Programming assistance tools to support the learning of IT programming in South African secondary schools

Novice programmers struggle to understand introductory programming concepts and this difficulty, associated with learning to program, contributes mainly to the lack of interest in the field of Computer Science at tertiary level. Programming assistance tools have been used to assist novice programmers extensively at education institutions. A programming assistance tool (PAT) is a software program that can be used by novice programmers to learn how to program and/or improve their understanding of programming concepts.This research proposes that novice programmers, specifically Information Technology (IT) scholars in South African secondary schools, could be supported by PATs. The main objective of this research was to determine whether the use of a PAT impacted IT scholars' understanding of programming concepts and their motivation towards programming in general. Criteria for the selection of PATs were derived from the programming difficulties identified in literature and from surveys to IT teachers and scholars. The selection criteria were grouped into programming knowledge and programming skills categories. Existing PATs were evaluated using the selection criteria and three PATs, namely, RoboMind, Scratch and B#, were selected for evaluation in this research study. A convenience sample of schools participated in the study. The three PATs provided different approaches while being able to support the Delphi programming language used in schools that participated in the study.The findings of this research indicated that, although scholars perceived the PATs to be useful in the explanation of certain of the programming concepts, there was no conclusive evidence that IT scholars who used a PAT had a significantly better understanding of programming concepts and motivation towards programming than scholars who did not use a PAT. Participant feedback was used to identify the strengths and shortcomings of the three PATs and to provide recommendations for the development of future PATs specifically designed to support IT scholars.     

A simple nucleus written in modula-2: A case study

A simple nucleus for a single-processor computer is considered. The entire nucleus program is written in the high-level programming language Modula-2¹ without assembly coding. The concepts of the nucleus and some simple applications are described. A complete listing of the nucleus is included. We conclude that programming of a nucleus in an appropriate high-level language is simpler than in an assembly language. The resulting nucleus has a comparable performance with other nuclei written in assembly code.     

Recovering traceability links between code and documentation

Software system documentation is almost always expressed informally in natural language and free text. Examples include requirement specifications, design documents, manual pages, system development journals, error logs, and related maintenance reports. We propose a method based on information retrieval to recover traceability links between source code and free text documents. A premise of our work is that programmers use meaningful names for program items, such as functions, variables, types, classes, and methods. We believe that the application-domain knowledge that programmers process when writing the code is often captured by the mnemonics for identifiers; therefore, the analysis of these mnemonics can help to associate high-level concepts with program concepts and vice-versa. We apply both a probabilistic and a vector space information retrieval model in two case studies to trace C++ source code onto manual pages and Java code to functional requirements. We compare the results of applying the two models, discuss the benefits and limitations, and describe directions for improvements.     

Program concept recognition and transformation

The automated recognition of abstract high-level conceptual information or concepts, which can greatly aid the understanding of programs and therefore support many software maintenance and reengineering activities, is considered. An approach to automated concept recognition and its application to maintenance-related program transformations are described. A unique characteristic of this approach is that transformations of code can be expressed as transformations of abstract concepts. This significantly elevates the level of transformation specifications     

Using Visual Context and Region Semantics for High-Level Concept Detection

In this paper we investigate detection of high-level concepts in multimedia content through an integrated approach of visual thesaurus analysis and visual context. In the former, detection is based on model vectors that represent image composition in terms of region types, obtained through clustering over a large data set. The latter deals with two aspects, namely high-level concepts and region types of the thesaurus, employing a model of a priori specified semantic relations among concepts and automatically extracted topological relations among region types; thus it combines both conceptual and topological context. A set of algorithms is presented, which modify either the confidence values of detected concepts, or the model vectors based on which detection is performed. Visual context exploitation is evaluated on TRECVID and Corel data sets and compared to a number of related visual thesaurus approaches.     

Real-time monitoring and short-term forecasting of land surface phenology

Land surface phenology is an important process for real-time monitoring and short-term forecasting in diverse land management, health, and hydrologic modeling applications. Yet current efforts to characterize phenological processes are limited by remote sensing challenges and lack of uncertainty estimates. Here, for a global distribution of phenologically and climatically similar phenoregions, we used the Advanced Very High Resolution Radiometer to develop a conceptually and computationally simple technique for real-time and forecast applications. Our overall approach was to analyze the phenological behavior of groups of pixels without recourse to smoothing or fitting. We used a 3-step initial process: (1) define a phenoregion specific normalized difference vegetation index threshold; (2) for all days from 1982-2003, calculate the percent of pixels above the threshold (PAT); (3) calculate daily 1982-2003 empirical distributions of PAT. For real-time monitoring, the current PAT may then be compared to the historical range of variability and visualized in relation to user-defined levels. Using similar concepts, we projected daily PAT up to one month in the future and compared predicted and actual dates at which a hypothetical PAT was reached. We found that the maximum lead-time of phenological forecasts could be analytically defined for user-specified uncertainty levels. The approach is adaptable to different remote sensing technologies and provides a foundation for ascribing a sequence of ground conditions (e.g. snowmelt, vegetative growth, pollen production, insect phenology) to remotely sensed land surface phenology observations.     

Perspective angle transform: Principle of shape from angles

This paper introduces a new relation, called the perspective angle transform (PAT), to deal with shape-from-angle problems, together with its application to 3D configuration recovery from an image. Three main aspects of PAT are presented in this paper. The first is the derivation of PAT which holds between the apparent and real angles under perspective projection. A concept is proposed of a virtual image plane and a new coordinate system, named the first perspective moving coordinate (FPMC) system, for analysis of the shape-from-range problems. Characteristics of FPMC are discussed briefly. The second point is the analysis of PAT properties, for which the general PAT form is introduced on another new coordinate system, named the second perspective moving coordinate (SPMC) system. Using this general form, the gradient of the plane including the real angle is constrained on a curve (PAT curve) of the fourth degree in the virtual image plane. The characteristics of PAT curves and relations between the general PAT form and skewed symmetry are summarized briefly. The last point concerns an application of PAT. As an example, we treat 3D configuration recovery from three arbitrary line segments in the image plane. This recovery corresponds to a generalization of the right-angled interpretation problem proposed and discussed by S.T. Barnard. A solution to the problem is shown using the general PAT form in conjunction with the concept of a virtual crossing point. The right-angled interpretation problem is ascribed to a quadratic equation. A simplified solution is also provided for the case where three line segments have a common crossing point in the image plane. This solution is based on the primary PAT form and is applicable to interpretation of a trihedral vertex with at least two right angles.This paper is an enlarged and polished version of a previous paper in Proc. IEEE Conf CVPR'86 [11]. A part of this paper summarizes the contents of the previous paper. However, perspective projection is treated here in more rigorous and more compact manner than in the previous paper.     

PAT: A pattern classification approach to automatic reference oracles for the testing of mesh simplification programs

Graphics applications often need to manipulate numerous graphical objects stored as polygonal models. Mesh simplification is an approach to vary the levels of visual details as appropriate, thereby improving on the overall performance of the applications. Different mesh simplification algorithms may cater for different needs, producing diversified types of simplified polygonal model as a result. Testing mesh simplification implementations is essential to assure the quality of the graphics applications. However, it is very difficult to determine the oracles (or expected outcomes) of mesh simplification for the verification of test results.A reference model is an implementation closely related to the program under test. Is it possible to use such reference models as pseudo-oracles for testing mesh simplification programs? If so, how effective are they?This paper presents a fault-based pattern classification methodology called PAT, to address the questions. In PAT, we train the C4.5 classifier using black-box features of samples from a reference model and its fault-based versions, in order to test samples from the subject program. We evaluate PAT using four implementations of mesh simplification algorithms as reference models applied to 44 open-source three-dimensional polygonal models. Empirical results reveal that the use of a reference model as a pseudo-oracle is effective for testing the implementations of resembling mesh simplification algorithms. However, the results also show a tradeoff: When compared with a simple reference model, the use of a resembling but sophisticated reference model is more effective and accurate but less robust.     

基于结构分析的高级语言控制结构恢复方法

为正确获得嵌入式可执行程序和汇编代码的高级语言控制结构,弥补现有高级程序控制结构恢复算法在处理非结构化区域的不足,将编译领域经典的控制流分析方法——结构分析算法引入到嵌入式汇编代码高级程序控制结构恢复研究中;针对嵌入式可执行程序的特点,对结构分析算法加以改进;利用结构分析算法的结果构造程序的控制树,生成高级语言代码。与开源反编译器DCC的对比实验结果表明,改进的结构分析算法在高级程序结构恢复问题上是可行有效的。     

Complete worst-case execution time analysis of straight-line hard real-time programs

In this article, the problem of finding a tight estimate on the worst-case execution time (WCET) of a hard real-time program is addressed. The analysis is focused on straight-line code (without loops and recursive function calls) which is quite commonly found in synthesised code for embedded systems. A comprehensive timing analysis system covering both low-level (assembler instruction level) as well as high-level aspects (programming language level) is presented. The low-level analysis covers all speed-up mechanisms used for modern superscalar processors: pipelining, instruction-level parallelism and caching. The high-level analysis uses the results from the low-level to compute the final estimate on the WCET. This is done by a heuristic for searching the longest really executable path in the control flow, based on the functional dependencies between various program parts.     

A component framework for system modeling based on high-level replacement systems

The aim of this paper is to present a generic component framework for system modeling that satisfies main requirements for component-based development in software engineering. In this sense, we have defined a framework that can be used, by providing an adequate instantiation, in connection with a large class of semi-formal and formal modeling techniques. Moreover, the framework is also flexible with respect to the connection of components, providing a compositional semantics of components. This means more precisely that the semantics of a system can be inferred from the semantics of its components. In contrast to other component concepts for data type specification techniques, our component framework is based on a generic notion of transformations. In particular, refinements and transformations are used to express intradependencies, between the export interface and the body of a component, and interdependencies, between the import and the export interfaces of different components. The generic component framework generalizes module concepts for different kinds of Petri nets and graph transformation systems proposed in the literature, and seems to be also suitable for visual modeling techniques, including parts of the UML, if these techniques provide a suitable refinement or transformation concept. In this paper the generic approach is instantiated in two steps. First to high-level replacement systems generalizing the transformation concept of graph transformations. In a second step it is further instantiated to low-level and high-level Petri nets. To show applicability we present sample components from a case study in the domain of production automation as proposed in a priority program of the German Research Council (DFG).     

Integrated Mining of Visual Features, Speech Features, and Frequent Patterns for Semantic Video Annotation

To support effective multimedia information retrieval, video annotation has become an important topic in video content analysis. Existing video annotation methods put the focus on either the analysis of low-level features or simple semantic concepts, and they cannot reduce the gap between low-level features and high-level concepts. In this paper, we propose an innovative method for semantic video annotation through integrated mining of visual features, speech features, and frequent semantic patterns existing in the video. The proposed method mainly consists of two main phases: 1) Construction of four kinds of predictive annotation models, namely speech-association, visual-association, visual-sequential, and statistical models from annotated videos. 2) Fusion of these models for annotating un-annotated videos automatically. The main advantage of the proposed method lies in that all visual features, speech features, and semantic patterns are considered simultaneously. Moreover, the utilization of high-level rules can effectively complement the insufficiency of statistics-based methods in dealing with complex and broad keyword identification in video annotation. Through empirical evaluation on NIST TRECVID video datasets, the proposed approach is shown to enhance the performance of annotation substantially in terms of precision, recall, and F-measure.     

Optimal solutions for semantic image decomposition

Bridging the gap between low-level and high-level image analysis has been a central challenge in computer vision throughout the last decades. In this article I will point out a number of recent developments in low-level image analysis which open up new possibilities to bring together concepts of high-level and low-level vision. The key observation is that numerous multi‐label optimization problems can nowadays be efficiently solved in a near-optimal manner, using either graph-theoretic algorithms or convex relaxation techniques. Moreover, higher-level semantic knowledge can be learned and imposed on the basis of such multi‐label formulations.     

Two-dimensional pinpointing: debugging with formal specifications

Debugging techniques and tools that draw on both the high-level concepts (defined as functions) used in formal specifications and the abstraction and information-hiding constructs used in modern languages are described. The technique is based on two components. One is a novel specification language with support tools. Ada programs are specified with a language that the authors created called Anna. Their tool set is used to check the Ada program's runtime behavior for consistency with the Anna specifications. The other technique uses the tool set to find missing specifications by comparing the specification with program prototypes and to test and debug Ada programs after an accepted specification has been developed. The approach, called two-dimensional pinpointing, locates inconsistencies in software that is structured in levels     

Using B SP and Python to simplify parallel programming

Scientific computing is usually associated with compiled languages for maximum efficiency. However, in a typical application program, only a small part of the code is time-critical and requires the efficiency of a compiled language. It is often advantageous to use interpreted high-level languages for the remaining tasks, adopting a mixed-language approach. This will be demonstrated for Python, an interpreted object-oriented high-level language that is well suited for scientific computing. Particular attention is paid to high-level parallel programming using Python and the BSP model. We explain the basics of BSP and how it differs from other parallel programming tools like MPI. Thereafter we present an application of Python and BSP for solving a partial differential equation from computational science, utilizing high-level design of libraries and mixed-language (Python–C or Python–Fortran) programming.     

call图与基于call图的相关分析

ｃａｌｌ图用来反映程序中过程之间的调用关系，在程序分析和程序转换中起着重要的作用。本文首先讨论了简单情形下ｃａｌｌ图的构造算法，然后提出了过程向量及其映射函数的概念，从而设计出一种针对允许过程作为参数时ｃａｌｌ图的构造算法，并对该算法进行了详细的分析，其时间复杂度为Ｏ。本文最后讨论并分析了基于ｃａｌｌ图的程序相关分析方法。     

具有概念联想功能的特定领域分词词典的自动构建

提出了一种基于PAT树型结构的高频字串提取的改进算法。并以此用来获得特定领域网页中的未登录词集合，利用基于语义距离的概念相似度计算公式来获得任一概念的相关概念，从而给出了用于特定领域搜索引擎的语义词典完整的自动构建方法。将生成的语义词典用于搜索引擎FlyingScnder中。实验结果证明新的词典比原有的手工构建的词典分词效果要理想得多。而且提供了概念联想的功能。