Moomba - A collaborative environment for supporting distributed extreme programming in global software development

Global Software Development (GSD) is an emerging distributive software engineering practice, in which a higher communication overhead due to temporal and geographical separation among developers is traded with gains in reduced development cost, improved flexibility and mobility for developers, increased access to skilled resource-pools and convenience of customer involvements. However, due to its distributive nature, GSD faces many fresh challenges in aspects relating to project coordination, awareness, collaborative coding and effective communication. New software engineering methodologies and processes are required to address these issues. Research has shown that, with adequate support tools, Distributed Extreme Programming (DXP) – a distributive variant of an agile methodology – Extreme Programming (XP) can be both efficient and beneficial to GDS projects. In this paper, we present the design and realization of a collaborative environment, called Moomba, which assists a distributed team in both instantiation and execution of a DXP process in GSD projects.

Heuristic algorithm for computing reversal distance with multigene families via binary integer programming

Hannenhalli and Pevzner developed the first polynomial-time algorithm for the combinatorial problem of sorting of signed genomic data. Their algorithm solves the minimum number of reversals required for rearranging a genome to another when gene duplication is nonexisting. In this paper, we show how to extend the Hannenhalli-Pevzner approach to genomes with multigene families. We propose a new heuristic algorithm to compute the reversal distance between two genomes with multigene families via the concept of binary integer programming without removing gene duplicates. The experimental results on simulated and real biological data demonstrate that the proposed algorithm is able to find the reversal distance accurately. ©2005 IEEE

The real-time refinement calculus: A foundation for machine-independent real-time programming

The real-time refinement calculus is an extension of the standard refinement calculus in which programs are developed from a precondition plus post-condition style of specification. In addition to adapting standard refinement rules to be valid in the real-time context, specific rules are required for the timing constructs such as delays and deadlines. Because many real-time programs may be nonterminating, a further extension is to allow nonterminating repetitions. A real-time specification constrains not only what values should be output, but when they should be output. Hence for a program to implement such a specification, it must guarantee to output values by the specified times. With standard programming languages such guarantees cannot be made without taking into account the timing characteristics of the implementation of the program on a particular machine. To avoid having to consider such details during the refinement process, we have extended our real-time programming language with a deadline command. The deadline command takes no time to execute and always guarantees to meet the specified time; if the deadline has already passed the deadline command is infeasible (miraculous in Dijkstra's terminology). When such a realtime program is compiled for a particular machine, one needs to ensure that all execution paths leading to a deadline are guaranteed to reach it by the specified time. We consider this checking as part of an extended compilation phase. The addition of the deadline command restores for the real-time language the advantage of machine independence enjoyed by non-real-time programming languages.

Computer-aided programming using formally specificed design templates

This paper describes a formal component language, used to support automated component-based program development. The components, referred to as templates, are machine processable, meaning that appropriate tool support, such as retrieval support, can be developed. The templates are highly adaptable, meaning that they can be applied to a wide range of problems. Some of the main features of the language are described, including: higher-order parameters; state variable declarations; specification statements and conditionals; applicability conditions and theories; meta-level place holders; and abstract data structures.