REENGINEERING TECHNIQUE ADAPTATION OF LEGACY SOFTWARE SYSTEMS

В статье рассматривается адаптация методики реинжиниринга унаследованных систем. Приводится обзор подходов к реинжинирингу. Несмотря на то, что термин «реинжиниринг» в первую очередь относится к изменению бизнес процессов, он удачно подходит и к модернизации программного обеспечения. Обосновывается необходимость адаптации методики. В статье описывается применение адаптированной методики на примере реинжиниринга программного комплекса для прогнозных исследований ТЭК. Приведен исторический обзор версий ПК «ИНТЭК» и описаны поэтапно все шаги проведения его реинжиниринга на основе агентно-сервисного подхода The article presents an adaptation of the legacy systems reengineering technique. An overview of approaches to reengineering is given. Although the term “reengineering” primarily refers to changing business processes, it is well suited to software development. The necessity of adapting the method has been substantiated. The article describes the application of the described methodology on the example of software complex reengineering for predictive research of the fuel and energy complex. A historical overview of the current problem is given and all stages of INTEC PC reengineering are described step by step

Detecting the Most Important Classes from Software Systems with Self Organizing Maps

Self Organizing Maps (SOM) are unsupervised neural networks suited for visualisation purposes and clustering analysis. This study uses SOM to solve a software engineering problem: detecting the most important (key) classes from software projects. Key classes are meant to link the most valuable concepts of a software system and in general these are found in the solution documentation. UML models created in the design phase become deprecated in time and tend to be a source of confusion for large legacy software. Therefore, developers try to reconstruct class diagrams from the source code using reverse engineering. However, the resulting diagram is often very cluttered and difficult to understand. There is an interest for automatic tools for building concise class diagrams, but the machine learning possibilities are not fully explored at the moment. This paper proposes two possible algorithms to transform SOM in a classification algorithm to solve this task, which involves separating the important classes - that should be on the diagrams - from the others, less important ones. Moreover, SOM is a reliable visualization tool which able to provide an insight about the structure of the analysed projects.

Multi-GNSS Single-Difference Baseline Processing at NGS with newly developed M-PAGES software

<p>The U.S. National Geodetic Survey (NGS) has historically processed dual-frequency GPS observations in a double-differenced mode using the legacy software called the Program for the Adjustment of GPS Ephemerides (PAGES). As part of NGS’ modernization efforts, a new software suite named M-PAGES (i.e., Multi-GNSS PAGES) is being developed to replace PAGES. M-PAGES consists of a suite of C++ and Python libraries, programs, and scripts built to process observations from all GNSS constellations. The M-PAGES team has developed a single-difference baseline processing strategy that is suitable for multi-GNSS. This approach avoids the difficulty of forming double-differences across systems or frequencies, which may inhibit integer ambiguity resolution. The M-PAGES suite is expected to deploy to NGS’ Online Positioning User Service (OPUS) later this year. Here, we present the processing strategy being implemented along with a performance evaluation from sample baseline solutions obtained from data collected within the NOAA CORS Network.</p>

Evolution of existing software to mobile computing platforms: Framework support and case study

Mobile computing as ubiquitous and pervasive technology supports portable and context-aware computation. To date, there exist a significant number of traditional computing systems–running on the web and/or workstation-based platforms–that lack features of mobile computing, including but not limited to ubiquity, context-sensing, and high interactivity. Software that executes on these traditional computing systems is referred to as legacy software that can be upgraded to exploit the features of mobile technologies. However, legacy software may contain critical data, logic, and processes that cannot be easily replaced. One of the solutions is to evolve legacy software systems by (a) upgrading their functionality while (b) preserving their data and logic. Recently research and development efforts are focused on modernizing the legacy systems as per the needs of service and cloud-based platforms. However, there does not exist any research that supports a systematic modernization of legacy software as per the requirements of the mobile platforms. We propose a framework named Legacy-to-Mobile as a solution that supports an incremental and process-driven evolution of the legacy software to mobile computing software. The proposed Legacy-to-Mobile framework unifies the concepts of software reverse engineering (recovering software artifacts) and software change (upgrading software artifacts) to support the legacy evolution. The framework follows an incremental approach with four processes that include (i) evolution planning, (ii) architecture modeling, (iii) architecture change, and (iv) software validation of mobile computing software. The framework provides the foundation (as part of futuristic research) to develop a tool prototype that supports automation and user decision support for incremental and process-driven evolution of legacy software to mobile computing platforms.

Refactoring Legacy Software for Layer Separation

One of the main aims in the layered software architecture is to divide the code into different layers so that each layer contains related modules and serves its upper layers. Although layered software architecture is matured now; many legacy information systems do not benefit from the advantages of this architecture and their code for the process/business and data access are mostly in a single layer. In many legacy systems, due to the integration of the code in one layer, changes to the software and its maintenance are mostly difficult. In addition, the big size of a single layer causes the load concentration and turns the server into a bottleneck where all requests must be executed on it. In order to eliminate these deficiencies, this paper presents a refactoring mechanism for the automatic separation of the business and data access layers by detecting the data access code based on a series of patterns in the input code and transferring it to a new layer. For this purpose, we introduce a code scanner which detects the target points based on these patterns and hence automatically makes the changes required for the layered architecture. According to the experimental evaluation results, the performance of the system is increased for the layer separated software using the proposed approach. Furthermore, it is examined that the application of the proposed approach provides additional benefits considering the qualitative criteria such as loosely coupling and tightly coherency.

Extracting Interactive Actor-Based Dataflow Models from Legacy C Code

Graphical actor-based models provide an abstract overview of the flow of data in a system. They are well-established for the model-driven engineering (MDE) of complex software systems and are supported by numerous commercial and academic tools, such as Simulink, LabVIEW or Ptolemy. In MDE, engineers concentrate on constructing and simulating such models, before application code (or at least a large fraction thereof) is synthesized automatically. However, a significant fraction of today’s legacy system has been coded directly, often using the C language. High-level models that give a quick, accurate overview of how components interact are often out of date or do not exist. This makes it challenging to maintain or extend legacy software, in particular for new team members.To address this problem, we here propose to reverse the classic synthesis path of MDE and to synthesize actor-based dataflow models automatically from source code. Here functions in the code get synthesized into nodes that represent actors manipulating data. Second, we propose to harness the modeling-pragmatic approach, which considers visual models not as static artefacts, but allows interactive, flexible views that also link back to textual descriptions. Thus we propose to synthesize actor models that can vary in level of detail and that allow navigation in the source code. To validate and evaluate our proposals, we implemented these concepts for C analysis in the open source, Eclipse-based KIELER project and conducted a small survey.