Evaluating neural networks as a method for identifying students in need of assistance

© 2017 ACM. Course instructors need to be able to identify students in need of assistance as early in the course as possible. Recent work has suggested that machine learning approaches applied to snapshots of small programming exercises may be an effective solution to this problem. However, these results have been obtained using data from a single institution, and prior work using features extracted from student code has been highly sensitive to differences in context. This work provides two contributions: first, a partial reproduction of previously published results, but in a different context, and second, an exploration of the efficacy of neural networks in solving this problem. Our findings confirm the importance of two features (the number of steps required to solve a problem and the correctness of key problems), indicate that machine learning techniques are relatively stable across contexts (both across terms in a single course and across courses), and suggest that neural network based approaches are as effective as the best Bayesian and decision tree methods. Furthermore, neural networks can be tuned to be reliably pessimistic, so they may serve a complementary role in solving the problem of identifying students who need assistance

Practically Applicable Formal Methods

Abstract. Formal methods are considered to be highly expensive. There-fore, they are currently applied almost only in high risk software develop-ment. In this paper, we show that formal techniques can be also efficiently used in standard large-scale applications. We focus on the generation of specifications which state the termination condition of for loops in Java code (expressed as so called Java Modeling Language decreases clauses). We demonstrate that with help of relatively simple techniques it is pos-sible to successfully generate the clauses for almost 80 % of the loops in a number of widely deployed applications. Moreover, it turns out that the remaining 20 % cases contain loops which should be carefully reviewed by software quality assurance personnel. The results show that our tech-nique might be helpful in spreading the usage of formal methods onto typical business software

Introductory programming: a systematic literature review

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

Untangling the woven web: Testing web-based software

In the early 90's, public interest in the Internet skyrocketed with the introduction of web browsers and hyper text markup language (HTML). As the world-wide web becomes more commercial and people start using browsers to purchase products and do other business, issues of website testing become more and more critical. In addition to web-based commerce

Semantic Foundations and Inference of Non-null Annotations

This paper proposes a semantics-based automatic null pointer analysis for inferring non-null annotations of fields in object-oriented programs. The analysis is formulated for a minimalistic OO language and is expressed as a constraint-based abstract interpretation of the program which for each field of a class infers whether the field is definitely non-null or possibly null after object initialization. The analysis is proved correct with respect to an operational semantics of the minimalistic OO language. This correctness proof has been machine checked using the Coq proof assistant. We also prove the analysis complete with respect to the non-null type system proposed by Fähndrich and Leino, in the sense that for every typable program the analysis is able to prove the absence of null dereferences without any hand-written annotations. Experiments with a prototype implementation of the analysis show that the inference is feasible for large programs

A new \u3ci\u3ePotamobates\u3c/i\u3e Champion species (Heteroptera: Gerridae) from Ecuador with new distribution records for \u3ci\u3eP. williamsi \u3c/i\u3eHungerford

Abstract: Potamobates sumaco new species is described from the Ecuadorian Amazon. Male and female genitalia differentiate P. sumaco from a similar parapatric species, P. williamsi Hungerford. Phylogenetic analysis indicates P. sumaco is closely related to the species of the P. tridentatus group which includes P. williamsi. A distribution map and revised key to Potamobates species are provided. Resumen: Se describe Potamobates sumaco nueva especies del Amazonas Ecuatoriano. Los genitales del macho y la hembra distinguen P. sumaco de la especie mas cercana P. williamsi Hungerford. El analisis filogenetico indica que P. sumaco partenece a1 grupo P. tridentatus. Se incluye un mapa de la distribucion y una clave modificada para la identificacion de las especies de Potamobates