Computational thinking can be deemed as thinking in algorithmic way, with which one can transpose given problems into computer algorithms. Since computational thinking requires abstract reasoning, it should not depend on particular programming languages. Unfortunately, introductory programming courses (CS1) often give students false impression that their goals are to teach a particular programming language. This study shares the design of new pedagogy for CS1 that removes dependency on a particular language and promotes computational thinking by teaching multiple programming languages simultaneously. Specifically, chosen programming languages range from low-level to high-level to expose students to different levels of abstraction from the details of computer architecture. Initial student survey responses from both trial and control groups show that there are significant improvements for the trial groups.

Software testing is a critical activity in increasing our confidence of a system under test and improving its quality.The key idea for testing a software application is to minimize the number of faults found in the system.The higher the testability of software, the better our chances to reveal these faults.We introduce a new type of testing harness called GannonJVM that improves the testability of software components.GannonJVM enhances the Java Virtual Machine (JVM) with a predicate analyzer and a bytecode interpreter.Our automated test framework is able to extract and visualize paths from the control flow graph of a given component.We also observe and analyze the predicates in a given a path during runtime.

SUMMARY Aspect‐oriented programming yields new types of programming faults due to the introduction of new constructs for dealing with crosscutting concerns. To reveal aspect faults, this paper presents a framework for testing whether or not aspect‐oriented programs conform to their state models. It supports two families of strategies (i.e. structure‐oriented and property‐oriented) for automated generation of aspect tests from aspect‐oriented state models. A structure‐oriented testing strategy derives tests and test code from an aspect‐oriented state model to meet a given structural coverage criterion, such as state coverage, transition coverage, or round trip. A property‐oriented testing strategy generates test code from the counterexamples of model checking. Two such strategies are checking an aspect‐oriented state model against trap properties and checking mutants of aspect models against system properties. Mutation analysis of aspect‐oriented programs is used to evaluate the effectiveness of these testing strategies. The experiments demonstrate that testing aspect‐oriented programs against their state models can detect many aspect faults. The comparative evaluations also reveal that the structure‐oriented and property‐oriented testing strategies complement each other—some aspect faults were detected by the structure‐oriented strategies, but not by the property‐oriented strategies and vice versa. Copyright © 2010 John Wiley & Sons, Ltd.

Functional modeling and safety analysis are two important aspects of safety-critical embedded systems. However, they are often conducted separately. In this paper, we present an approach for integrating fault-tree-based safety analysis into statechart-based functional modeling. The proposed approach uses systematic transformation steps that maintain the semantics of both the fault tree and the statechart. It also provides a set of conversion rules that transform the gates of fault trees into statechart notations. The resultant model shows how the system behaves when a failure condition occurs and acts as a basis model that ensures safety through requirement validation. Using the gas burner case study, we demonstrate the advantages of the integrated model over the use of separate models, such as the lack of ambiguities, separation of concerns, and taking the order of the occurrence of faults into consideration.

As software systems are encompassing a wide range of fields and applications, software reliability becomes a crucial step. The need for safety analysis and test cases that have high probability to uncover plausible faults are necessities in proving software quality. System models that represent only the operational behavioral of a system are incomplete sources for deriving test cases and performing safety analysis before the implementation process. Therefore, a system model that encompasses faults is required. This paper presents a technique that formalizes a safety model through the incorporation of faults with system specifications. The technique focuses on introducing semantic faults through the integration of fault trees with system specifications or statechart. The method uses a set of systematic transformation rules that tries to maintain the semantics of both fault trees and statechart representations during the transformation of fault trees into statechart notations.