A holistic approach to managing software change impact

Change is inevitable in the software product lifecycle. When a software change occurs, all of the stakeholders and related artifacts should be considered in determining the success of the change action in a collaborative development environment such as JAD (joint application development). In this regard, current implementation-based or homogeneous impact analyses are insufficient; therefore, this paper presents a holistic approach to change impact analysis in handling not only software contents but also other items such as requirements, documents and data. This approach characterizes product contents and relates heterogeneous items by using attributes and linkages. It also uses an object-oriented propagation mechanism to handle dynamic looping in determining the impact of changes. A prototype, EPIC, was built to realize this approach and these concepts. A walkthrough example is provided in order to verify the work of the proposed approach. An empirical study is presented to discuss the benefits of the proposed approach and the application of EPIC in a software company. Lessons learned from the case study and improvement issues of the proposed approach and the tool are also discussed.     

Product ranking using hierarchical aspect structures

Product-related comparative reviews are one of the most helpful information sources for consumers to rank the competing products and make purchase decisions. The comparative reviews are even more valuable if they are concerning specific aspects. However, the fact that very few comparative reviews express direct opinions on product aspects makes aspect-based product ranking a difficult task. In this paper, we present a novel hierarchical aspect-based product ranking approach. We first mine aspect-based pairwise comparative opinions from both user reviews on multiple review websites and community-based question answering pairs containing product comparison information. Next, we use our hierarchical structure-based model to propagate and reassign the aspect-based comparative opinions by using the parent-child and sibling relations between aspects in the product aspect hierarchy. The structure-based model helps to address the data sparsity issue of very few or no comparative reviews for some aspects. Finally, we employ graph-based ordering algorithms to consolidate these reassigned pairwise opinions into listwise comparison results. Experiments on a set of candidate electronic products prove that the proposed approach is effective for aspect-based product ranking.     

A novel rating prediction method based on user relationship and natural noise

Rating prediction is a hot spot in the research of recommender systems. There are lots of methods in this field such as collaborative filtering. However, few of these approaches take users’ friendship relationships into consideration, which actually contain significant information for rating prediction. Besides, there exists natural noise in users’ ratings. In this paper, we propose a rating prediction algorithm named NF-SVM based on the analysis of users’ natural noise and relationships. We cluster users to sharpen the similarity attribute among users, and use an iterative algorithm to obtain the rank of users’ rating quality. Then, we analyze users’ rating history to obtain the attributes of users’ natural noise. All these attributes are used to build a training set for SVM to get a prediction model. We also tested our algorithm in a data set which is crawled down from Douban, one of the largest movie rating web sites in China. Then we compared our algorithm with other state-of-the-art rating prediction methods. Extensive experiments show that our algorithm outperforms the other algorithms.     

Model-based pairwise testing for feature interaction coverage in software product line engineering

Testing software product lines (SPLs) is very challenging due to a high degree of variability leading to an enormous number of possible products. The vast majority of today??s testing approaches for SPLs validate products individually using different kinds of reuse techniques for testing. Because of their reusability and adaptability capabilities, model-based approaches are suitable to describe variability and are therefore frequently used for implementation and testing purposes of SPLs. Due to the enormous number of possible products, individual product testing becomes more and more infeasible. Pairwise testing offers one possibility to test a subset of all possible products. However, according to the best of our knowledge, there is no contribution discussing and rating this approach in the SPL context. In this contribution, we provide a mapping between feature models describing the common and variable parts of an SPL and a reusable test model in the form of statecharts. Thereby, we interrelate feature model-based coverage criteria and test model-based coverage criteria such as control and data flow coverage and are therefore able to discuss the potentials and limitations of pairwise testing. We pay particular attention to test requirements for feature interactions constituting a major challenge in SPL engineering. We give a concise definition of feature dependencies and feature interactions from a testing point of view, and we discuss adequacy criteria for SPL coverage under pairwise feature interaction testing and give a generalization to the T-wise case. The concept and implementation of our approach are evaluated by means of a case study from the automotive domain.     

Fully employing software inspections data

Software inspections provide a proven approach to quality assurance for software products of all kinds, including requirements, design, code, test plans, among others. Common to all inspections is the aim of finding and fixing defects as early as possible, and thereby providing cost savings by minimizing the amount of rework necessary later in the life cycle. Measurement data, such as the number and type of found defects and the effort spent by the inspection team, provide not only direct feedback about the software product to the project team, but are also valuable for process improvement activities. In this paper, we discuss NASA??s use of software inspections and the rich set of data that has resulted. In particular, we present results from analysis of inspection data that illustrate the benefits of fully utilizing that data for process improvement at several levels. Examining such data across multiple inspections or projects allows team members to monitor and trigger cross project improvements. Such improvements may focus on the software development processes of the whole organization as well as improvements to the applied inspection process itself.     

Quality-aware analysis in product line engineering with the orthogonal variability model

Software product line engineering is about producing a set of similar products in a certain domain. A variability model documents the variability amongst products in a product line. The specification of variability can be extended with quality information, such as measurable quality attributes (e.g., CPU and memory consumption) and constraints on these attributes (e.g., memory consumption should be in a range of values). However, the wrong use of constraints may cause anomalies in the specification which must be detected (e.g., the model could represent no products). Furthermore, based on such quality information, it is possible to carry out quality-aware analyses, i.e., the product line engineer may want to verify whether it is possible to build a product that satisfies a desired quality. The challenge for quality-aware specification and analysis is threefold. First, there should be a way to specify quality information in variability models. Second, it should be possible to detect anomalies in the variability specification associated with quality information. Third, there should be mechanisms to verify the variability model to extract useful information, such as the possibility to build a product that fulfils certain quality conditions (e.g., is there any product that requires less than 512?MB of memory?). In this article, we present an approach for quality-aware analysis in software product lines using the orthogonal variability model (OVM) to represent variability. We propose to map variability represented in the OVM associated with quality information to a constraint satisfaction problem and to use an off-the-shelf constraint programming solver to automatically perform the verification task. To illustrate our approach, we use a product line in the automotive domain which is an example that was created in a national project by a leading car company. We have developed a prototype tool named FaMa-OVM, which works as a proof of concepts. We were able to identify void models, dead and false optional elements, and check whether the product line example satisfies quality conditions.     

Operationalised product quality models and assessment: The Quamoco approach

ContextSoftware quality models provide either abstract quality characteristics or concrete quality measurements; there is no seamless integration of these two aspects. Quality assessment approaches are, hence, also very specific or remain abstract. Reasons for this include the complexity of quality and the various quality profiles in different domains which make it difficult to build operationalised quality models.ObjectiveIn the project Quamoco, we developed a comprehensive approach aimed at closing this gap.MethodThe project combined constructive research, which involved a broad range of quality experts from academia and industry in workshops, sprint work and reviews, with empirical studies. All deliverables within the project were peer-reviewed by two project members from a different area. Most deliverables were developed in two or three iterations and underwent an evaluation.ResultsWe contribute a comprehensive quality modelling and assessment approach: (1) A meta quality model defines the structure of operationalised quality models. It includes the concept of a product factor, which bridges the gap between concrete measurements and abstract quality aspects, and allows modularisation to create modules for specific domains. (2) A largely technology-independent base quality model reduces the effort and complexity of building quality models for specific domains. For Java and C# systems, we refined it with about 300 concrete product factors and 500 measures. (3) A concrete and comprehensive quality assessment approach makes use of the concepts in the meta-model. (4) An empirical evaluation of the above results using real-world software systems showed: (a) The assessment results using the base model largely match the expectations of experts for the corresponding systems. (b) The approach and models are well understood by practitioners and considered to be both consistent and well suited for getting an overall view on the quality of a software product. The validity of the base quality model could not be shown conclusively, however. (5) The extensive, open-source tool support is in a mature state. (6) The model for embedded software systems is a proof-of-concept for domain-specific quality models.ConclusionWe provide a broad basis for the development and application of quality models in industrial practice as well as a basis for further extension, validation and comparison with other approaches in research.     

Comparing data summaries for processing live queries over Linked Data

A growing amount of Linked Data??graph-structured data accessible at sources distributed across the Web??enables advanced data integration and decision-making applications. Typical systems operating on Linked Data collect (crawl) and pre-process (index) large amounts of data, and evaluate queries against a centralised repository. Given that crawling and indexing are time-consuming operations, the data in the centralised index may be out of date at query execution time. An ideal query answering system for querying Linked Data live should return current answers in a reasonable amount of time, even on corpora as large as the Web. In such a live query system source selection??determining which sources contribute answers to a query??is a crucial step. In this article we propose to use lightweight data summaries for determining relevant sources during query evaluation. We compare several data structures and hash functions with respect to their suitability for building such summaries, stressing benefits for queries that contain joins and require ranking of results and sources. We elaborate on join variants, join ordering and ranking. We analyse the different approaches theoretically and provide results of an extensive experimental evaluation.     

An SVD-Entropy and bilinearity based product ranking algorithm using heterogeneous data

E-commerce websites, besides selling products and services, pay ample emphasis on providing a platform for consumers to share their opinions about past and potential purchases. They share such opinions as product reviews (star ratings, plain text, etc.) and answering product related questions (Q&A data). There are several machine learning and classification approaches available to scrutinize this review data, e.g., algorithms based on Entropy measures, Bilinear Similarity, stochastic methods, etc. In this paper, we review some of the prevalent review classification techniques and present a hybrid approach, involving Singular Value Decomposition (SVD), Entropy and Bilinear Similarity measures, that uses heterogeneous product data and simultaneously analyze and rank products for customers. With experimental results, we show that our approach effectively ranks products using (1) text reviews (2) Q&A data (3) five-star rating of products and has 10% improved prediction accuracy as compared to the individual approaches. Also, using SVD, we achieve a 35% runtime efficiency for our algorithm while only sacrificing 1% of the prediction accuracy.     

基于用户信任和兴趣的概率矩阵分解推荐方法

传统协同过滤推荐算法存在数据稀疏性、冷启动、新用户等问题.随着社交网络和电子商务的迅猛发展,利用用户间的信任关系和用户兴趣提供个性化推荐成为研究的热点.本文提出一种结合用户信任和兴趣的概率矩阵分解（STUIPMF）推荐方法.该方法首先从用户评分角度挖掘用户间的隐性信任关系和潜在兴趣标签,然后利用概率矩阵分解模型对用户评分信息、用户信任关系、用户兴趣标签信息进行矩阵分解,进一步挖掘用户潜在特征,缓解数据稀疏性.在Epinions数据集上进行实验验证,结果表明,该方法能够在一定程度上提高推荐精度,缓解冷启动和新用户问题,同时具有较好的可扩展性.     

Manufacturing evaluation using resource-based, template-free features

This paper addresses the theory and tools that promote rapid product and process development of machined products. A foundation of this approach is the application of a new definition of manufacturing features called resource-based free-form features. Using free-form features we demonstrate how cost, time and quality predictions, based on available equipment, are computed. We also introduce the concept of intelligently clustering alternative features to achieve better process alternatives. The approach presented herein is appropriate throughout the product design life-cycle as an aid to faster product realization by evaluating the parochial manufacturability of a completed design. In particular, this approach will provide the design team with cost, time and quality predictions, based on available equipment, that can be used to guide the design process. It also provides the manufacturing team with an approach to evaluating producibility and generating a production plan for a product model using available equipment in terms of cost, time and quality.     

Setting quality targets for coming releases with QUPER: an industrial case study

Quality requirements play a critical role in driving architectural design and are an important issue in software development. Therefore, quality requirements need to be considered, specified, and quantified early during system analysis and not later in the development phase in an ad-hoc fashion. This paper presents the quality performance model that estimates quality targets in relation to market expectations as a basis for the architecting of quality requirements. The purpose of the model is to provide concepts for qualitative reasoning of quality levels in the decision-making of setting actual targets of quality requirements for coming releases of the product. The quality performance model is evaluated at one case company, using a market-driven development approach, in the electronic payment-processing domain. The results show that the model is useful for supporting early decision-making in, e.g., release planning of quality requirements.     

Quality metrics in high-dimensional data visualization: an overview and systematization

In this paper, we present a systematization of techniques that use quality metrics to help in the visual exploration of meaningful patterns in high-dimensional data. In a number of recent papers, different quality metrics are proposed to automate the demanding search through large spaces of alternative visualizations (e.g., alternative projections or ordering), allowing the user to concentrate on the most promising visualizations suggested by the quality metrics. Over the last decade, this approach has witnessed a remarkable development but few reflections exist on how these methods are related to each other and how the approach can be developed further. For this purpose, we provide an overview of approaches that use quality metrics in high-dimensional data visualization and propose a systematization based on a thorough literature review. We carefully analyze the papers and derive a set of factors for discriminating the quality metrics, visualization techniques, and the process itself. The process is described through a reworked version of the well-known information visualization pipeline. We demonstrate the usefulness of our model by applying it to several existing approaches that use quality metrics, and we provide reflections on implications of our model for future research.     

An organizational maturity model of software product line engineering

Software product line engineering is an inter-disciplinary concept. It spans the dimensions of business, architecture, process, and the organization. Some of the potential benefits of this approach include cost reduction, improvements in product quality and a decrease in product development time. The increasing popularity of software product line engineering in the software industry necessitates a process maturity evaluation methodology. Accordingly, this paper presents an organizational maturity model of software product line engineering for evaluating the maturity of organizational dimension. The model assumes that organizational theories, behavior, and management play a critical role in the institutionalization of software product line engineering within an organization. Assessment questionnaires and a rating methodology comprise the framework of this model. The objective and design of the questionnaires are to collect information about the software product line engineering process from the dual perspectives of organizational behavior and management. Furthermore, we conducted two case studies and reported the assessment results using the organizational maturity model presented in this paper.     

Applying the IPA and DEMATEL models to improve the order-winner criteria: A case study of Taiwan’s network communication equipment manufacturing industry

The purpose of this study is to use the gap-analysis method to calculate the performance of quality characteristics and apply the multiple regression analysis method to establish the overall level of satisfaction and implicit importance of quality characteristics. In addition we will use the decision making trial and evaluation laboratory (DEMATEL) method to analyze the cause-effect relationship and level of influence among different quality characteristics in order to make revisions to the traditional IPA model and find the core problems that are involved with winning orders. The methodology that we propose for this research not only makes revisions to the IPA model’s method of directly using explicit information from customer responses, we also solved the influence of the cause-effect relationships of quality characteristics. For our research we analyzed the case of a company from Taiwan’s network communication equipment manufacturing industry in order to make our corrections to the IPA model and gain the benefits of using the DEMATEL model. The findings of our research show that with the corrections to the IPA and the methodology of DEMATEL we can find and correct the core problems of the company that was analyzed, improve quality control and therefore improve the company’s ability to win and be compatible for orders.     

Assessing information quality of e-learning systems: a web mining approach

E-learning systems provide a promising solution as an information exchanging channel. Improved technologies could mean faster and easier access to information but do not necessarily ensure the quality of this information; for this reason it is essential to develop valid and reliable methods of quality measurement and carry out careful information quality evaluations. This paper proposes an assessment model for information quality in e-learning systems based on the quality framework we proposed previously: the proposed framework consists of 14 quality dimensions grouped in three quality factors: intrinsic, contextual representation and accessibility. We use the relative importance as a parameter in a linear equation for the measurement scheme. Formerly, we implemented a goal-question-metrics approach to develop a set of quality metrics for the identified quality attributes within the proposed framework. In this paper, the proposed metrics were computed to produce a numerical rating indicating the overall information quality published in a particular e-learning system. The data collection and evaluation processes were automated using a web data extraction technique and results on a case study are discussed. This assessment model could be useful to e-learning systems designers, providers and users as it provides a comprehensive indication of the quality of information in such systems.     

A multi source product reputation model

Product reputation model is very important for customers and manufacturers in order to make decisions. Several product reputation models are proposed in literature which use customer reviews in order to compute reputation values. However, the aggregation methods used are not able to estimate a good reputation value when some ratings are false. Some of these aggregation methods are not robust to false and biased ratings because a single false rating is enough to change the result. Others are robust to false ratings but not able to reflect the recent opinions about product quickly. In addition, most of the product reputation models are based on single source, therefore suffer from availability and vulnerability issues. In this paper, we propose a multi-source product reputation model where robust and strategy proof aggregation methods are used. A source credibility measure method is proposed, which uses four factors to determine malicious sources. Furthermore, a suitable decay principle for product reputation is also introduced in order to reflect the newest opinions quickly. The results show that proposed model is robust, strategy proof and able to provide a good estimation even if some ratings are false.     

How Much Software Quality Investment Is Enough: A Value-Based Approach

A classical problem facing many software projects is determining when to stop testing and release the product for use. Risk analysis helps address this issue by balancing the risk exposure of doing too little with the risk exposure of doing too much. A quantitative approach based on the COCOMO II cost-estimation model and the COQUALMO quality-estimation model helps answer the question, "How much software quality investment is enough?" The authors use the models and some representative empirical data to assess the relative payoff of value-based testing as compared to value-neutral testing. They include examples of the approach's use under differing value profiles.     

Dynamic simulation of product process

During 90’s Nokia utilized Concurrent Engineering (CE) process in mobile phone business successfully. Strong growing of the company, more complex technologies, maturing markets and changes in competition has increased the need to develop the product process of the company to keep its position as an agile, innovative and productive product developer. Dynamic simulation approach has been one of the activities among other product process re-engineering efforts in the company.This paper describes the approach and “Product Process Decision Simulation” (PPDS) solution as the first implemented application of the approach. A dynamic model of product development has been created and applied to manage product process complex dynamic behavior on system level in order to reduce product development cycle times, slippages and costs as well as improve perceived product quality. The key contribution of the simulation solution is to provoke facilitated discussion in order to gain shared understanding of interdependencies and dynamic causes and effects in product process.The implementation and frequent simulation workshops have started in June 2006 and about 500 R&D people have already participated.     

Model-based verification of quantitative non-functional properties for software product lines

Evaluating quality attributes of a design model in the early stages of development can significantly reduce the cost and risks of developing a low quality product. To make this possible, software designers should be able to predict quality attributes by reasoning on a model of the system under development. Although there exists a variety of quality-driven analysis techniques for software systems, only a few work address software product lines. This paper describes how probabilistic model checking techniques and tools can be used to verify non-functional properties of different configurations of a software product line. We propose a model-based approach that enables software engineers to assess their design solutions for software product lines in the early stages of development. Furthermore, we discuss how the analysis time can be surprisingly reduced by applying parametric model checking instead of classic model checking. The results show that the parametric approach is able to substantially alleviate the verification time and effort required to analyze non-functional properties of software product lines.