A Model-Driven Approach for Business Process Management

The Business Process Management is a common mechanism recommended by a high number of standards for the management of companies and organizations. In software companies this practice is every day more accepted and companies have to assume it, if they want to be competitive. However, the effective definition of these processes and mainly their maintenance and execution are not always easy tasks. This paper presents an approach based on the Model-Driven paradigm for Business Process Management in software companies. This solution offers a suitable mechanism that was implemented successfully in different companies with a tool case named NDTQ-Framework.Ministerio de Educación y Ciencia TIN2010-20057-C03-02Junta de Andalucía TIC-578

An Empirical Study of the Effectiveness of 'Forcing Diversity' Based on a Large Population of Diverse Programs

Use of diverse software components is a viable defence against common-mode failures in redundant softwarebased systems. Various forms of "Diversity-Seeking Decisions" (“DSDs”) can be applied to the process of developing, or procuring, redundant components, to improve the chances of the resulting components not failing on the same demands. An open question is how effective these decisions, and their combinations, are for achieving large enough reliability gains. Using a large population of software programs, we studied experimentally the effectiveness of specific "DSDs" (and their combinations) mandating differences between redundant components. Some of these combinations produced much better improvements in system probability of failure per demand (PFD) than "uncontrolled" diversity did. Yet, our findings suggest that the gains from such "DSDs" vary significantly between them and between the application problems studied. The relationship between DSDs and system PFD is complex and does not allow for simple universal rules (e.g. "the more diversity the better") to apply

An Extended Stable Marriage Problem Algorithm for Clone Detection

Code cloning negatively affects industrial software and threatens intellectual property. This paper presents a novel approach to detecting cloned software by using a bijective matching technique. The proposed approach focuses on increasing the range of similarity measures and thus enhancing the precision of the detection. This is achieved by extending a well-known stable-marriage problem (SMP) and demonstrating how matches between code fragments of different files can be expressed. A prototype of the proposed approach is provided using a proper scenario, which shows a noticeable improvement in several features of clone detection such as scalability and accuracy.Comment: 20 pages, 10 figures, 6 table

A model driven approach for software systems reliability

The reliability assurance of software systems from design to deployment level through transformation techniques and model driven approach, is described. Once the reliability mechanisms provided by current component-based development architectures (CBDA) are designed in a platform-independent way, platform-based design and implementation models must be extended. Current CBDAs, such as Enterprise Java Beans, address a considerable range of features to support system reliability. The evaluation aims to test maturity of the approach, its applicability, and the effectiveness of reliability models. The techniques such as process algebras are generally considered time consuming, in regard to software development

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

Badger: Complexity Analysis with Fuzzing and Symbolic Execution

Hybrid testing approaches that involve fuzz testing and symbolic execution have shown promising results in achieving high code coverage, uncovering subtle errors and vulnerabilities in a variety of software applications. In this paper we describe Badger - a new hybrid approach for complexity analysis, with the goal of discovering vulnerabilities which occur when the worst-case time or space complexity of an application is significantly higher than the average case. Badger uses fuzz testing to generate a diverse set of inputs that aim to increase not only coverage but also a resource-related cost associated with each path. Since fuzzing may fail to execute deep program paths due to its limited knowledge about the conditions that influence these paths, we complement the analysis with a symbolic execution, which is also customized to search for paths that increase the resource-related cost. Symbolic execution is particularly good at generating inputs that satisfy various program conditions but by itself suffers from path explosion. Therefore, Badger uses fuzzing and symbolic execution in tandem, to leverage their benefits and overcome their weaknesses. We implemented our approach for the analysis of Java programs, based on Kelinci and Symbolic PathFinder. We evaluated Badger on Java applications, showing that our approach is significantly faster in generating worst-case executions compared to fuzzing or symbolic execution on their own