Extraction of objects from legacy systems: an example using cobol legacy systems

In the last few years the interest in legacy information system has increased because of the escalating resources spent on their maintenance. On the other hand, the importance of extracting knowledge from business rules is becoming a crucial issue for modern business: sometime, because of inappropriate documentation, this knowledge is essentially only stored in the code. A way to improve their use and maintainability in the present environment is to migrate them into a new hardware / software platform reusing as much of their experience as possible during this process. This migration process promotes the population of a repository of reusable software components for their reuse in the development of a new system in that application domain or in the later maintenance processes. The actual trend in the migration of a legacy information system, is to exploit the potentialities of object oriented technology as a natural extension of earlier structured programming techniques. This is done by decomposing the program into several agent-like modules communicating via message passing, and providing to this system some object oriented key features. The key step is the "object isolation", i.e. the isolation of .groups of routines and related data items : to candidates in order to implement an abstraction in the application domain. The main idea of the object isolation method presented here is to extract information from the data flow, to cluster all the procedures on the base of their data accesses. It will examine "how" a procedure accesses the data in order to distinguish several types of accesses and to permit a better understanding of the functionality of the candidate objects. These candidate modules support the population of a repository of reusable software components that might be used as a basis of the process of evolution leading to a new object oriented system reusing the extracted objects

Evaluating Legacy System Migration Technologies through Empirical Studies

We present two controlled experiments conducted with master students and practitioners and a case study conducted with practitioners to evaluate the use of MELIS (Migration Environment for Legacy Information Systems) for the migration of legacy COBOL programs to the web. MELIS has been developed as an Eclipse plug-in within a technology transfer project conducted with a small software company [16]. The partner company has developed and marketed in the last 30 years several COBOL systems that need to be migrated to the web, due to the increasing requests of the customers. The goal of the technology transfer project was to define a systematic migration strategy and the supporting tools to migrate these COBOL systems to the web and make the partner company an owner of the developed technology. The goal of the controlled experiments and case study was to evaluate the effectiveness of introducing MELIS in the partner company and compare it with traditional software development environments. The results of the overall experimentation show that the use of MELIS increases the productivity and reduces the gap between novice and expert software engineers

Pragmatic cost estimation for web applications

Cost estimation for web applications is an interesting and difficult challenge for researchers and industrial practitioners. It is a particularly valuable area of ongoing commercial research. Attaining on accurate cost estimation for web applications is an essential element in being able to provide competitive bids and remaining successful in the market. The development of prediction techniques over thirty years ago has contributed to several different strategies. Unfortunately there is no collective evidence to give substantial advice or guidance for industrial practitioners. Therefore to address this problem, this thesis shows the way by investigating the characteristics of the dataset by combining the literature review and industrial survey findings. The results of the systematic literature review, industrial survey and an initial investigation, have led to an understanding that dataset characteristics may influence the cost estimation prediction techniques. From this, an investigation was carried out on dataset characteristics. However, in the attempt to structure the characteristics of dataset it was found not to be practical or easy to get a defined structure of dataset characteristics to use as a basis for prediction model selection. Therefore the thesis develops a pragmatic cost estimation strategy based on collected advice and general sound practice in cost estimation. The strategy is composed of the following five steps: test whether the predictions are better than the means of the dataset; test the predictions using accuracy measures such as MMRE, Pred and MAE knowing their strengths and weaknesses; investigate the prediction models formed to see if they are sensible and reasonable model; perform significance testing on the predictions; and get the effect size to establish preference relations of prediction models. The results from this pragmatic cost estimation strategy give not only advice on several techniques to choose from, but also give reliable results. Practitioners can be more confident about the estimation that is given by following this pragmatic cost estimation strategy. It can be concluded that the practitioners should focus on the best strategy to apply in cost estimation rather than focusing on the best techniques. Therefore, this pragmatic cost estimation strategy could help researchers and practitioners to get reliable results. The improvement and replication of this strategy over time will produce much more useful and trusted results.Cost estimation for web applications is an interesting and difficult challenge for researchers and industrial practitioners. It is a particularly valuable area of ongoing commercial research. Attaining on accurate cost estimation for web applications is an essential element in being able to provide competitive bids and remaining successful in the market. The development of prediction techniques over thirty years ago has contributed to several different strategies. Unfortunately there is no collective evidence to give substantial advice or guidance for industrial practitioners. Therefore to address this problem, this thesis shows the way by investigating the characteristics of the dataset by combining the literature review and industrial survey findings. The results of the systematic literature review, industrial survey and an initial investigation, have led to an understanding that dataset characteristics may influence the cost estimation prediction techniques. From this, an investigation was carried out on dataset characteristics. However, in the attempt to structure the characteristics of dataset it was found not to be practical or easy to get a defined structure of dataset characteristics to use as a basis for prediction model selection. Therefore the thesis develops a pragmatic cost estimation strategy based on collected advice and general sound practice in cost estimation. The strategy is composed of the following five steps: test whether the predictions are better than the means of the dataset; test the predictions using accuracy measures such as MMRE, Pred and MAE knowing their strengths and weaknesses; investigate the prediction models formed to see if they are sensible and reasonable model; perform significance testing on the predictions; and get the effect size to establish preference relations of prediction models. The results from this pragmatic cost estimation strategy give not only advice on several techniques to choose from, but also give reliable results. Practitioners can be more confident about the estimation that is given by following this pragmatic cost estimation strategy. It can be concluded that the practitioners should focus on the best strategy to apply in cost estimation rather than focusing on the best techniques. Therefore, this pragmatic cost estimation strategy could help researchers and practitioners to get reliable results. The improvement and replication of this strategy over time will produce much more useful and trusted results

Acquiring data designs from existing data-intensive programs

The problem area addressed in this thesis is extraction of a data design from existing data intensive program code. The purpose of this is to help a software maintainer to understand a software system more easily because a view of a software system at a high abstraction level can be obtained. Acquiring a data design from existing data intensive program code is an important part of reverse engineering in software maintenance. A large proportion of software systems currently needing maintenance is data intensive. The research results in this thesis can be directly used in a reverse engineering tool. A method has been developed for acquiring data designs from existing data intensive programs, COBOL programs in particular. Program transformation is used as the main tool. Abstraction techniques and the method of crossing levels of abstraction are also studied for acquiring data designs. A prototype system has been implemented based on the method developed. This involved implementing a number of program transformations for data abstraction, and thus contributing to the production of a tool. Several case studies, including one case study using a real program with 7000 Hues of source code, are presented. The experiment results show that the Entity-Relationship Attribute Diagrams derived from the prototype can represent the data designs of the original data intensive programs. The original contribution of the thesis is that the approach presented in this thesis can identify and extract data relationships from the existing code by combining analysis of data with analysis of code. The approach is believed to be able to provide better capabilities than other work in the field. The method has indicated that acquiring a data design from existing data intensive program code by program transformation with human assistance is an effective method in software maintenance. Future work is suggested at the end of the thesis including extending the method to build an industrial strength tool

Complex adaptive systems based data integration : theory and applications

Data Definition Languages (DDLs) have been created and used to represent data in programming languages and in database dictionaries. This representation includes descriptions in the form of data fields and relations in the form of a hierarchy, with the common exception of relational databases where relations are flat. Network computing created an environment that enables relatively easy and inexpensive exchange of data. What followed was the creation of new DDLs claiming better support for automatic data integration. It is uncertain from the literature if any real progress has been made toward achieving an ideal state or limit condition of automatic data integration. This research asserts that difficulties in accomplishing integration are indicative of socio-cultural systems in general and are caused by some measurable attributes common in DDLs. This research’s main contributions are: (1) a theory of data integration requirements to fully support automatic data integration from autonomous heterogeneous data sources; (2) the identification of measurable related abstract attributes (Variety, Tension, and Entropy); (3) the development of tools to measure them. The research uses a multi-theoretic lens to define and articulate these attributes and their measurements. The proposed theory is founded on the Law of Requisite Variety, Information Theory, Complex Adaptive Systems (CAS) theory, Sowa’s Meaning Preservation framework and Zipf distributions of words and meanings. Using the theory, the attributes, and their measures, this research proposes a framework for objectively evaluating the suitability of any data definition language with respect to degrees of automatic data integration. This research uses thirteen data structures constructed with various DDLs from the 1960\u27s to date. No DDL examined (and therefore no DDL similar to those examined) is designed to satisfy the law of requisite variety. No DDL examined is designed to support CAS evolutionary processes that could result in fully automated integration of heterogeneous data sources. There is no significant difference in measures of Variety, Tension, and Entropy among DDLs investigated in this research. A direction to overcome the common limitations discovered in this research is suggested and tested by proposing GlossoMote, a theoretical mathematically sound description language that satisfies the data integration theory requirements. The DDL, named GlossoMote, is not merely a new syntax, it is a drastic departure from existing DDL constructs. The feasibility of the approach is demonstrated with a small scale experiment and evaluated using the proposed assessment framework and other means. The promising results require additional research to evaluate GlossoMote’s approach commercial use potential

Missoula VoTech Course Catalog, 1982-1983

Course catalog for Missoula VoTech (now Missoula College).https://scholarworks.umt.edu/votechcoursecatalogs/1007/thumbnail.jp

A software classification scheme

Reusing code is one approach to software reusability. Code is the end product of the software lifecycle. It is delivered in a low level representation that is difficult to reuse unless an almost perfect match exists between available features and required specifications. There is a need to organize large inventories of software such that reusable code is easy to locate and exchange. The relative success in the reuse of code fragments reported by some software factories is due in part to their capacity to encapsulate domain specific functions and create specialized libraries of components classified by these locally standardized functions.A general software classification scheme that organizes reusability related attributes and common functions from different domains is proposed as a partial solution to the software reusability problem. For the problem of selecting from similar, potentially reusable. components, a partial solution based on evaluation of common characteristics is also proposed. A library system is presented that integrates the proposed classification scheme with an evaluation mechanism based on inherent component attributes, programming languages characteristics and reuser experience.The fundamental contribution of this dissertation is a formal treatment of a faceted scheme for software classification leading to better understanding of reusability at the code level. This approach has been prototyped in a library system for the semi-automatic classification of software components. Analysis were performed to evaluate the classification scheme. The results show the potential of the scheme in organizing collections of code fragments, in improving retrieval, and in simplifying the classification process. Tests of the evaluation mechanism showed positive correlation with evaluations conducted by potential reusers