Software resources configured by end users to monitor non-critical medical conditions
can cause unnecessary pain or discomfort for users who rely on them [Orrick 2006].
Because of these quality issues, researchers have begun to study end-user program-
ming practices and invent new kinds of technologies that collaborate with end users to
improve software quality. This research area is called end-user software engineering
(EUSE). This topic is distinct from related topics in end-user development in its focus on
software quality. For example, there have been prior surveys of novice programming en-
vironments [Kelleher and Pausch 2005], discussing systems that either help students ac-
quire computing skills or enable the creation of computational artifacts; while quality is a
concern in these contexts, this work focuses largely on learning goals. There have also
been surveys on end-user programming [Sutcliffe and Mehandjiev 2004, Lieberman et al.
2006][Wulf et al. 2006], but these focus on the construction of programs to support other
goals, but not on engineering activities peripheral to construction, such as requirements,
specifications, reuse, testing, and debugging.
In this article, these software engineering activities are our primary focus. We start by
proposing definitions of programming, end-user programming, and end-user software
engineering, focusing on differences in intents and priorities between end-user program-
ming and professional software development. We follow with a lifecycle-oriented treat-
ment of end-user software engineering research, organizing more than a decade of re-
search on incorporating requirements, design, testing, verification, and debugging into
end users’ existing work practices. We then discuss a variety of crosscutting issues in
end-user software engineering research, including the role of risk, reward, and domain of
practice on end users’ decision-making, as well as strategies for persuading users to en-
gage in more rigorous software engineering activities as part of their normal work. We
also discuss individual factors, such as self-efficacy and gender, and their influence on
how effectively people use EUSE tools.
What we found in our review of these research efforts were two different histories.
First, studies of end-user software engineering concerns have had a consistently broad
scope. Researchers have studied children [Petre and Blackwell 2007], middle-school stu-
dents [Baker 2007, Kelleher et al. 2007], system administrators [Barrett et al. 2004], peo-
ple at home [Blackwell 2004], knowledge workers in large companies [Bogart et al.
2008, Scaffidi et al. 2006], interaction designers [Ko et al. 2004, Brandt et al. 2008,
Myers et al. 2008], natural scientists [Carver et al. 2007, Segal 2007], software architects
[Lakshminarayanan et al. 2006], bioinformatics professionals [Letondal 2006], web de-
signers [Rode and Rosson 2003], and even volunteers helping with disaster relief [Scaf-
fidi et al. 2007].
In contrast to studies of EUSE, contributions to EUSE tools have historically had a
narrow scope. Early work focused largely on spreadsheets and event-based computing
paradigms and on perfective aspects of end-user software engineering, such as testing,
verification and debugging. Part of this historical bias is due to the fact that doing re-
search on a particular paradigm has required mature and flexible programming languages,
platforms, and IDEs on which to build more helpful software engineering tools, and most
end-user programming platforms have not exhibited these properties. More recently how-
ever, this bias has been eliminated, with recent work focusing on a much broader set of
domains and paradigms, including the web, mobile devices, personal information man-
agement, business processes, and programming in the home. Researchers have also ex-
tended their focus from perfective activities to design, including work on requirements,
specifications, and reuse. Part of this shift is due to the advent of interactive web applica-
tions, as sharing code is becoming much more common.
These trends, coupled with the fact that computing is rapidly being incorporated into
an incredible array of human activities, suggest that EUSE research will become similarly
diverse. This will pose many challenges for the field, since the various domains studied
and supported by research may have little in common. This is also an opportunity, how-
ever, for researchers to identify what is common across these diverse areas of practice.
This article represents an effort at identifying some of these fundamental challenges,
grounded in lessons from prior work.
One contribution of this article is to identify existing terms in EUSE research and fill in
terminology gaps, creating a well-defined vocabulary upon which to build future re-
search. In this section, we start with a basic definition of programming and end with a
definition of end-user software engineering.
2.1. Programming and Programs
We define programming similarly to modern English dictionaries, as the process of plan-
ning or writing a program. This leads to the need for a definition of the term program.
Some definitions of “program” are in terms of the language, in which the program is writ-
ten, requiring, for example, that the notation be Turing complete, and able to specify se-
quence, conditional logic and iteration. However, definitions such as these are heavily
influenced by the type of activity being automated. To remove these somewhat arbitrary
constraints from the definition, for the purposes of this paper we define a program as a
collection of specifications that may take variable inputs, and that can be executed (or
interpreted) by a device with computational capabilities. Note that the variability of input
values requires that the program has the ability to execute on future values, which is one
way it is different from simply doing a computation once manually. This definition cap-
tures general purpose languages in wide use, such as Java and C, but also notations as
simple as VCR programs, written to record a particular show when the time of day (in-
put) satisfies the specified constraint, and combinations of HTML and CSS, which are
interpreted to produce a specific visual rendering of shapes and text. It also captures the
use of report generators, which take some abstract specification of the desired report and
automatically create the finished report.
2.2. End-User Programming
We now turn to end-user programming, a phrase popularized by Nardi  in her in-
vestigations into spreadsheet use in office workplaces. An end user
is simply any com-
puter user. We then define end-user programming as programming to achieve the result
of a program primarily for personal, rather public use. The important distinction here is
that program itself is not primarily intended for use by a large number of users with vary-
ing needs. For example, a teacher may write a grades spreadsheet to track students’ test
scores, a photographer might write a Photoshop script to apply the same filters to a hun-
dred photos, or a caretaker might write a script to help a person with cognitive disabilities
be more independent [Carmien and Fischer 2008]. In these end-user programming situa-
tions, the program is a means to an end and only one of potentially many tools that could
be used to accomplish a goal. This definition also includes a skilled software developer
writing “helper” code to support some primary task. For example, a developer is engag-
ing in end-user programming when writing code to visualize a data structure to help di-
agnose a bug. Here, the tool and its output are intended to support the developers’ par-
ticular task, but not a broader group of users or use cases.
In contrast to end-user programming, professional programming has the goal of pro-
ducing code for others to use. The intent might be to make money, or to write it for fun,
or perhaps as a public service (as is the case for many free and open source projects).
The “end” in “end user” comes from economics and business, where the person who purchases a software
product may be different from the “end user” who uses it. Our use of the phrase in this article is more for his-
torical consistency than because we need to make this distinction.
Therefore, the moment novice web designers move from designing a web page for them-
selves to designing a web page for someone else, the nature of their activity has changed.
The same is true if the developer mentioned above decides to share the data structure
visualization tool with the rest of his team. The moment this shift in intent occurs, the
developer must plan and design for a broader range of possible uses, increasing the im-
portance of design and testing, and the prevalence of potential bugs.
It is also important to clarify two aspects of this “intent”-based definition. First, our
definition is not intended to be dichotomous, but continuous. After all, there is no clear
distinction between a program intended for use by five people and a program intended for
fifty. Instead, the key distinction is that as the number of intended uses of the program
increases, a programmer will have to increasingly consider software engineering con-
cerns in order to satisfy increasingly complex and diverse constraints. Second, even if a
programmer does not intend for a program to be used by others, circumstances may
change: the program may have broader value, and the code which was originally un-
tested, hacked together, and full of unexercised bugs may suddenly require more rigorous
software engineering attention.
While our definition of end-user programming is a departure from previously pub-
lished definitions, we do so both to bring clarity to field and to discuss some of the under-
lying dimensions of historical use. For example, a number of connotations of the phrase
have emerged in research, many using it to refer to “novice” programming or “non-
professional” programming, or system design that involves the participation of end users.
Many have also used it to describe an individual’s identity [Nardi 1993]. We believe
these connotations conflate a number of related, but non-equivalent concepts.
For example, consider its use as an identity. A wide variety of people may engage in
end-user programming; Table 1 gives just a glimpse of the diversity of people’s computa-
tional creations. While it is natural to use the phrase “end-user programmers” to describe
these groups, it is not always accurate, because a persons’ intent in programming can
depend on their task. For example, an accountant may use spreadsheets at home to keep
track of a family loan, but use and share a spreadsheet at work to manage annual tax
preparation activities with other accountants. It would be inaccurate to call this account-
ant an end-user programmer in all situations, when the spreadsheet at home is intended
for personal, short-term use, but the one at work is heavily maintained and repeatedly
used by multiple people. Thus, when we use the phrase “end-user programmer” in this
paper, we are indicating the intent behind a programming task, not a fundamental aspect
of the programmer’s identity.
Class of people
Activities of programming and tools and languages used
Write scripts to glue systems together, using text editors and scripting languages
Prototype user interfaces with tools like Visual Basic and Flash
Create interactive art with languages like Processing (http://processing.org)
Teach science and math with spreadsheets [Niess et al. 2007]
Tabulate and summarize financial data with spreadsheets
Calculate and assess risks using financial simulation tools like MATLAB
Model and design structures using FormZ and other 3D modelers
Create animations and games with Alice [Dann et al. 2006] and Scratch
Middle school girls
Use Alice to tell stories [Kelleher and Pausch 2006, Kelleher and Pausch 2007]
Health care workers
Write specifications to generate medical report forms
Use MATLAB and Prograph [Cox et al. 1989] to perform tests and simulations
Write e-mail rules to manage, sort and filter e-mail
Video game players
Author “mods” for first person shooters, online multiplayer games, and The Sims
Create digital music with synthesizers and musical dataflow languages
VCR and TiVo users
Record television programs in advance by specifying parameters and schedules
Write control schedules for heating and lighting systems with X10
Apple OS X users
Automate workflow using AppleScript and Automator
Process and graph mathematical data with calculator scripting languages
Author and generate data-base backed reports with Crystal Reports
Table 1. A partial list of class of people who write programs and the kinds of programs they write.
It is also important to not conflate end-user programming with inexperience. Profes-
sional developers with decades of experience can engage in end-user programming by
writing code for personal use, with no intent to share their program with others. They
may complete their end-user programming task more quickly and with fewer bugs, but
they will not approach the work with the same quality goals that they would for produc-
tion code. To illustrate this distinction, consider Figure 1, which portrays programming
experience and intent as two separate dimensions. Computer science students and profes-
sional programmers code with the intent of creating software for people to use (or grade),
but vary in their experience. Similarly, end-user programming involves programming for
personal use, but can include a wide range of programming expertise (of course, there are
many more inexperienced programmers than experienced ones; we are not arguing that
the distribution of experience is uniform).
Similarly, it is important to not conflate end-user programming with the use of “sim-
ple” languages. Experienced developers may use general purpose languages like C++ to
achieve end-user programming goals, and in fact, many scientists do use such languages
to do exploratory scientific analyses, without the intent of sharing the code or polishing it
for future use [Segal 2007]. Similarly, experienced developers may use simple markup
languages such as HTML and CSS to design commercial web sites. In general, end-user
programming can involve a wide range of languages, from macro recording, to domain-
specific languages, to conventional, general-purpose languages. The key distinction in the
choice of language is whether it helps a person achieve their personal goal (e.g., “choos-
ing the right tool for the job”).
Related to the choice of language, end-user programming should not be conflated
Figure 1. Programming activities along dimensions of experience and intent. The diagram is not intended to
suggest the distribution of programmers (as there are many more without experience than with), but simply the
underlying dimensions that characterize programming activity. The upward slant in end-user programming
indicates that people with more experience tend to plan for other uses of their code.
with the use of particular interaction technique for constructing code. Java programs can
be written with a text editor or a visual editor [Ko and Myers 2006] and languages that
are traditionally written with visual editors, such as dataflow languages like Yahoo Pipes
(http://pipes.yahoo.com) and Prograph [Matwin & Petrzykowski 1985], can also be ex-
pressed in textual syntax. The use of visual code editors has more to do with the difficulty
of learning and manipulating textual syntax than the intent of the programmer.
There are a number of phrases related to “end-user programming” that are worth dis-
cussing relative to our definition. End-user development has been defined as “a set of
methods, techniques, and tools that allow users of software systems, who are acting as
non-professional software developers, at some point to create, modify, or extend a soft-
ware artifact” [Lieberman et al. 2006]. This notion of end-user development also focuses
on the use and adaptations of software over time, and focuses on elements of the software
lifecycle beyond the stage of creating a new program. More specifically, mutual-
development, co-development, and participatory design refer to activities in which end
users are involved in a system design, but may or may not be involved in its actual coding
[Henderson and Kyng 1991, Costabile et al. 2009, Mackay 1990]. These accounts of or-
ganizational, social, and collaborative perspectives on end-user development offer several
valuable perspectives on how people appropriate and customize software, most of which
are beyond the scope of this survey.
Terms such as customization, configuring [Eagan and Stasko 2008], and tailoring
[Trigg and Bødker 1994, Kahler 2001] include parameterization of existing programs, but
not direct modification of a program’s source code. Visual programming refers to a set of
interaction techniques and visual notations for expressing programs. The phrase often
implies use by end-user programmers, but visual notations are not always targeted at a
particular type of programming practice. Domain-specific languages are programming
languages designed for writing programs for a particular kind of context or practice. End-
user programming may or may not involve such languages, since what defines end-user
programming is the intent, not the choice of languages or tools. Finally, scripts and
scripting languages are often distinguished from programs and programming languages
by the use of machine interpretation rather than compilation and their “high-level” use in
coordinating the functions of multiple programs or services. The phrase end-user pro-
gramming, because it is often conflated with inexperience, often connotes the use of
scripting languages since these languages have the reputation of being easier to learn.
2.3. End-User Software Engineering
With definitions of programming and end-user programming, we now turn to the central
topic of this article, end-user software engineering. As we discussed in the previous sec-
tion, the intent behind programming is what distinguishes end-user programming from
other activities. This is because programmers’ intents determine to what extent they con-
sider concerns such as reliability, reuse, and maintainability and the extent to which they
engage in activities that reinforce these qualities, such as testing, verification, and debug-
ging. Therefore, if one defines software engineering as systematic and disciplined activi-
ties that address software quality issues
, the key difference between professional soft-
ware engineering and end-user software engineering is the amount attention given to
software quality concerns.
In professional software engineering, the amount of attention is much greater: if a
program is intended for use by millions of users, all with varying concerns and unique
contexts of use, a programmer must consider quality regularly and rigorously in order to
succeed. This is perhaps why definitions of software engineering often imply rigor. For
example, IEEE Standard 610.12 defines software engineering as “the application of sys-
tematic, disciplined, quantifiable approaches to the development, operation, and mainte-
nance of software.” Systematicity, discipline, and quantification all require significant
time and attention, so much so that professional software developers spend more time
testing and maintaining code than developing it [Tassey 2002] and they often structure
their teams, communication, and tools around performing these activities [Ko et al.
In contrast, end-user software engineering still involves systematic and disciplined
activities that address software quality issues, but these activities are secondary to the
goal that the program is helping to achieve. Because of this difference in priorities and
Because the meaning of the phrase software engineering is still under much debate, we use the definition from
current IEEE standards.
Software Engineering Activity Professional SE
Testing and Verification
Table 2. Qualitative differences between professional and end-user software engineering.
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