As computing becomes a mainstream discipline embedded in the school curriculum and acts as an enabler for an increasing range of academic disciplines in higher education, the literature on introductory programming is growing. Although there have been several reviews that focus on specific aspects of introductory programming, there has been no broad overview of the literature exploring recent trends across the breadth of introductory programming.This paper is the report of an ITiCSE working group that conducted a systematic review in order to gain an overview of the introductory programming literature. Partitioning the literature into papers addressing the student, teaching, the curriculum, and assessment, we explore trends, highlight advances in knowledge over the past 15 years, and indicate possible directions for future research.

Identifying and correcting syntax errors is a challenge all novice programmers confront. As educators, the more we understand about the nature of these errors and how students respond to them, the more effective our teaching can be. It is well known that just a few types of errors are far more frequently encountered by students learning to program than most. In this paper, we examine how long students spend resolving the most common syntax errors, and discover that certain types of errors are not solved any more quickly by the higher ability students. Moreover, we note that these errors consume a large amount of student time, suggesting that targeted teaching interventions may yield a significant payoff in terms of increasing student productivity.

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Debugging is an important skill for novice programmers to acquire. Error messages help novices to locate and correct errors, but compiler messages are frequently inadequate. We have developed a system that provides enhanced error messages, including concrete examples that illustrate the kind of error that has occurred and how that kind of error could be corrected. We evaluate the effectiveness of the enhanced error messages with a controlled empirical study and find no significant effect.

Common exam practice centres around two question types: code tracing (reading) and code writing. It is commonly believed that code tracing is easier than code writing, but it seems obvious that different skills are needed for each. These problems also differ in their value on an exam. Pedagogically, code tracing on paper is an authentic task whereas code writing on paper is less so. Yet, few instructors are willing to forgo the code writing question on an exam. Is there another way, easier to grade, that captures the "problem solving through code creation process" we wish to examine? In this paper we propose Parson's puzzle-style problems for this purpose. We explore their potential both qualitatively, through interviews, and quantitatively through a set of CS1 exams. We find notable correlation between Parsons scores and code writing scores. We find low correlation between code writing and tracing and between Parsons and tracing. We also make the case that marks from a Parsons problem make clear what students don't know (specifically, in both syntax and logic) much less ambiguously than marks from a code writing problem. We make recommendations on the design of Parsons problems for the exam setting, discuss their potential uses and urge further investigations of Parsons problems for assessment of CS1 students.