and security purposes) and, unfortunately,
    matches well what the outsourcing industry can offer. We are training
    easily replaceable professionals.

These
trends are visible in the latest curriculum recommendations from the
Association for Computing Machinery (ACM). Curriculum 2005 does not
mention mathematical prerequisites at all, and it mentions only one
course in the theory of programming languages [1].

We
have seen these developments from both sides: As faculty members at New
York University for decades, we have regretted the introduction of Java
as a first language of instruction for most computer science majors. We
have seen how this choice has weakened the formation of our students,
as reflected in their performance in systems and architecture courses.
As founders of a company that specializes in Ada programming tools for
mission-critical systems, we find it harder to recruit qualified
applicants who have the right foundational skills. We want to advocate
a more rigorous formation, in which formal methods are introduced early
on, and programming languages play a central role in CS education.

Formal Methods and Software Construction

Formal
techniques for proving the correctness of programs were an extremely
active subject of research 20 years ago. However, the methods (and the
hardware) of the time prevented these techniques from becoming
widespread, and as a result they are more or less ignored by most CS
programs. This is unfortunate because the techniques have evolved to
the point that they can be used in large-scale systems and can
contribute substantially to the reliability of these systems. A case in
point is the use of SPARK in the re-engineering of the ground-based air
traffic control system in the United Kingdom (see a description of
iFACTS – Interim Future Area Control Tools Support, at
<www.nats.co.uk/article/90>). SPARK is a subset of Ada augmented
with assertions that allow the designer to prove important properties
of a program: termination, absence of run-time exceptions, finite
memory usage, etc. [2]. It is obvious that this kind of design and
analysis methodology (dubbed Correctness by Construction) will add
substantially to the reliability of a system whose design has involved
SPARK from the beginning. However, PRAXIS, the company that developed
SPARK and which is designing iFACTS, finds it hard to recruit people
with the required mathematical competence (and this is present even in
the United Kingdom, where formal methods are more widely taught and
used than in the United States).

Another
formal approach to which CS students need exposure is model checking
and linear temporal logic for the design of concurrent systems. For a
modern discussion of the topic, which is central to mission-critical
software, see [3].

Another
area of computer science which we find neglected is the study of
floating-point computations. At New York University, a course in
numerical methods and floating-point computing used to be required, but
this requirement was dropped many years ago, and now very few students
take this course. The topic is vital to all scientific and engineering
software and is semantically delicate. One would imagine that it would
be a required part of all courses in scientific computing, but these
often take MatLab to be the universal programming tool and ignore the
topic altogether.

The Pitfalls of Java as a First Programming Language

Because
of its popularity in the context of Web applications and the ease with
which beginners can produce graphical programs, Java has become the
most widely used language in introductory programming courses. We
consider this to be a misguided attempt to make programming more fun,
perhaps in reaction to the drop in CS enrollments that followed the
dot-com bust. What we observed at New York University is that the Java
programming courses did not prepare our students for the first course
in systems, much less for more advanced ones. Students found it hard to
write programs that did not have a graphic interface, had no feeling
for the relationship between the source program and what the hardware
would actually do, and (most damaging) did not understand the semantics
of pointers at all, which made the use of C in systems programming very
challenging.

Let
us propose the following principle: The irresistible beauty of
programming consists in the reduction of complex formal processes to a
very small set of primitive operations. Java, instead of exposing this
beauty, encourages the programmer to approach problem-solving like a
plumber in a hardware store: by rummaging through a multitude of
drawers (i.e. packages) we will end up finding some gadget (i.e. class)
that does roughly what we want. How it does it is not interesting! The
result is a student who knows how to put a simple program together, but
does not know how to program. A further pitfall of the early use of
Java libraries and frameworks is that it is impossible for the student
to develop a sense of the run-time cost of what is written because it
is extremely hard to know what any method call will eventually execute.
A lucid analysis of the problem is presented in [4].

We
are seeing some backlash to this approach. For example, Bjarne
Stroustrup reports from Texas A & M University that the industry is
showing increasing unhappiness with the results of this approach.
Specifically, he notes the following:

I
have had a lot of complaints about that [the use of Java as a first
programming language] from industry, specifically from AT&T, IBM,
Intel, Bloomberg, NI, Microsoft, Lockheed-Martin, and more. [5]

He noted in a private discussion on this topic, reporting the following:

It
[Texas A&M] did [teach Java as the first language]. Then I started
teaching C++ to the electrical engineers and when the EE students
started to out-program the CS students, the CS department switched to
C++. [5]

It
will be interesting to see how many departments follow this trend. At
AdaCore, we are certainly aware of many universities that have adopted
Ada as a first language because of similar concerns.

A Real Programmer Can Write in Any Language (C, Java, Lisp, Ada)

Software
professionals of a certain age will remember the slogan of old-timers
from two generations ago when structured programming became the rage:
Real programmers can write Fortran in any language. The slogan is a
reminder of how thinking habits of programmers are influenced by the
first language they learn and how hard it is to shake these habits if
you do all your programming in a single language. Conversely, we want
to say that a competent programmer is comfortable with a number of
different languages and that the programmer must be able to use the
mental tools favored by one of them, even when programming in another.
For example, the user of an imperative language such as Ada or C++ must
be able to write in a functional style, acquired through practice with
Lisp and ML1, when manipulating recursive structures. This
is one indication of the importance of learning in-depth a number of
different programming languages. What follows summarizes what we think
are the critical contributions that well-established languages make to
the mental tool-set of real programmers. For example, a real programmer
should be able to program inheritance and dynamic dispatching in C,
information hiding in Lisp, tree manipulation libraries in Ada, and
garbage collection in anything but Java. The study of a wide variety of
languages is, thus, indispensable to the well-rounded programmer.

Why C Matters

C
is the low-level language that everyone must know. It can be seen as a
portable assembly language, and as such it exposes the underlying
machine and forces the student to understand clearly the relationship
between software and hardware. Performance analysis is more
straightforward, because the cost of every software statement is clear.
Finally, compilers (GCC for example) make it easy to examine the
generated assembly code, which is an excellent tool for understanding
machine language and architecture.

Why C++ Matters

C++
brings to C the fundamental concepts of modern software engineering:
encapsulation with classes and namespaces, information hiding through
protected and private data and operations, programming by extension
through virtual methods and derived classes, etc. C++ also pushes
storage management as far as it can go without full-blown garbage
collection, with constructors and destructors.

Why Lisp Matters

Every
programmer must be comfortable with functional programming and with the
important notion of referential transparency. Even though most
programmers find imperative programming more intuitive, they must
recognize that in many contexts that a functional, stateless style is
clear, natural, easy to understand, and efficient to boot.

An
additional benefit of the practice of Lisp is that the program is
written in what amounts to abstract syntax, namely the internal
representation that most compilers use between parsing and code
generation. Knowing Lisp is thus an excellent preparation for any
software work that involves language processing.

Finally,
Lisp (at least in its lean Scheme incarnation) is amenable to a very
compact self-definition. Seeing a complete Lisp interpreter written in
Lisp is an intellectual revelation that all computer scientists should
experience.

Why Java Matters

Despite
our comments on Java as a first or only language, we think that Java
has an important role to play in CS instruction. We will mention only
two aspects of the language that must be part of the real programmer’s
skill set:

  1. An understanding of concurrent programming (for which threads provide a basic low-level model).
  2. Reflection,
    namely the understanding that a program can be instrumented to examine
    its own state and to determine its own behavior in a dynamically
    changing environment.

Why Ada Matters

Ada
is the language of software engineering par excellence. Even when it is
not the language of instruction in programming courses, it is the
language chosen to teach courses in software engineering. This is
because the notions of strong typing, encapsulation, information
hiding, concurrency, generic programming, inheritance, and so on, are
embodied in specific features of the language. From our experience and
that of our customers, we can say that a real programmer writes Ada in
any language. For example, an Ada programmer accustomed to Ada’s
package model, which strongly separates specification from
implementation, will tend to write C in a style where well-commented
header files act in somewhat the same way as package specs in Ada. The
programmer will include bounds checking and consistency checks when
passing mutable structures between subprograms to mimic the
strong-typing checks that Ada mandates [6]. She will organize
concurrent programs into tasks and protected objects, with well-defined
synchronization and communication mechanisms.

The
concurrency features of Ada are particularly important in our age of
multi-core architectures. We find it surprising that these
architectures should be presented as a novel challenge to software
design when Ada had well-designed mechanisms for writing safe,
concurrent software 30 years ago.

Programming Languages Are Not the Whole Story

A
well-rounded CS curriculum will include an advanced course in
programming languages that covers a wide variety of languages, chosen
to broaden the understanding of the programming process, rather than to
build a résumé in perceived hot languages. We are somewhat dismayed to
see the popularity of scripting languages in introductory programming
courses. Such languages (Javascript, PHP, Atlas) are indeed popular
tools of today for Web applications. Such languages have all the
pedagogical defaults that we ascribe to Java and provide no opportunity
to learn algorithms and performance analysis. Their absence of strong
typing leads to a trial-and-error programming style and prevents
students from acquiring the discipline of separating design of
interfaces from specifications.

However,
teaching the right languages alone is not enough. Students need to be
exposed to the tools to construct large-scale reliable programs, as we
discussed at the start of this article. Topics of relevance are
studying formal specification methods and formal proof methodologies,
as well as gaining an understanding of how high-reliability code is
certified in the real world. When you step into a plane, you are
putting your life in the hands of software which had better be totally
reliable. As a computer scientist, you should have some knowledge of
how this level of reliability is achieved. In this day and age, the
fear of terrorist cyber attacks have given a new urgency to the
building of software that is not only bug free, but is also immune from
malicious attack. Such high-security software relies even more
extensively on formal methodologies, and our students need to be
prepared for this new world.

References

  1. Joint
    Taskforce for Computing Curricula. “Computing Curricula 2005: The
    Overview Report.” ACM/AIS/ IEEE, 2005 <www.acm.org/education
    /curric_vols/CC2005-March06 Final.pdf>.
  2. Barnes, John. High Integrity Ada: The Spark Approach. Addison-Wesley, 2003.
  3. Ben-Ari, M. Principles of Concurrent and Distributed Programming. 2nd ed. Addison-Wesley, 2006.
  4. Mitchell,
    Nick, Gary Sevitsky, and Harini Srinivasan. “The Diary of a Datum: An
    Approach to Analyzing Runtime Complexity in Framework-Based
    Applications.” Workshop on Library-Centric Software Design,
    Object-Oriented Programming, Systems, Languages, and Applications, San
    Diego, CA, 2005.
  5. Stroustrup, Bjarne. Private communication. Aug. 2007.
  6. Holzmann Gerard J. “The Power of Ten – Rules for Developing Safety Critical Code.” IEEE Computer June 2006: 93-95.

Note

  1. Several
    programming language and system names have evolved from acronyms whose
    formal spellings are no longer considered applicable to the current
    names for which they are readily known. ML, Lisp, GCC, PHP, and SPARK
    fall under this category.

About the Authors
Dr. Robert B.K. Dewar

Robert B.K. Dewar, Ph.D., is
president of AdaCore and a professor emeritus of computer science at
New York University. He has been involved in the design and
implementation of Ada since 1980 as a distinguished reviewer, a member
of the Ada Rapporteur group, and the chief architect of Gnu Ada
Translator. He was a member of the Algol68 committee and is the
designer and implementor of Spitbol. Dewar lectures widely on
programming languages, software methodologies, safety and security, and
on intellectual property rights. He has a doctorate in chemistry from
the University of Chicago.

AdaCore
104 Fifth AVE 15th FL
New York, NY 10011
Phone: (212) 620-7300 ext. 100
Fax: (212) 807-0162
E-mail: dewar@adacore.com



Dr. Edmond Schonberg

Edmond Schonberg, Ph.D.,
is vice-president of AdaCore and a professor emeritus of computer
science at New York University. He has been involved in the
implementation of Ada since 1981. With Robert Dewar and other
collaborators, he created the first validated implementation of Ada83,
the first prototype compiler for Ada9X, and the first full
implementation of Ada2005. Schonberg has a doctorate in physics from
the University of Chicago.

AdaCore
104 Fifth AVE 15th FL
New York, NY 10011
E-mail: schonberg@adacore.com

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