Supporting software evolution through dynamically retrieving traces to UML artifacts

Context: Successful software systems continuously evolve to accommodate feature requests of a diverse customer-base. At some point during this evolution, the variety of customer needs and increased system complexity suggests the consideration of a software product line (SPL).Aim: The goal of this research is to support the decision maker facing the enhancement of an evolving software system (ESS) by determining the most appropriate product line design (out of a given set of candidate SPL portfolios) to minimize the technical risk and maximize the business value.Method: The proposed method called OPTESS is aimed at finding an evolution plan for the ESS which optimizes both the given technical and business objectives. Business analysis using a value-based pricing mechanism is applied to a set of initially proposed SPL portfolios (for enhancing the ESS) such that profit is maximized. Technical analysis is applied to the same initially proposed SPL portfolios to minimize the risk of failure of ESS due to implementation of new features. Business and technical analyses improve the performance of solutions for their respective objectives by modifying the feature sets of candidate SPL portfolios. OPTESS helps the decision maker select a plan for enhancement of an ESS by performing trade- off analysis between economic and technical objectives.Results: The method was initially evaluated through a case study for a set of 9 new candidate features to be added to an open source text editing system called jEdit. OPTESS helped the decision maker to identify 3 non-dominated solutions judged to be the best contenders for addition when considering both technical and economic criteria.

Identifying a strategy for legacy software system evolution requires analysis and assessment activities. Information on performance and costs of software systems must be considered when making decisions on the most suitable strategy to be applied. Many approaches have been defined for supporting this task, and several authors have proposed decision frameworks for aiding the selection of evolution strategy. These approaches often lack of techniques for the management of uncertainty, traditionally considered as unscientific and as a source of errors and arising from the confidence of the answers provided by respondents. An approach previously proposed is analyzed and extended with fuzzy logic concepts. The approach uses a measurement framework based on the Goal-Question-Metric (GQM) paradigm and a set of critiquing tables. Fuzzy logic principles have been introduced in both components, for obtaining a better insight of the analyzed software system quality and an indication of the risks to be assumed when one selected strategy is adopted instead of another.

The Web has become a large repository of documents (or pages) written in many different languages. In this context, traditional information retrieval (IR) techniques cannot be used whenever the user query and the documents being retrieved are in different languages. To address this problem, new cross‐language information retrieval (CLIR) techniques have been proposed. In this work, we describe a method for cross‐language retrieval of medical information. This method combines query terms and related medical concepts obtained automatically through a categorization procedure. The medical concepts are used to create a linguistic abstraction that allows retrieval of information in a language‐independent way, minimizing linguistic problems such as polysemy. To evaluate our method, we carried out experiments using the OHSUMED test collection, whose documents are written in English, with queries expressed in Portuguese, Spanish, and French. The results indicate that our cross‐language retrieval method is as effective as a standard vector space model algorithm operating on queries and documents in the same language. Further, our results are better than previous results in the literature.

The Web enables to have access to silo-ed information describing news articles, often offering a multitude of viewpoints that, once combined, can provide a broader picture of the story being reported on the news. In this paper, we propose an approach that automatically extracts representative features of a news item, namely named entities, from textual content attached to a video item (subtitles) and from a set of documents from the Web collected using entity expansion techniques. Approaches relying on entity expansion generally try to collect and process the important facts behinds a particular news item, but they are often too dependent on frequency-based functions and information retrieval techniques thus neglecting the multi-dimensional relationships that are established among the entities. We propose a concentric-based approach that enables to represent the context of a news item, by harmonizing into a single model the representative entities, which can be extracted using information retrieval and natural language processing techniques (Core), and other entities that get prominent according to different dimensions such as informativeness, semantic connectivity, or popularity (Crust). We compare our approach with a baseline by analyzing the compactness of the generated summary on an existing gold standard available on the Web. Results of the experiments show that our approach converges faster to the ideal compact news snapshot with an improvement of 36.9% over the baseline.

Companies often develop and maintain a collection of product variants that share some common features but also support different, customer-specific features. To reengineering such legacy product variants for systematic reuse, one must identify features and their implementing code units (e.g. functions, files) in different product variants. Information retrieval (IR) techniques may be applied for that purpose. In this paper, we discuss problems that hinder direct application of IR techniques to a collection of product variants. To counter these problems, we present an approach to support effective feature location in product variants. The novelty of our approach is that we exploit commonalities and differences of product variants by software differencing and FCA techniques so that IR technique can achieve satisfactory results for feature location in product variants. We have implemented our approach and conducted evaluation with a collection of nine Linux kernel product variants. Our evaluation shows that our approach always significantly outperforms a direct application of IR technique in the subject product variants.

Metric-based Evaluation of Implemented Software Architectures

Pengembangan perangkat lunak adalah tugas kompleks dan membutuhkan adaptasi untuk mengakomodasi kebutuhan pengguna. Untuk membuat konsep dan perubahan perangkat lunak, dalam pemeliharaan, sekarang telah dikembangkan lebih mudah dalam pengembangan perangkat lunak, pola model-view-controller, yang merupakan arsitektur yang dapat membantu memfasilitasi dalam pengembangan dan pemeliharaan perangkat luna. Hal ini, karena dalam arsitektur model tiga-lapis, yaitu: tampilan dan pengontrolan dalam pembangunan dilakukan secara independen, sehingga dapat memberikan dahan dalam pengembangan dan pemeliharaan. Selain itu, arsitektur ini juga dapat melihat hal-hal yang sederhana dan menarik bagi pengguna. Software sistem on-line test adalah perangkat lunak yang memerlukan interaksi dengan pengguna, dan pemeliharaan perangkat adaptif. Karena sistem ujian on-line memerlukan pengembangan perangkat lunak untuk mengakomodasi kebutuhan ini berkembang dengan cepat. Makalah ini untuk menganalisis Model-View-Controller dan mencoba pembangunan, untuk menerapkannya dalam pengembangan perangkat lunak sistem pengujian on-line.

This chapter provides a perspective on a problem-based learning (PBL) approach to teaching information retrieval (IR) theory, techniques, and practice at under- and postgraduate levels. The educational philosophy of PBL is outlined, and its pertinence to addressing the challenges of teaching IR in terms of both the diverse nature of the subject and also of the students is discussed. It is argued that teaching IR as a solution to a problem (access to information) and as a problem (how can we organize information in IR systems so it can be accessed) provides an engaging and challenging way to teach it to a range of students. It also draws connections between IR theory and techniques and relates IR to other disciplines through showing how similar problems are faced in other subjects. Some specific examples of teaching exercises based on PBL are provided with a discussion and reflection on their effectiveness. Finally assessment and feedback from students are discussed.

Being such a vast resource of information, World Wide Web has become irreplaceable but the outburst of information available over the internet has made web search a time consuming and a very complex process. Now days if someone need to retrieve any information using internet they come across huge number of web pages because of large amount of data on web. It becomes difficult task to find information so in order to retrieve meaningful and intelligent information we have many information retrieval (IR) techniques. To gather the significant information from such a vast available resource Information Retrieval (IR); a method of retrieving such information resources which are relevant to an information need is applied. This paper would review few of these methods for intelligent information retrieval systems on web based on the Ontology information retrieval techniques.

The decision on whether to proceed to top-down or bottom-up during software development has a strong and underestimated impact on the quality of the final product including its later evolvability. Various examples for both strategies taken from such different domains as operating systems and computer games provide evidence that bottom-up developed systems are more suitable for future evolution. The reasons for this range from the increased compositionality of bottom-up developed artefacts at the technical level up to a greater independence from certain requirements which constitute the most transient part of a software system. Besides those advantages concerning evolvability, the negative effects of bottom-up orientation can not be ignored. Furthermore, proceeding bottom-up contradicts most conventional development processes. We regard this as a clear indication for the need of new development processes to improve the construction of evolvable software.

Tracking a variety of traceability links between artifacts assists software developers in comprehension, efficient development, and effective management of a system. Traceability systems to date based on various Information Retrieval (IR) techniques have been faced with a major open research challenge: how to extract these links with both high precision and high recall. In this paper we describe an experimental approach that combines Regular Expression, Key Phrases, and Clustering with IR techniques to enhance the performance of IR for traceability link recovery between documents and source code. Our preliminary experimental results show that our combination technique improves the performance of IR, increases the precision of retrieved links, and recovers more true links than IR alone.

Data is arguably the most valuable asset of the modern world. In this era, the success of any data-intensive solution relies on the quality of data that drives it. Among vast amount of data that are captured, managed, and analyzed everyday, geospatial data are one of the most interesting class of data that hold geographical information of real-world phenomena and can be visualized as digital maps. Geo-spatial data is the source of many enterprise solutions that provide local information and insights. In order to increase the quality of such solutions, companies continuously aggregate geospatial datasets from various sources. However, lack of a global standard model for geospatial datasets makes the task of merging and integrating datasets difficult and error-prone. Traditionally, domain experts manually validate the data integration process by merging new data sources and/or new versions of previous data against conflicts and other requirement violations. However, this approach is not scalable and is hinder toward rapid release, when dealing with frequently changing big datasets. Thus more automated approaches with limited interaction with domain experts is required. As a first step to tackle this problem, in this paper, we leverage Information Retrieval (IR) and geospatial search techniques to propose a systematic and automated conflict identification approach. To evaluate our approach, we conduct a case study in which we measure the accuracy of our approach in several real-world scenarios and we interview with software developers at Localintel Inc. (our industry partner) to get their feedbacks.

Our objective is to perform an empirical investigation on factors affecting software developer acceptance and utilization of electronic process guides (EPGs) and to discuss the implications of the findings. The potential benefits of EPGs can only be realized when key capabilities are not only adopted, but also infused across the organization. We conducted a survey of 97 software developers in a medium-sized software company to test the importance of organizational support and four factors on the perceived attributes of using the EPG to its infusion. The results showed that perceived usefulness is the fundamental driver in explaining current system usage and future use intentions, and furthermore, that perceived compatibility, perceived ease of use, and organizational support were the key determinants of perceived usefulness. This study advances our understanding of software developers' acceptance and utilization of EPGs in a voluntary setting. This way, software organizations can learn more about the determinants of successfully adopting and infusing EPGs and, accordingly, to take more appropriate actions.

Software restructuring is the process of re-organizing the logical structure of existing software systems in order to improve particular quality attributes of software products. During design or maintenance, software developers often use intuition, rather than an objective set of criteria, to determine, recapture, or restructure the design of a software system. In this dissertation, we provide a quantitative framework for software restructuring. In the framework, restructuring decisions are guided by visualized design information and quantitative design-level measures. The restructuring process is automated by supporting tools. A set of design-level cohesion and coupling measures provides the objective criteria for comparing alternative design structures. They are derived, compared, and applied in our software restructuring framework. The process insures that restructuring results in measurable and visible improvements in design quality. Applying our framework can result in restructured software systems that are easier to maintain and reuse.

The capability of an enterprise to innovate and promptly and effectively respond to change requests coming from both internal and external drivers has nowadays become a measure of the competitiveness of the enterprise in all business sectors. Innovation often implies modifying the enterprise business processes and, as a consequence, requires the evolution of the enterprise software systems. In this context, the workshop on Evolution of Software Systems in a Business Context (ESSBC), held in Budapest, Hungary, as part of the IEEE Software Technology and Engineering Practice workshop series (STEP 2005), aimed at discussing experiences and research outcomes and identifying research issues in supporting the evolution of enterprise software systems to reach innovation goals