Muhammad Imran Babar

PHandler: An expert system for a scalable software requirements prioritization process

Software requirements engineering is a critical discipline in the software development life cycle. The major problem in software development is the selection and prioritization of the requirements in order to develop a system of high quality. This research analyzes the issues associated with existing software requirement prioritization techniques. One of the major issues in software requirement prioritization is that the existing techniques handle only toy projects or software projects with very few requirements. The current techniques are not suitable for the prioritization of a large number of requirements in projects where requirements may grow to the hundreds or even thousands. The research paper proposes an expert system, called the Priority Handler (PHandler), for requirement prioritization. PHandler is based on the value-based intelligent requirement prioritization technique, neural network and analytical hierarchical process in order to make the requirement prioritization process scalable. The back-propagation neural network is used to predict the value of a requirement in order to reduce the extent of expert biases and make the PHandler efficient. Moreover, the analytical hierarchy process is applied on prioritized groups of requirements in order to enhance the scalability of the requirement prioritization process.

StakeMeter: Value-Based Stakeholder Identification and Quantification Framework for Value-Based Software Systems

Value-based requirements engineering plays a vital role in the development of value-based software (VBS). Stakeholders are the key players in the requirements engineering process, and the selection of critical stakeholders for the VBS systems is highly desirable. Based on the stakeholder requirements, the innovative or value-based idea is realized. The quality of the VBS system is associated with the concrete set of valuable requirements, and the valuable requirements can only be obtained if all the relevant valuable stakeholders participate in the requirements elicitation phase. The existing value-based approaches focus on the design of the VBS systems. However, the focus on the valuable stakeholders and requirements is inadequate. The current stakeholder identification and quantification (SIQ) approaches are neither state-of-the-art nor systematic for the VBS systems. The existing approaches are time-consuming, complex and inconsistent which makes the initiation process difficult. Moreover, the main motivation of this research is that the existing SIQ approaches do not provide the low level implementation details for SIQ initiation and stakeholder metrics for quantification. Hence, keeping in view the existing SIQ problems, this research contributes in the form of a new SIQ framework called ‘StakeMeter’. The StakeMeter framework is verified and validated through case studies. The proposed framework provides low-level implementation guidelines, attributes, metrics, quantification criteria and application procedure as compared to the other methods. The proposed framework solves the issues of stakeholder quantification or prioritization, higher time consumption, complexity, and process initiation. The framework helps in the selection of highly critical stakeholders for the VBS systems with less judgmental error.

A Bi-metric and Fuzzy c-means based intelligent stakeholder quantification system for value-based software

Requirements engineering (RE) deals with the software requirements elicitation, validation and verification processes and implementation of elicited requirements. The RE process, for value-based software (VBS) development, is one of the highly complex and non-linear processes which mainly depends on the key stakeholders. VBS systems are extremely different from traditional systems due to their association with financial streams. There is a need of value-based RE practices. Stakeholders’ analysis plays a vital role in the selection of critical stakeholders for RE phase in VBS development. Different stakeholders’ identification and quantification (SIQ) approaches are presented by researchers in order to identify and quantify the stakeholders. The existing approaches are not uniform in terms of process activities and different stakeholders’ attributes. Nonuniformity results in higher time consumption and higher complexity. The existing SIQ approaches are not suitable for current value-based RE practices. Hence, this research presents an intelligent decision support system for the VBS SIQP using stakeholder metrics and fuzzy logic. The data is finally divided into three clusters in order to select the highly prioritized stakeholders for VBS systems.

Technique for early reliability prediction of software components using behaviour models

Behaviour models are the most commonly used input for predicting the reliability of a software system at the early design stage. A component behaviour model reveals the structure and behaviour of the component during the execution of system-level functionalities. There are various challenges related to component reliability prediction at the early design stage based on behaviour models. For example, most of the current reliability techniques do not provide fine-grained sequential behaviour models of individual components and fail to consider the loop entry and exit points in the reliability computation. Moreover, some of the current techniques do not tackle the problem of operational data unavailability and the lack of analysis results that can be valuable for software architects at the early design stage. This paper proposes a reliability prediction technique that, pragmatically, synthesizes system behaviour in the form of a state machine, given a set of scenarios and corresponding constraints as input. The state machine is utilized as a base for generating the component-relevant operational data. The state machine is also used as a source for identifying the nodes and edges of a component probabilistic dependency graph (CPDG). Based on the CPDG, a stack-based algorithm is used to compute the reliability. The proposed technique is evaluated by a comparison with existing techniques and the application of sensitivity analysis to a robotic wheelchair system as a case study. The results indicate that the proposed technique is more relevant at the early design stage compared to existing works, and can provide a more realistic and meaningful prediction.

Multi-aspects based requirements priortization technique for value-based software developments

In requirements engineering (RE), different activities are carried on to add up business values to the software products. In value-base software (VBS), financial impacts on business are measured, and this phenomenon makes VBS different than other traditional software applications. In VBS systems, determination of valuable requirements is a crucial task and depends on multiple aspects or factors. Requirement prioritization is a part of RE and is considered as a crucial decision-making activity. Requirements prioritization is a process where requirements are arranged in an order to create a stakeholder priority list. Different requirements prioritization techniques are used by the experts in the industry to partially support the prioritization process for VBS development. Business and technical aspects play a vital role to make prioritization process effective. In existing requirements prioritization techniques, technical aspects are not applied well, and their consideration is partial only. Moreover, the business aspects are ignored which are highly vital for VBS development. There is a need to introduce multi-aspects requirements prioritization technique to support the selection of candidate requirements for VBS development. Hence, this paper focuses on a new requirements prioritization technique for VBS.

A Comparative Analysis of Quality Assurance of Mobile Applications using Automated Testing Tools

Use of mobile applications are trending these days due to adoption of handheld mobile devices with operating systems such as Android, iOS and Windows. Delivering quality mobile apps is as important as in any other web or desktop application. Simplification and ease of quality assurance or evaluation in mobile devices is achieved by using automated testing tools. These tools have been evaluated for their features, platforms, code coverage, and efficiency. However, they have not been evaluated and compared to each other for different quality attributes they can enhance in the apps under test. This research study aims to evaluate different testing tools focusing on identifying quality factors they aid to achieve in the apps under test. Furthermore, it aims to measure overall trends of essential quality factors achieved using automated testing tools. The findings of this study are beneficial to the practitioners and researchers. The practitioners need to look up for specific tools which aid them to assure the desired quality factors in the apps under test. The researchers may base their studies on the findings of this study to propose solutions or revise existing tools in order to achieve maximum number of critical quality attributes in the app under test. This study revealed that the trend of automated testing is high on usability, correctness and robustness. Moreover, the trend is average on testability and performance. However, for assurance of extensibility, maintainability, scalability, and platform compatibility, only a few tools are available.

Impact of Story Point Estimation on Product using Metrics in Scrum Development Process

Agile Software Development techniques are worldwide accepted, regardless of the definition of agile we all must agree with the fact that agile is maturing day by day, suppliers of software systems are moving away from traditional waterfall techniques and other development practices in favor of agile methods. There are numerous types of methodologies, domains/ methods in agile for which are to be selected according to the current situation and demand of the current project. As a case scenario in the following research will discuss scrum as a development technique in which we will focus on the effort estimation(s) and their effects by discussing distinct metrics. Mainly estimation refers directly to cost, time and complexity during the life cycle of project. Metrics will help the teams to better understand the development progress and building releasing (releases) of software easier in a fluent and robust way. The following paper thus identifies aspects mainly ignored by the development team(s) during estimation.

Correction: Technique for Early Reliability Prediction of Software Components Using Behaviour Models.

[This corrects the article DOI: 10.1371/journal.pone.0163346.].