A method for re-modularising legacy code

This thesis proposes a method for the re-modularisation of legacy COBOL. Legacy code often performs a number of functions that if split, would improve software maintainability. For instance, program comprehension would benefit from a reduction in the size of the code modules. The method aims to identify potential reuse candidates from the functions re-modularised, and to ensure clear interfaces are present between the new modules. Furthermore, functionality is often replicated across applications and so the re-modularisation process can also seek to reduce commonality and hence the overall amount of a company's code requiring maintenance. A 10 step method is devised which assembles a number of new and existing techniques into an approach suitable for use by staff not having significant reengineering experience. Three main approaches are used throughout the method; that is the analysis of the PERFORM structure, the analysis of the data, and the use of graphical representations. Both top-down and bottom-up strategies to program comprehension are incorporated within the method as are automatable, and user controlled processes to reuse candidate selection. Three industrial case studies are used to demonstrate and evaluate the method. The case studies range in size to gain an indication of the scalability of the method. The case studies are used to evaluate the method on a step by step basis; both strong points and deficiencies are identified, as well as potential solutions to the deficiencies. A review is also presented to assesses the three main approaches of the methods; the analysis of the PERFORM and data structures, and the use of graphical representations. The review uses the process of software evolution for its evaluation using successive versions of COBOL software. The method is retrospectively applied to the earliest version and the known changes identified from the following versions are used to evaluate the re-modularisations. Within the evaluation chapters a new link within the dominance tree is proposed as is an approach for dealing with multiple dominance trees. The results show that «ach approach provides an important contribution to the method as well as giving a useful insight (in the form of graphical representations) of the process of software evolution

Evolution of batch-oriented COBOL systems into object-oriented systems through unified modelling language.

Throughout the world, there are many legacy systems that fulfil critical business functions but often require new functionality to comply with new business rules or require redeployment to another platform. Legacy systems vary tremendously in size, functionality, type (such as batch-oriented or real-time), programming language source code, and many other factors. Furthermore, many of these legacy systems have missing or obsolete documentation which makes it difficult for developers to re-develop the system to meet any new functionality. Moreover, the high cost of whole scale redevelopment and high switchover costs preclude any replacement systems for these legacy systems. Reengineering is often proposed as a solution to this dilemma of high re-development and switchover costs. However, reengineering a legacy system often entails restructuring and re-documenting a system. Once these restructuring and re-documentation processes have been completed, the developers are better able to redevelop the parts of the systems that are required to meet any new functionality. This thesis introduces a number of methods to restructure a procedurally-structured, batch-oriented COBOL system into an object-oriented, event-driven system through the use of an intermediate mathematical language, the Wide Spectrum Language (WSL), using system source code as the only documentation artefact. This restructuring process is accomplished through the application of several algorithms of object identification, independent task evaluation, and event identification that are provided in the thesis. Once these transformations are complete, method(s) are specified to extract a series of UML diagrams from this code in order to provide documentation of this system. This thesis outlines which of the UML diagrams, as specified in the UML Specifications version 1.5, can be extracted using the specified methods and under what conditions this extraction, using system source code only, can occur in a batch-oriented system. These UML diagrams are first expressed through a WSL-UML notation; a notation which follows the semantics and structure of UML Specifications version 1.5 in order to ensure compatibility with UML but is written as an extension of WSL in order to enable WSL to represent abstract modelling concepts and diagrams. This WSL-UML notation is then imported into a visual UML diagramming tool for the generation of UML diagrams to represent this system. The variety of legacy systems precludes any universal approach to reengineering. Even if a legacy system shares a common programming language, such as COBOL, the large number of COBOL constructs and the huge number of possible dialects prevents any universal translator of the original program code to another. It is hoped that by focusing on one particular type of legacy system with constraints, in this case a batch-oriented COBOL system with its source code its only surviving artefact, and by providing validated algorithms to restructure and re-document these legacy systems in the Unified Modelling Language, an industry system modelling standard, and by determining which of these Unified Modelling Language can be extracted practically from such a system, some of the parameters and uncertainties, such as program understanding of an undocumented system, in reengineering this type of system can be reduced

A Planning Approach to Migrating Domain-specific Legacy Systems into Service Oriented Architecture

The planning work prior to implementing an SOA migration project is very important for its success. Up to now, most of this kind of work has been manual work. An SOA migration planning approach based on intelligent information processing methods is addressed to semi-automate the manual work. This thesis will investigate the principle research question: “How can we obtain SOA migration planning schemas (semi-) automatically instead of by traditional manual work in order to determine if legacy software systems should be migrated to SOA computation environment?”. The controlled experiment research method has been adopted for directing research throughout the whole thesis. Data mining methods are used to analyse SOA migration source and migration targets. The mined information will be the supplementation of traditional analysis results. Text similarity measurement methods are used to measure the matching relationship between migration sources and migration targets. It implements the quantitative analysis of matching relationships instead of common qualitative analysis. Concretely, an association rule and sequence pattern mining algorithms are proposed to analyse legacy assets and domain logics for establishing a Service model and a Component model. These two algorithms can mine all motifs with any min-support number without assuming any ordering. It is better than the existing algorithms for establishing Service models and Component models in SOA migration situations. Two matching strategies based on keyword level and superficial semantic levels are described, which can calculate the degree of similarity between legacy components and domain services effectively. Two decision-making methods based on similarity matrix and hybrid information are investigated, which are for creating SOA migration planning schemas. Finally a simple evaluation method is depicted. Two case studies on migrating e-learning legacy systems to SOA have been explored. The results show the proposed approach is encouraging and applicable. Therefore, the SOA migration planning schemas can be created semi-automatically instead of by traditional manual work by using data mining and text similarity measurement methods

Search based software engineering: Trends, techniques and applications

© ACM, 2012. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version is available from the link below.In the past five years there has been a dramatic increase in work on Search-Based Software Engineering (SBSE), an approach to Software Engineering (SE) in which Search-Based Optimization (SBO) algorithms are used to address problems in SE. SBSE has been applied to problems throughout the SE lifecycle, from requirements and project planning to maintenance and reengineering. The approach is attractive because it offers a suite of adaptive automated and semiautomated solutions in situations typified by large complex problem spaces with multiple competing and conflicting objectives. This article provides a review and classification of literature on SBSE. The work identifies research trends and relationships between the techniques applied and the applications to which they have been applied and highlights gaps in the literature and avenues for further research.EPSRC and E

Evolving Legacy System\u27s Features into Fine-grained Components Using Regression Test-Cases

Because many software systems used for business today are considered legacy systems, the need for software evolution techniques has never been greater. We propose a novel evolution methodology for legacy systems that integrates the concepts of features, regression testing, and Component-Based Software Engineering (CBSE). Regression test suites are untapped resources that contain important information about the features of a software system. By exercising each feature with its associated test cases using code profilers and similar tools, code can be located and refactored to create components. The unique combination of Feature Engineering and CBSE makes it possible for a legacy system to be modernized quickly and affordably. We develop a new framework to evolve legacy software that maps the features to software components refactored from their feature implementation. In this dissertation, we make the following contributions: First, a new methodology to evolve legacy code is developed that improves the maintainability of evolved legacy systems. Second, the technique describes a clear understanding between features and functionality, and relationships among features using our feature model. Third, the methodology provides guidelines to construct feature-based reusable components using our fine-grained component model. Fourth, we bridge the complexity gap by identifying feature-based test cases and developing feature-based reusable components. We show how to reuse existing tools to aid the evolution of legacy systems rather than re-writing special purpose tools for program slicing and requirement management. We have validated our approach on the evolution of a real-world legacy system. By applying this methodology, American Financial Systems, Inc. (AFS), has successfully restructured its enterprise legacy system and reduced the costs of future maintenance

Ernst Denert Award for Software Engineering 2020

This open access book provides an overview of the dissertations of the eleven nominees for the Ernst Denert Award for Software Engineering in 2020. The prize, kindly sponsored by the Gerlind & Ernst Denert Stiftung, is awarded for excellent work within the discipline of Software Engineering, which includes methods, tools and procedures for better and efficient development of high quality software. An essential requirement for the nominated work is its applicability and usability in industrial practice. The book contains eleven papers that describe the works by Jonathan Brachthäuser (EPFL Lausanne) entitled What You See Is What You Get: Practical Effect Handlers in Capability-Passing Style, Mojdeh Golagha’s (Fortiss, Munich) thesis How to Effectively Reduce Failure Analysis Time?, Nikolay Harutyunyan’s (FAU Erlangen-Nürnberg) work on Open Source Software Governance, Dominic Henze’s (TU Munich) research about Dynamically Scalable Fog Architectures, Anne Hess’s (Fraunhofer IESE, Kaiserslautern) work on Crossing Disciplinary Borders to Improve Requirements Communication, Istvan Koren’s (RWTH Aachen U) thesis DevOpsUse: A Community-Oriented Methodology for Societal Software Engineering, Yannic Noller’s (NU Singapore) work on Hybrid Differential Software Testing, Dominic Steinhofel’s (TU Darmstadt) thesis entitled Ever Change a Running System: Structured Software Reengineering Using Automatically Proven-Correct Transformation Rules, Peter Wägemann’s (FAU Erlangen-Nürnberg) work Static Worst-Case Analyses and Their Validation Techniques for Safety-Critical Systems, Michael von Wenckstern’s (RWTH Aachen U) research on Improving the Model-Based Systems Engineering Process, and Franz Zieris’s (FU Berlin) thesis on Understanding How Pair Programming Actually Works in Industry: Mechanisms, Patterns, and Dynamics – which actually won the award. The chapters describe key findings of the respective works, show their relevance and applicability to practice and industrial software engineering projects, and provide additional information and findings that have only been discovered afterwards, e.g. when applying the results in industry. This way, the book is not only interesting to other researchers, but also to industrial software professionals who would like to learn about the application of state-of-the-art methods in their daily work

Supporting feature-level software maintenance

Software maintenance is the process of modifying a software system to fix defects, improve performance, add new functionality, or adapt the system to a new environment. A maintenance task is often initiated by a bug report or a request for new functionality. Bug reports typically describe problems with incorrect behaviors or functionalities. These behaviors or functionalities are known as features. Even in very well-designed systems, the source code that implements features is often not completely modularized. The delocalized nature of features makes maintaining them challenging. Since maintenance tasks are expressed in terms of features, the goal of this dissertation is to support software maintenance at the feature-level. We focus on two tasks in particular: feature location and impact analysis via feature coupling.;Feature location is the process of identifying the source code that implements a feature, and it is an essential first step to any maintenance task. There are many existing techniques for feature location that incorporate various types of analyses such as static, dynamic, and textual. In this dissertation, we recognize the advantages of leveraging several types of analyses and introduce a new approach to feature location based on combining dynamic analysis, textual analysis, and web mining algorithms applied to software. The use of web mining for feature location is a novel contribution, and we show that our new techniques based on web mining are significantly more effective than the current state of the art.;After using feature location to identify a feature\u27s source code, maintenance can be completed on that feature. Impact analysis should then be performed to revalidate the system and determine which other features may have been affected by the modifications. We define three feature coupling metrics that capture the relationship between features based on structural information, textual information, and their combination. Our novel feature coupling metrics can be used for impact analysis to quantify the strength of coupling between pairs of features. We performed three empirical studies on open-source software systems to assess the feature coupling metrics and established three major results. First, there is a moderate to strong statistically significant correlation between feature coupling and faults. Second, feature coupling can be used to correctly determine about half of the other features that would be affected by a change to a given feature. Finally, we found that the metrics align with developers\u27 opinions about pairs of features that are actually coupled