Software Product Management Research Articles

Managing and Analysing Software Product Line Requirements

Modelling software product line (SPL) features plays a crucial role to a successful development of SPL. Feature diagram is one of the widely used notations to model SPL variants. However, there is a lack of precisely defined formal notations for representing and verifying such models. This paper presents an approach that we adopt to model SPL variants by using UML and subsequently verify them by using first-order logic. UML provides an overall modelling view of the system. First-order logic provides a precise and rigorous interpretation of the feature diagrams. We model variants and their dependencies by using propositional connectives and build logical expressions. These expressions are then validated by the Alloy verification tool. The analysis and verification process is illustrated by using Computer Aided Dispatch (CAD) system.

Understanding users’ behavior with software operation data mining

Software usage concerns knowledge about how end-users use the software in the field, and how the software itself responds to their actions. In this paper, we present the Usage Mining Method to guide the analysis of data collected during software operation, in order to extract knowledge about how a software product is used by the end-users. Our method suggests three analysis tasks which employ data mining techniques for extracting usage knowledge from software operation data: users profiling, clickstream analysis and classification analysis. The Usage Mining Method was evaluated through a prototype that was executed in the case of Exact Online, the main online financial management application in the Netherlands. The evaluation confirmed the supportive role of the Usage Mining Method in software product management and development processes, as well as the applicability of the suggested data mining algorithms to carry out the usage analysis tasks.

Finding the tool that fits best: cloud based task management for electronic resources

PurposeThe article aims to examine how the University of Maryland, College Park, evaluated two specific task management software packages that could make the pre‐order workflow for electronic resources more transparent to library staff.Design/methodology/approachThe results from an electronic resources gap analysis done at the University of Maryland, College Park, were used as a basis to evaluate and select task management systems.FindingsTwo electronic resource management systems, CORAL and License Manager, were selected. They were evaluated in the areas of task, license and vendor information management.Originality/valueThis paper provides criteria that could be used to evaluate tools that support license management for electronic resources.

What are the roles of software product managers? An empirical investigation

Software product management covers both technical and business activities to management of products like roadmaps, strategic, tactical, and release planning. In practice, one product manager is seldom responsible for all these activities but several persons share the responsibilities. Therefore, it is important to understand the boundaries of product managers’ work in managing software products, as well as the impact a product manager has on the company business. The purpose of the study is to clarify what roles of software product managers exist and understand how these roles are interrelated with each other and the whole structure and business of an organization. The study is designed as an interpretative qualitative study using grounded theory as the research method. Based on the gathered data we developed a framework that reveals the role of a product manager in the organization and shows how this role can evolve by extending the level of responsibilities. Using the framework, we identified four stereotypical roles of product managers in the studied organizations: experts, strategists, leaders, and problem solvers. The presented framework shows that product managers’ roles are not limited to the conception of the “mini-CEO.” The results allow product managers and top management to collaborate effectively by assigning responsibilities and managing expectations by having a common tool for understanding the role of product managers in the organization.

Effects of social injustice on breast health-seeking behaviors of low-income women.

The study uses qualitative research to gain a better understanding of what occurs after low-income women receive an abnormal breast screening and the factors that influence their decisions and behavior. A heuristic model is presented for understanding this complexity. Qualitative research methods used to elicited social and cultural themes related to breast cancer screening follow-up. Individual telephone interviews were conducted with 16 women with confirmed breast anomaly. Low-income women screened through a national breast cancer early detection program. Grounded theory using selective coding was employed to elicit factors that influenced the understanding and follow-up of an abnormal breast screening result. Interviews were digitally recorded, transcribed, and uploaded into NVivo 8, a qualitative management and analysis software package. For women (16, or 72% of case management referrals) below 250% of the poverty level, the impact of social and economic inequities creates a psychosocial context underlined by structural and cultural barriers to treatment that forecasts the mechanism that generates differences in health outcomes. The absence of insurance due to underemployment and unemployment and inadequate public infrastructure intensified emotional stress impacting participants' health decisions. The findings that emerged offer explanations of how consistent patterns of social injustice impact treatment decisions in a high-risk vulnerable population that have implications for health promotion research and systems-level program improvement and development.

A new tabu search-based hyper-heuristic algorithm for solving construction leveling problems with limited resource availabilities

We present a tabu search-based hyper-heuristic algorithm for solving construction resource leveling problems, i.e. resource leveling under resource constraints with the prescribed maximum project duration to be equal or greater than the initial/minimum duration, as well as the related resource availability cost problem. The algorithm operates within a commercial project management software package by altering the priorities assigned to activities. The hyper-heuristic controls a set of low-level heuristics, which modify the priorities of selected activities by performing simple moves such as “replace” and “swap”. The most promising heuristics according to their efficiency are applied first, and a tabu list is used to prohibit heuristics with recently poor performance from being applied too soon. The application of the algorithm in three project cases showed that the proposed procedure is promising for handling resource optimization problems. ► Hyperheuristics recently introduced to treat construction project scheduling problems. ► THH is the first tabu hyperheuristic applied to construction scheduling problems. ► THH is a flexible procedure that easily can be applied to different problems. ► Application of the algorithm proved it as promising for treating leveling problems.

Application of modern educational technologies in the training for the management of accidents with chemical hazards

The article presents the application of modern educational technology in the training for the management of accidents with chemical hazards. It describes the 'HeSPRO' software package created to integrate the functions of evaluation and prediction of the effects of hazardous substances both in chemical accidents and during the use of highly toxic substances. The assessment of the software package application was carried out based on hypothetical models. The chemical hazard assessment was carried out through the analysis of the obtained results. It was concluded that the software package provides optimal conditions for effective evaluation and prediction of the situation in chemical accidents with hazardous materials.

Improving software product management: a knowledge management approach

The skills and practices of a product manager can be seen as part of the intellectual capital of a software vendor. From this perspective, it is surprising that knowledge regarding software product management is not yet widely available. This impedes many companies from effectively improving their SPM methods. To support knowledge dissemination, method assessment, and method improvement in this and other areas, we propose the online method engine. The solution combines knowledge management principles with incremental process improvement in order to allow software companies to obtain improvement guidance for their SPM methods, specific to their situation. The approach is designed to be domain-independent.

Project Management Software Utilization and Project Performance

The impacts of IT/IS on organizations gave rise to a great deal of interest from the researchers during the last decades. However, studies on the impacts of IT/IS on the performance of engineering projects are less numerous. Moreover, the impacts from IT/IS on engineering projects are rarely based on real data of projects. The objective of this study is to investigate, from real project data, the level of utilization of a project management software package, developed by an engineering construction firm recognized internationally, and its link with project performance. Results stemming from non-parametric tests and correlation analyses show that the level of use of the software, and some of its subsystems, appears to be linked to project performance.

Algorithms and parameters for improved accuracy in physics data libraries

Recent efforts for the improvement of the accuracy of physics data libraries used in particle transport are summarized. Results are reported about a large scale validation analysis of atomic parameters used by major Monte Carlo systems (Geant4, EGS, MCNP, Penelope etc.); their contribution to the accuracy of simulation observables is documented. The results of this study motivated the development of a new atomic data management software package, which optimizes the provision of state-of-the-art atomic parameters to physics models. The effect of atomic parameters on the simulation of radioactive decay is illustrated. Ideas and methods to deal with physics models applicable to different energy ranges in the production of data libraries, rather than at runtime, are discussed.

On the Design of a Knowledge Management System for Incremental Process Improvement for Software Product Management

Incremental software process improvement deals with the challenges of step-wise process improvement in a time where resources are scarce and many organizations are struggling with the challenges of effective management of software products. Effective knowledge sharing and incremental approaches are essential for improving the success rate of process improvement efforts. Recently, the authors’ have worked on the development of a knowledge management system, the Online Method Engine, that enables incremental, situational process improvement in the field of software product management. This has resulted in an initial system design. The authors describe the findings from seven exploratory case studies on incremental process improvement. The lessons learned during these case studies are used to refine the design of the Online Method Engine.

Informatics and Computing.

Informatics and Computing.

Lean Solutions to Software Product Management Problems

Although the discipline of software product management plays an important role in the development of successful products, each company adopts its practices in its own way. Regardless of variations, companies face common problems. This article identifies five problems that lean principles to software product management can help organizations avoid or solve.

About Our Authors

About Our Authors

EXP-PAC: Providing comparative analysis and storage of next generation gene expression data

Microarrays and more recently RNA sequencing has led to an increase in available gene expression data. How to manage and store this data is becoming a key issue. In response we have developed EXP-PAC, a web based software package for storage, management and analysis of gene expression and sequence data. Unique to this package is SQL based querying of gene expression data sets, distributed normalization of raw gene expression data and analysis of gene expression data across experiments and species. This package has been populated with lactation data in the international milk genomic consortium web portal (http://milkgenomics.org/). Source code is also available which can be hosted on a Windows, Linux or Mac APACHE server connected to a private or public network (http://mamsap.it.deakin.edu.au/~pcc/Release/EXP_PAC.html)

Enterprise Systems – A Research Agenda

This document reflects the current state-of the-art in Enterprise Systems and introduces a number of open issues and challenges from a research point of view. We present a reconstructed perspective on Enterprise Systems based on a research framework characterized by the three dimensions of multi-phase, multi-entity and multi-package with an underlying meta-theoretical approach following the notion of sociomateriality. Based on this framework, we articulate the research vision of the Enterprise Systems research group at the University of Mannheim. Furthermore, we provide an overview on our current research organized in the three research areas of “Software Product Development and Management”, “Individual Perspective on Enterprise Systems” and “Value-Augmented Enterprise Systems” investigating the entire Enterprise Systems phenomenon from different viewpoints of the introduced research framework.

Methods to Manage Information Sources for Software Product Managers in the Energy Market

The German energy market is facing several challenges due to changes in regulation, technical advancements as well as increasing energy costs and climate achievements like CO2 reduction. This results in changing requirements for companies in the energy market and thus business information systems, which support their core tasks and processes. Software product managers in energy and software developing companies in charge of driving the functional development of information systems have to deal with these challenges and need to develop new information systems or enhance existing ones. Conceptual models proved helpful to design and implement information systems within several industries. However, identification and management of models as well as impact analysis of model changes results difficult. This contribution describes methods to construct, use and maintain a domain specific reference model catalogue to support requirements analysis for software product manager in the German electricity and gas market.

Evaluating and Improving Risk Formulas for Allocating Limited Budgets to Expensive Risk‐Reduction Opportunities

Simple risk formulas, such as risk = probability × impact, or risk = exposure × probability × consequence, or risk = threat × vulnerability × consequence, are built into many commercial risk management software products deployed in public and private organizations. These formulas, which we call risk indices, together with risk matrices, "heat maps," and other displays based on them, are widely used in applications such as enterprise risk management (ERM), terrorism risk analysis, and occupational safety. But, how well do they serve to guide allocation of limited risk management resources? This article evaluates and compares different risk indices under simplifying conditions favorable to their use (statistically independent, uniformly distributed values of their components; and noninteracting risk-reduction opportunities). Compared to an optimal (nonindex) approach, simple indices produce inferior resource allocations that for a given cost may reduce risk by as little as 60% of what the optimal decisions would provide, at least in our simple simulations. This article suggests a better risk reduction per unit cost index that achieves 98-100% of the maximum possible risk reduction on these problems for all budget levels except the smallest, which allow very few risks to be addressed. Substantial gains in risk reduction achieved for resources spent can be obtained on our test problems by using this improved index instead of simpler ones that focus only on relative sizes of risk (or of components of risk) in informing risk management priorities and allocating limited risk management resources. This work suggests the need for risk management tools to explicitly consider costs in prioritization activities, particularly in situations where budget restrictions make careful allocation of resources essential for achieving close-to-maximum risk-reduction benefits.

Construction Resource Allocation and Leveling Using a Threshold Accepting–Based Hyperheuristic Algorithm

AbstractIn this study we propose a threshold accepting based hyperheuristic for solving in a single run both the resource-constrained project scheduling problem or resource allocation, and the resource leveling problem. Having their roots in the field of artificial intelligence, hyperheuristics operate in the “low-level” heuristics domain rather than in the solutions domain. The hyperheuristic has been implemented within a commercial project management software package. Low-level heuristics operate on the solution domain defined by the priority values that the software uses for resource allocation. A case example from the literature and computational experiments on randomly generated projects demonstrate that the hyperheuristic achieves good performance in a timely manner, improving the results provided by the software.

Design and implementation of an audit trail in compliance with US regulations

Audit trails have been used widely to ensure quality of study data and have been implemented in computerized clinical trials data systems. Increasingly, there is a need to audit access to study participant identifiable information to provide assurance that study participant privacy is protected and confidentiality is maintained. In the United States, several federal regulations specify how the audit trail function should be implemented. To describe the development and implementation of a comprehensive audit trail system that meets the regulatory requirements of assuring data quality and integrity and protecting participant privacy and that is also easy to implement and maintain. The audit trail system was designed and developed after we examined regulatory requirements, data access methods, prevailing application architecture, and good security practices. Our comprehensive audit trail system was developed and implemented at the database level using a commercially available database management software product. It captures both data access and data changes with the correct user identifier. Documentation of access is initiated automatically in response to either data retrieval or data change at the database level. Currently, our system has been implemented only on one commercial database management system. Although our audit trail algorithm does not allow for logging aggregate operations, aggregation does not reveal sensitive private participant information. Careful consideration must be given to data items selected for monitoring because selection of all data items using our system can dramatically increase the requirements for computer disk space. Evaluating the criticality and sensitivity of individual data items selected can control the storage requirements for clinical trial audit trail records. Our audit trail system is capable of logging data access and data change operations to satisfy regulatory requirements. Our approach is applicable to virtually any data that can be stored in a relational database.