Monday, September 11, 2017

IEEE July/August Issue, Blog, and SE Radio Summary

Associate Editor: Brittany Johnson (@drbrittjaydlf)

The July/August Issue of IEEE Software again provides articles that cover a range of software engineering-related topics. The themes in this issue include reliability and requirements engineering, technical debt, and agile development.

Special in this issue is a look at the history of IEEE Software in the article "Insights from the Past: The IEEE Software History Experiment" by Zeljko Obrenovic. By looking at the history website, this article proposes the practical value in using historical data. There is also discussion of the future of IEEE Software based on historical data.

The focus topic in this issue of IEEE Software was Reliability Engineering. This issue featured the following articles on reliability engineering:

One of the main concerns around reliability engineering is the growing ubiquity of software in safety critical systems. As pointed out by Diomidis Spinellis in "Software Reliability Redux", the more software is integrated into our daily lives the more we need adequate reliability engineering. Going more in depth on the topic, in "Requirements Engineering for Safety-Critical Systems: Overview and Challenges",  Martins and colleagues talk about some of the challenges that comes with engineering safety critical systems. In particular, they focus on dealing with safety requirements, discussing topics from reducing the gap between academia and industry and communicating requirements throughout the development process.

In "Safety Analysis of Safety-Critical Systems Using State-Space Models", Kumar and colleagues made one suggestion for dealing with safety analysis of safety critical systems; using state-space models for safety issue prognosis. They created an approach that takes UML state diagrams and maps them to state-space models, using Petri nets for dynamic behavioral analysis. They were able to validate their approach using a nuclear power plant's emergency core cooling system. Despite their findings, there are still strides that can be made to improve the state-of-the-art in regards to processes and tools in place for building and maintaining reliable safety critical systems.

IEEE Software Blog

The IEEE Software Blogs posts in July and August focused on vulnerabilities. Mehdi Mirakhorli wrote a blog post on tactical vulnerabilities, or vulnerabilities that result from incorrect implementation or deterioration of security tactics during coding and maintenance. Cor-Paul Bezemer and Zhen Ming (Jack) Jiang explored if and how developers use performance testing to identify vulnerabilities. They studied Java-based open source projects on GitHub and found that there may be missing tool support for effective performance testing. Maleknaz Nayebi and Federica Sarro used crowdsourcing in a case study of the Fort McMurray wildfire, along with their method called MAPFEAT, to determine useful mobile app features.

SE Radio

SE Radio welcomed two new hosts in July and August: Kishore Bhatia of BlockApps and Bryan Reinero of MongoDB.  For Kishore's first broadcast, he spoke with Kieren James-Lubin about security topics such as Blockchains, Crytocurrency, Bitcoins, and Distributed Ledger. For Bryan's first broadcast, he and Jason Hand discuss handling outages and responding to program failures. 
Other topics discussed on SE Radio in July and August include type driven development, rules engines, and P vs. NP.


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Monday, September 4, 2017

IEEE May/June Issue, Blog, and SE Radio Summary

Associate Editor: Brittany Johnson (@drbrittjaydlf)

 The May/June issue of IEEE Software provided a wide range articles on software-related issues; from energy-aware systems to deep learning, there's something for just about everyone. Although the focus of this issue was automotive software, there are features on various other software topics.

The focus topic in this issue of IEEE Software was Automotive Software. This issue featured the following articles on Automotive Software.

As suggested by the Editor, Diomidis Spinellis, in his article "How Abundance Changes Software Engineering", increase in software processing power has lead to changes in how we use computing technologies. This includes the relatively recent innovation of automotive software. In "Future Automotive Architecture and the Impact of IT Trends", Traub and colleagues discuss the opportunities that advances in IT and consumer-electronics afford the automotive industry. Much of the discussion focuses on the importance of seamless and scalable architecture for automotive software.

With the creation of things like Google's self driving car, and the potential for this to be a commercially available product, the importance of security in the software behind our vehicles is increasing. The authors of "Secure Automotive Software: The Next Steps" discuss this issue in depth, starting with the challenges faced by developers that work on automotive software.  Based on these challenges, the authors discuss some recommendations they have for improving the security of software used in the auto industry. Some of their recommendations include using static analysis for compile-time assurance and cryptography for runtime protection.


This issue also included articles on the feature topics of mobile app development, agile development, continuous deployment, and the business of software engineering  encompassed in the following articles:



IEEE Software Blog

The topics in the blog posts for May and June show a little more diversity than last month's...figuratively and literally. Anna Filippova of Carnegie Mellon contributed a blog post on how brainstorming can be used to support inclusiveness in diverse teams. Other topics discussed in these blog posts include cross-stack configuration errors, library adoption, and the effect of casual contributions on software quality.

SE Radio 

In this issue, SE Radio welcomed another new host, Matthew Farwell of Nexthink. In his debut, he spoke with Yakov Fain about Angular, including who should use it and why. Many of the episodes in this issue center around technologies and how developers are using them, including Elasticsearch, Docker, and LLVM.  SE Radio also deployed a listener survey to get feedback from their listeners -- don't forget to provide your feedback!

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Monday, July 24, 2017

Tactical Vulnerabilities in Chromium, PHP and Thunderbird

By:  Mehdi Mirakhorli (@MehdiMirakhorli), Associate Editor

 Software engineers face a constantly growing pressure to build secure software by design, where systems have to be designed from the ground up to be secure and resistant to attacks. To achieve this goal, security architects work with various stakeholders to identify security requirements and adopt appropriate architectural solutions to address these requirements. These architectural solutions are often based on security tactics. Security tactics as reusable solutions to satisfy security quality attributes regarding resisting attacks (e.g., tactic “Authenticate Actors”), detecting attacks (e.g., tactic “Detect Intrusion”), reacting to attacks (e.g., tactic “Revoke Access”), and recovering from attacks (e.g., tactic “Audit”). Despite the significant efforts that go into designing secure systems, security can slowly erode because of ongoing maintenance activities. Incorrect implementation of security tactics or the deterioration of security tactics during coding and maintenance activities can result in vulnerabilities in the security architecture of the system, thus compromising key security requirements. We refer to these vulnerabilities as tactical vulnerabilities.

The code snippet in Listing 1 from a J2EE web application shows an example of such tactical vulnerabilities which is the incorrect implementation of the “Manage User Sessions” tactic. The correct implementation of this tactic in a web application would allow the system to keep track of users that are currently authenticated (including permissions they hold). However, in the given code snippet, the application authenticates users with LoginContext.login() without first calling HttpSession.invalidate() to invalidate any existing session. This enables attackers to fixate (i.e., find or set) another user’s session identifier (e.g., by inducing a user to initiate a session using the session identifier provided by the attacker). Once the user authenticates him/herself with this forged session identifier, the attacker would be able to hijack or steal his/her authenticated session. Although architects have used the “Manage User Sessions” tactic in the architecture design of the web application, the developers have failed to implement it correctly, resulting in a tactical vulnerability that can be exploited for session fixation attacks.
Recent empirical studies of security vulnerabilities have neglected the architectural context, including design decisions such as tactics and patterns. They mostly focus on studying and understanding coding issues related to the management of data structures and variables (e.g., buffer overflow/over-read). 

Goal of This Study

Here, I’d like to report an in-depth case study of software vulnerabilities associated with architectural security tactics across three large-scale open-source systems (Chromium, PHP, and Thunderbird). In this blog post, I only present the results, the scientific process and systematic approach used to make the conclusions can be found in our research article here.

Common Tactical Vulnerabilities

Table I lists the root causes (i.e., vulnerability types) of tactical vulnerabilities in each of the three studied systems, the related architecture tactics, as well as the total number of CVEs caused by the given vulnerability type.


Key findings

While Chromium, PHP, and Thunderbird have adopted a wide range of architectural tactics to secure the systems by design, a remarkable number of vulnerabilities discovered in these systems are due to incorrect implementations of these tactics. 

  • While Chromium, PHP, and Thunderbird have adopted a wide range of architectural tactics to secure the systems by design, a remarkable number of vulnerabilities discovered in these systems are due to incorrect implementations of these tactics
  • Improper Input Validation (CWE-20) and Improper 
Access Control (CWE-284) are the most occurring root causes for security vulnerabilities in Chromium, PHP, and Thunderbird. 

  • Vulnerabilities in the three studied systems are mostly related to tactics “Validate Inputs” and “Authorize Actors” for resisting attacks. 

  • Security of studied projects was compromised by reusing or importing vulnerable versions of third-party libraries. In the case of Chromium, such vulnerabilities occurred 106 times, while in Thunderbird and PHP, 7 and 8 times, respectively.
  • Tactical and non-tactical vulnerabilities have a similar distribution over time and releases, even though the absolute numbers of tactical and non-tactical vulnerabilities differ.
  • When fixing tactical vulnerabilities, there is no statistically higher or lower code churn compared to fixing non-tactical vulnerabilities.
  • When fixing tactical vulnerabilities, the number of affected files is not statistically significantly higher or lower compared to fixing non-tactical vulnerabilities.

Read more



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Monday, July 17, 2017

Performance testing in Java-based open source projects

by Cor-Paul Bezemer (@corpaul), Queen's University, Canada
Associate Editor: Zhen Ming (Jack) Jiang, York University, Canada
From a functional perspective, the quality of open source software (OSS) is on par with comparable closed-source software [1]. However, in terms of nonfunctional attributes, such as reliability, scalability, or performance, the quality is less well-understood. For example, Heger et al. [2] stated that performance bugs in OSS go undiscovered for a longer time than functional bugs, and fixing them takes longer.

 As many OSS libraries (such as apache/log4j) are used almost ubiquitously across a large span of other OSS or industrial applications, a performance bug in such a library can lead to widespread slowdowns. Hence, it is of utmost importance that the performance of OSS is well-tested.

 We studied 111 Java-based open source projects from GitHub to explore to what extent and how OSS developers conduct performance tests. First, we searched for projects that included at least one of the keywords 'bench' or 'perf' in the 'src/test' directory. Second, we manually identified the performance and functional tests inside that project. Third, we identified performance-sensitive projects, which mentioned in the description of their GitHub repository that they are the 'fastest', 'most efficient', etc. For a more thorough description of our data collection process, see our ICPE 2017 paper [3]. In the remainder of this blog post, the most significant findings of our study are highlighted.

Finding # 1 - Performance tests are maintained by a single developer or a small group of developers. 
In 50% of the projects, all performance test developers are one or two core developers of the project. In addition, only 44% of the test developers worked on the performance tests as well.

 Finding # 2 - Compared to the functional tests, performance tests are small in most projects. 
The median SLOC (source lines of code) in performance tests in the studied projects was 246, while the median SLOC of functional tests was 3980. Interestingly, performance-sensitive projects do not seem to have more or larger performance tests than non-performance-sensitive projects.

Finding # 3 - There is no standard for the organization of performance tests. 
In 52% of the projects, the performance tests are scattered throughout the functional test suite. In 9% of the projects, code comments are used to communicate how a performance test should be executed. For example, the RangeCheckMicroBenchmark.java file from the nbronson/snaptree project contains the following comment:
/*
* This is not a regression test, but a micro-benchmark.
*
* I have run this as follows:
*
* repeat 5 for f in -client -server;
* do mergeBench dolphin . jr -dsa\
*       -da f RangeCheckMicroBenchmark.java;
* done
*/
public class RangeCheckMicroBenchmark {
...
}

 In four projects, we even observed that code comments were used to communicate the results of a previous performance test run.

Finding # 4 - Most projects have performance smoke tests. 
We identified the following five types of performance tests in the studied projects:
  1. Performance smoke tests: These tests (50% of the projects) typically measure the end-to-end execution time of important functionality of the project.
  2. Microbenchmarks: 32% of the projects use microbenchmarks, which can be considered performance unit tests. Stefan et al. [4] studied microbenchmarks in depth in their ICPE 2017 paper.
  3. One-shot performance tests: These tests (15% of the projects) were meant to be executed once, e.g., to test the fix for a performance bug.
  4. Performance assertions: 5% of the projects try to integrate performance tests in the unit-testing framework, which results in performance assertions. For example, the TransformerTest.java file from the anthonyu/Kept-Collections project asserts that one bytecode serialization method is at least four times as fast as the alternative.
  5. Implicit performance tests: 5% of the projects do not have performance tests, but simply yield a performance metric (e.g., the execution time of the unit test suite). 
The different types of tests show that there is a need for performance tests at different levels, ranging from low-level microbenchmarks to higher-level smoke tests.

Finding # 5 - Dedicated performance test frameworks are rarely used. 
Only 16% of the studied projects used a dedicated performance test framework, such as JMH or Google Caliper. Most projects use a unit test framework to conduct their performance tests. One possible explanation is that developers are trying hard to integrate their performance tests into the continuous integration processes. 

The main takeaway of our study

Our observations imply that developers are currently missing a “killer app” for performance testing, which would likely standardize how performance tests are conducted, in the same way as JUnit standardized unit testing for Java. An ubiquitous performance testing tool will need to support performance tests on different levels of abstraction (smoke tests versus detailed microbenchmarking), provide strong integration into existing build and CI tools, and support both, extensive testing with rigorous methods as well as quick-and-dirty tests that pair reasonable expressiveness with being fast to write and maintain even by developers who are not experts in software performance engineering.

References

[1] M. Aberdour. Achieving quality in open-source software. IEEE Software. 2007.
[2] C. Heger, J. Happe, and R. Farahbod. Automated Root Cause Isolation of Performance Regressions During Software Development. In Proceedings of the 4th ACM/SPEC International Conference on Performance Engineering (ICPE). 2013.
[3] P. Leitner and C.-P. Bezemer. An exploratory study of the state of practice of performance testing in Java-based open source projects. In Proceedings of the 8th ACM/SPEC on International Conference on Performance Engineering (ICPE). 2017. 
[4] P. Stefan, V. Horky, L. Bulej, and P. Tuma. Unit testing performance in Java projects: Are we there yet? In Proceedings of the 8th ACM/SPEC on International Conference on Performance Engineering (ICPE). 2017.

If you like this article, you might also enjoy reading:

[1] Jose Manuel Redondo, Francisco Ortin. A Comprehensive Evaluation of Common Python Implementations. IEEE Software. 2015.
[2] Yepang Liu, Chang Xu, Shing-Chi Cheung. Diagnosing Energy Efficiency and Performance for Mobile Internetware Applications. IEEE Software. 2015.
[3] Francisco Ortin, Patricia Conde, Daniel Fernández Lanvin, Raúl Izquierdo. The Runtime Performance of invokedynamic: An Evaluation with a Java Library. IEEE Software. 2014.

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    Monday, July 10, 2017

    Crowdsourced Exploration of Mobile App Features: A Case Study of the Fort McMurray Wildfire

    By: Maleknaz Nayebi @MaleknazNayebi
    Associate editor: Federica Sarro @f_sarro


    Software products have an undeniable impact on people's daily life. However, software can only help if it matches user’s needs. Often, up to 80% of software features are never or almost never used. To bring the real impact into the society, understanding the specific needs of the users is critical. Social media provide such opportunity to a good extent.

    This is a post summarizing the main idea of an ICSE 2017 SEIS track paper titled "Crowdsourced exploration of mobile app features: a case study of the Fort McMurray wildfire". The two interviews complement the description and highlight the results. 

    We gathered the online communications of Albertans about Fort McMurray fire at the time of this crisis. People formed unofficial online support groups on Facebook and Twitter trying to distribute and reply to the needs of evacuees. For example, for sharing a car, and fuel, baby clothes, getting information about road traffic and gas station lineups, reporting incidents or criminal movements and so on they put a post on Twitter or Facebook and add #yymfire or #FortMcMurray fire hashtags. Then, other members following these hashtags offered them help. In the case of emergency situations (such as natural disaster or man-made attacks), a cell phone may suddenly become the victims only resources.

    We developed a method called MAPFEAT to gather and analyze social media posts. With MAPFEAT we elicit requirements from the unstructured communication and automatically map them into an app feature already existing in one of the apps of the whole app store. By evaluating these features through crowdsourcing, MAPFEAT ranks and prioritizes the app features that expect the highest match with user needs and thus should be included in a software application. 

    In the case of Fort McMurray fire, we analyzed almost 70,000 tweets and mapped them into app features using MAPFEAT. We compared the features we had with the features already existing in 26 emergency apps.  The results showed that none of the top 10 most essential features for victims is available in any of the 26 apps. Among top 40 essential features as we gathered, only six was provided by some of the existing wildfire apps. In total, we mined 144 features, and 85% of them were evaluated as essential and worthwhile by the general public.

    The mismatch between user’s requirements and software design is a well-known software engineering problem. With the lightweight and high capacity cell devices, now software engineering is, more than ever, a way to help people in solving problems. This would be only possible if we find solutions to involve the general public in the decision process.  

    Links to interviews:

    Fort McMurray wildfire tweets show key info missing during disasters: Alberta study

     Evacuees struggled for answers during Fort McMurray wildfire: U of C

    MAPFEAT is a series of analytical techniques and AI methods. For more information please refer to: Nayebi, M., Quapp, R., Ruhe, G., Marbouti, M., & Maurer, F. (2017, May). Crowdsourced exploration of mobile app features: a case study of the Fort McMurray wildfire. In Proceedings of the 39th International Conference on Software Engineering: Software Engineering in Society Track (pp. 57-66). IEEE Press.

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    Monday, June 26, 2017

    On the rise of Casual Contributions in postmodern Software Development - How does it impact Software Quality

    By: Naveen N Kulkarni
    Associate Editor: Sridhar Chimalakonda (@ChimalakondaSri)

    Postmodernism, a term used in variety of disciplines like arts, literature, fashion, music, movies and technology, is used to describe a tendency of philosophical movements and resulting shifts where there is a rejection of the predecessor. In case of software engineering too, the postmodernistic views have challenged the rigidity of traditional approaches; much like agile methods challenged the need for upfront requirement gathering, perpetual beta cycles where users are considered co-developers or heterogeneous application stack replaced with homogeneous stacks like Node.js and Vert.x. In case of collaboration in software development we see breaking the norm of controlled contributions to shared contributions to fragmented contributions combined with social underpinnings.

    In context of Open Source Software (OSS), empirical studies have shown that developers aim to rapidly deliver ’credible promises’ to keep their projects viable and active [Sojer, Haefliger]. With social interactions gaining popularity on the Internet, casual contributions (popularly known as pull requests on platforms such as, GitHub and BitBucket) to OSS is increasing. Empirical studies suggest that such contributions are not trivial, but involves bug fixes, refactoring and new features. While an OSS can deliver its promise faster with such requests, it can can quickly overwhelm the developers evaluating them whether to accept or not in case there are many. In order to deliver faster, it is intuitive that developers choose project relevance and code quality as the primary factors to evaluate the pull requests (substantiated in a recent survey by Gousios et al.). To minimize the effort, many OSS projects use strict policies that include discussions, linting, clean merge, tests and code reviews; most of which are automated through continuous integration tools. As the casual contributions can be unplanned and opportunistic, attempts are made by the development 1 2 team to understand the context of contribution through prior discussions. For example, in case of Scala, pull requests are accepted only if it is discussed on ’scala-internals’ mailing list. Also, mandatory discussions with more than one developers is required depending on the complexity of the contribution. All these are undertaken as a part of the quality assessment of the casual contribution. However, with such extensive checks and large volumes, the pull requests can quickly get stale, making it even harder for developers and contributors to understand the impact of composing multiple parallel contribution.

    Survey of work practices in managing and integrating pull request suggest that every contribution requires multiple code review sessions. This is substantiated by the fact that code reviews require ”code reading” to find defects, which is greatly dependent on individual expertise. Unfortunately, though they are perceived as a best practice, they are often localized and informal. Today’s code review session include interactive sessions, discussions and in-line comments. A study of modern code review process show that 35% of the review suggestions are discarded and 23% of the changes are applied after review (Beller M et al.). It is suggested that this process can be more people independent in postmodern software engineering. On the quality, there are very few qualitative evidences relating to code review process. Recent study by McIntosh et al. suggest that review coverage as an important factor to ensure quality. However, quality criteria are subjective during code reviews. Quality criteria is often restricted to statically analyzed source code using popular continuous integration tools (like Sonar or Squale), coding style and test cases.

    Despite the challenges, we observe casual contributions are raising. For example, at the time of writing this post, the rails and redis projects have nearly 500 open pull requests. The bootstrap, npm, tensorflow and docker have nearly 100 open pull requests. More detailed analysis on the growth of pull requests can be found at http://ghtorrent.org/pullreq-perf/ and https://octoverse.github.com/. As we adopt different approaches to compose software with frequent fragmented contributions, we are faced with challenges, such as emergent behavior, constraint violations and conflicting assumptions. These challenges arise due to the parallel and isolated nature of the contributions. Though these challenges are not new, we believe the current practices on quality assessments are inadequate to address them. The techniques used today help developers quickly spot local mismatches but they are not effective for comprehending global mismatches that originate due to many complex relationship among the software elements. In our initial study, we found similar evidence when a opportunistically reused external module not only violated the existing constraints, but also added unanticipated behavior making the software restrictive.

    Attempts to address the global mismatches using architectural reasoning and design decisions approaches have so far has met with limited success. Also, during code reviews are insufficient to highlight the ramifications of a contribution on the global constraints and mismatches. To overcome this issue, the merge process should extend beyond syntactic merge to include techniques for identifying constraint mismatches. We believe, by validating the constraint synthesized as predicates from the hot paths (critical execution flow) can optimally help validating the global mismatches. In past, predicate abstractions are effectively used for software verification (SLAM). On one hand, the predicate abstraction can facilitate theoretical guarantees, synthesizing the predicates can be overwhelming due to state explosion. To overcome this we can use descriptive statistical models (created from the features available in the source code) to choose a subset of predicates sufficient for the verification. Alternatively, mining of software repository techniques can play pivotal role in developing alternative approaches where they not only provide factual data, but help in decision process. Mining constraints as a set of sequential patterns (SPADE, a popular sequence mining algorithm) can be used where comparing sequence for dissimilarities between the source codes can suggest mismatches.

    There is a need for lightweight processes to cope with the dramatic shifts in the postmodern software engineering. In case of casual contributions, defining code quality can be confounding due to their inherent isolated nature. So, code reviews are critical and there is a need for alternative approaches that account for the various postmodern shifts. Without this the software quality in postmodern software development will remain elusive.

    References

    • SojerM, Henkel J. Code reuse in open source software development: quantitative evidence, drivers, and impediments. Journal of the Association for Information Systems 2010; 11(12):868901.
    •Stanciulescu S, Schulze S,Wasowski A. Forked and integrated variants in an open-source firmware project. Proceedings of the IEEE Int’l Conference on Software Maintenance and Evolution, ICSME 15, Bremen, Germany, 2015; 151160.
    • Perry DE, Siy HP, Votta LG. Parallel changes in large-scale software development: an observational case study. ACM Transactions on Software Engineering and Methodology (TOSEM) 2001; 10(3):308337.
    • Gousios G, Zaidman A, Storey MA, Deursen Av. Work Practices and Challenges in Pull-Based Development: The Integrators Perspective. Proceedings of the 37th International Conference on Software Engineering, 2015, vol. 1, pp. 358368.
    • Scala Pull request Policy, http://docs.scala-lang.org/scala/pull-request-policy.html, accessed 15-Mar-2017.
    • Pinto G, Steinmacher I, Gerosa MA. More common than you think: An in-depth study of casual contributors. Proceedings of the 23rd IEEE Intl Conference on Software Analysis, Evolution, and Reengineering, SANER 16, Suita, Osaka, Japan, 2016; pp. 112123. 4
    • Beller M, Bacchelli A, Zaidman A, Juergens E. Modern Code Reviews in Open-Source Projects: Which Problems Do They Fix? In Proceedings of Mining Software Repository, MSR’14, Hyderabad, India, 2014.
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