DEVELOPMENT STRATEGY AND MANAGEMENT OF AI-BASED VULNERABILITY DETECTION APPLICATIONS IN ENTERPRISE SOFTWARE ENVIRONMENT

2023 | European Conference On Information Systems | Citations: 0

Authors: Behfar, Stefan

Abstract: Industries are now struggling with high level of security-risk vulnerabilities ... Expand

Abstract: Industries are now struggling with high level of security-risk vulnerabilities in their software environment which mainly originate from open-source dependencies. Industries' percentage of open source in codebases is about 54% whereas ones with high security risks is about 30% (Synopsys 2018).While there are existing solutions for application security analysis, these typically only detect a limited subset of possible errors based on pre-defined rules. With the availability of open-source vulnerability resources, it is now possible to use data-driven techniques to discover vulnerabilities. Although there are a few AI-based solutions available, but there are some associated challenges: 1) use of artificial intelligence for application security (AppSec) towards vulnerability detection has been very limited and definitely not industry oriented, 2) the strategy to develop, use and manage such AppSec products in enterprises have not been investigated; therefore cybersecurity firms do not use even limited existing solutions. In this study, we aim to address these challenges with some strategies to develop such AppSec, their use management and economic values in enterprise environment. Collapse

Topics: artificial intelligence new product development source code open source software metric

Methods: machine learning artificial neural network

The Effects of Programming Style on Open Source Collaboration

2017 | International Conference on Information Systems | Citations: 0

Authors: Wang, Zhiyi; Hahn, Jungpil

Abstract: Open source software (OSS) development has recently garnered much attention from ... Expand

Abstract: Open source software (OSS) development has recently garnered much attention from both industry practitioners and academic researchers. However, existing research on OSS usually focus on the role of behavioral factors in affecting collaboration outcomes but has neglected to critically consider the nature of software itself. In this study, we seek to integrate collaboration factors and software factors in OSS collaboration. Specifically, we investigate the role of programming style in open source collaboration, where strict guidelines for coding are usually not enforced. We develop three implications of programming style on contributor, development and diffusion from a diversity perspective. Additionally, two team level factors that moderate the negative effects of programming style are discussed. A comprehensive measure for quantifying programming style is proposed and verified in our preliminary investigation. Our study is expected to contribute to the literature on OSS development, software engineering and diversity in distributed work groups. Collapse

Topics: source code open source systems development JavaScript programming language

Methods: statistical hypothesis test econometric modeling data modeling linear regression analysis econometric model

Ranking software components for reuse based on non-functional properties

2016 | Information Systems Frontiers | Citations: 0

Authors: Kessel, Marcus; Atkinson, Colin

Abstract: One of the biggest obstacles to software reuse is the cost involved in evaluatin ... Expand

Abstract: One of the biggest obstacles to software reuse is the cost involved in evaluating the suitability of possible reusable components. In recent years, code search engines have made significant progress in establishing the semantic suitability of components for new usage scenarios, but the problem of ranking components according to their non-functional suitability has largely been neglected. The main difficulty is that a component’s non-functional suitability for a specific reuse scenario is usually influenced by multiple, “soft” criteria, but the relative weighting of metrics for these criteria is rarely known quantitatively. What is required, therefore, is an effective and reliable strategy for ranking software components based on their non-functional properties without requiring users to provide quantitative weighting information. In this paper we present a novel approach for achieving this based on the non-dominated sorting of components driven by a specification of the relative importance of non-functional properties as a partial ordering. After describing the ranking algorithm and its implementation in a component search engine, we provide an explorative study of its properties on a sample set of components harvested from Maven Central. Collapse

Topics: Java search engine software metric source code systems development

Methods: computational algorithm design artifact optimization model literature study descriptive statistic

Predicting Stability of Open-Source Software Systems Using Combination of Bayesian Classifiers

2014 | ACM Transactions on Management Information Systems | Citations: 0

Authors: Bouktif, Salah; Sahraoui, Houari; Ahmed, Faheem

Abstract: The use of free and Open-Source Software (OSS) systems is gaining momentum. Orga ... Expand

Abstract: The use of free and Open-Source Software (OSS) systems is gaining momentum. Organizations are also now adopting OSS, despite some reservations, particularly about the quality issues. Stability of software is one of the main features in software quality management that needs to be understood and accurately predicted. It deals with the impact resulting from software changes and argues that stable components lead to a cost-effective software evolution. Changes are most common phenomena present in OSS in comparison to proprietary software. This makes OSS system evolution a rich context to study and predict stability. Our objective in this work is to build stability prediction models that are not only accurate but also interpretable, that is, able to explain the link between the architectural aspects of a software component and its stability behavior in the context of OSS. Therefore, we propose a new approach based on classifiers combination capable of preserving prediction interpretability. Our approach is classifier-structure dependent. Therefore, we propose a particular solution for combining Bayesian classifiers in order to derive a more accurate composite classifier that preserves interpretability. This solution is implemented using a genetic algorithm and applied in the context of an OSS large-scale system, namely the standard Java API. The empirical results show that our approach outperforms state-of-the-art approaches from both machine learning and software engineering. Collapse

Topics: Java application programming interface systems development software metric packaged software

Methods: computational algorithm Student's t-test parametric test machine learning descriptive statistic

Theories: theory of case-based reasoning

A comparative study of iterative and non-iterative feature selection techniques for software defect prediction

2014 | Information Systems Frontiers | Citations: 0

Authors: Khoshgoftaar, Taghi M.; Gao, Kehan; Napolitano, Amri; Wald, Randall

Abstract: Two important problems which can affect the performance of classification models ... Expand

Abstract: Two important problems which can affect the performance of classification models are high-dimensionality (an overabundance of independent features in the dataset) and imbalanced data (a skewed class distribution which creates at least one class with many fewer instances than other classes). To resolve these problems concurrently, we propose an iterative feature selection approach, which repeated applies data sampling (in order to address class imbalance) followed by feature selection (in order to address high-dimensionality), and finally we perform an aggregation step which combines the ranked feature lists from the separate iterations of sampling. This approach is designed to find a ranked feature list which is particularly effective on the more balanced dataset resulting from sampling while minimizing the risk of losing data through the sampling step and missing important features. To demonstrate this technique, we employ 18 different feature selection algorithms and Random Undersampling with two post-sampling class distributions. We also investigate the use of sampling and feature selection without the iterative step (e.g., using the ranked list from a single iteration, rather than combining the lists from multiple iterations), and compare these results from the version which uses iteration. Our study is carried out using three groups of datasets with different levels of class balance, all of which were collected from a real-world software system. All of our experiments use four different learners and one feature subset size. We find that our proposed iterative feature selection approach outperforms the non-iterative approach. Collapse

Topics: systems development system quality software metric IT project system development method

Methods: machine learning computational algorithm case study support vector machine parametric test

The adoption of software measures: A technology acceptance model (TAM) perspective

2014 | Information & Management | Citations: 4

Authors: Wallace, Linda G.; Sheetz, Steven D.

Abstract: The use of software measures for project management and software process improve ... Expand

Abstract: The use of software measures for project management and software process improvement has been encouraged for many years. However, the low level of acceptance and use of software measures in practice has been a constant concern. In this paper we propose and test a model which explains and predicts the use of software measures. The model is based on the technology acceptance model (TAM) and operationalizes the perceived usefulness construct according to the “desirable properties of software measures.” Our research provides guidance for software engineers in selecting among different software measures and for software metrics coordinators who are planning measurement programs. Collapse

Topics: perceived usefulness perceived ease of use ease of use electronic mail technology adoption

Methods: survey structural equation modeling data transformation SEM tool survey design

Theories: technology acceptance model

All Are Not Equal: An Examination of the Economic Returns to Different Forms of Participation in Open Source Software Communities

2013 | Information Systems Research | Citations: 49

Authors: Hann, Il-Horn; Roberts, Jeffrey A.; Slaughter, Sandra A.

Abstract: Open source software (OSS) communities live and die with the continuous contribu ... Expand

Abstract: Open source software (OSS) communities live and die with the continuous contributions of programmers who often participate without direct remuneration. An intriguing question is whether such sustained participation in OSS projects yields economic benefits to the participants. Moreover, as participants engage in OSS projects, they take on different roles and activities in the community. This raises additional questions of whether different forms of participation in OSS communities are associated with different economic rewards and, if so, in which contexts. In this paper, we draw upon theories of signaling and job matching to hypothesize that participants who possess “proof” of their skills in OSS projects are financially rewarded for their activities in the labor market. More specifically, we distinguish between participation in OSS communities that is associated with a signaling value for unobserved productivity characteristics and an additional value that accrues to participants whose OSS roles and activities match those in their paid employment. Following a cohort of OSS programmers over a six-year period, we empirically examine the wages and OSS performance of participants in three of the foremost OSS projects operating within the Apache Software Foundation. Controlling for individual characteristics and other wage-related factors, our findings reveal that credentials earned through a merit-based ranking system are associated with as much as an 18% increase in wages. Moreover, we find that participants who have OSS project management responsibilities receive additional financial rewards if their professional job is in IT management. These findings suggest that rank within an OSS meritocracy is a credible and precise signal of participants' productive capacity and that participants' roles and activities in an OSS community have additional financial value when aligned with their paid employment. Collapse

Topics: IS management IT career IT manager source code IT job

Methods: survey longitudinal research propensity score method cross sectional research theory development

Theories: signaling theory

HOW MICROBLOG FOLLOWER NETWORKS AFFECT OPEN SOURCE SOFTWARE PROJECT SUCCESS

2010 | International Conference on Information Systems | Citations: 0

Authors: Yang, Xuan; Hu, Daning; Davison, Robert M

Abstract: Successful open source software (OSS) projects require efficient communication m ... Expand

Abstract: Successful open source software (OSS) projects require efficient communication means and a steady supply of voluntary developers. Microblogging, as well as the follower network it generates, is becoming increasingly popular as an emerging Web 2.0 communication technology in many online OSS communities. However, little is known about how microblogging follower networks affect OSS project success. Based on theories drawn from the social network domain, OSS and virtual team research,we hypothesized two follower network mechanisms – preferential attachment and structural holes – which may significantly affect OSS project success, by improving knowledge sharing and attracting more skillful developers. We plan to empirically study a microblog follower network in a large online OSS community, aiming to examine the impacts of the two hypothesized follower network mechanisms on OSS project success. Our potential findings may provide insights for OSS project managers to better manage microblog communications and thereby achieve project success. Collapse

Topics: microblog team productivity social network application programming interface open source

Methods: longitudinal data analysis longitudinal research regression analysis method qualitative content analysis

Theories: social network theory

Mejorando la Administración de los Procesos Mediante el Uso de Métricas de Software: Un caso de Estudio

2006 | Americas Conference on Information Systems | Citations: 0

Authors: Pineda, Hilda; Jenkins, Marcelo

Abstract: This paper describes a case study about the experience in designing and implemen ... Expand

Abstract: This paper describes a case study about the experience in designing and implementing a software metrics program to measure and improve the process in a systems development organization. We explain how the metrics system was designed and implemented, including the use of a software tool we developed to collect and analyze the metrics results at all levels of the organization, and summarize the benefits obtained from their use from the process improvement standpoint. The issues discussed in this paper may interest organizations that want to improve their processes through the systematic use of quality and productivity metrics for software development and maintenance. Collapse

Topics: systems development business process improvement software metric

Methods: case study

The Effectiveness of Knowledge Transfer Portfolios in Software Process Improvement: A Field Study

2006 | Information Systems Research | Citations: 22

Authors: Slaughter, Sandra A.; Kirsch, Laurie J.

Abstract: Because of challenges often experienced when deploying software, many firms have ... Expand

Abstract: Because of challenges often experienced when deploying software, many firms have embarked on software process improvement (SPI) initiatives. Critical to the success of these initiatives is the transfer of knowledge across individuals who occupy a range of roles in various organizational units involved in software production. Prior research suggests that a portfolio of different mechanisms, employed frequently, can be required for effective knowledge transfer. However, little research exists that examines under what situations differing portfolios of mechanisms are selected. Further, it is not clear how effective different portfolio designs are. In this study, we conceptualize knowledge transfer portfolios in terms of their composition (the types of mechanisms used) and their intensity (the frequency with which the mechanisms are utilized). We hypothesize the influence of organizational design decisions on the composition and intensity of knowledge transfer portfolios for SPI. We then posit how the composition and intensity of knowledge transfer portfolios affect performance improvement. Our findings indicate that a more intense portfolio of knowledge transfer mechanisms is used when the source and recipient are proximate, when they are in a hierarchical relationship, or when they work in different units. Further, a source and recipient select direction-based portfolios when they are farther apart, in a hierarchical relationship, or work in different units. In terms of performance, our results reveal that the fit between the composition and intensity of the knowledge transfer portfolio influences the recipient's performance improvement. At lower levels of intensity direction-based portfolios are more effective, while at higher levels of intensity routine-based portfolios yield the highest performance improvement. We discuss the implications of our findings for researchers and for managers who want to promote knowledge transfer to improve software processes in their organizations. Collapse

Topics: knowledge sharing software process improvement Chief Information Officer business process improvement systems development

Methods: qualitative interview descriptive statistic sensitivity analysis archival research generalized least square